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@misc{Javier13,
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author = {D. Wunderlich},
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note = {\url{http://pille.iwr.uni-heidelberg.de/~kinect01/doc/classdescription.html#kinectcloud-section} [Stand 09. Februar 2014]},
}
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author = {Aptina},
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@misc{msdnskeletal,
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author = {Josep Forest i Collado},
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@article{Scharstein03,
author = {Daniel Scharstein and Richard Szeliski},
title = {High-Accuracy Stereo Depth Maps Using Structured Light},
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title={Bayesian Filtering for Location Estimation},
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title={Indoor Mobile Robot Localization using Probabilistic Multi-Sensor Fusion},
year={2007},
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pages={1-6},
keywords={feature extraction;mobile robots;sensor fusion;service robots;Hokuyo infrared range-finder;Polaroid 6500 ultrasonic rangers;feature extraction;indoor mobile robot localization;light refraction;mobile service robot;probabilistic multisensor fusion;servo sonar ring;Acoustic materials;Acoustic refraction;Acoustic sensors;Feature extraction;Indoor environments;Mobile robots;Sensor phenomena and characterization;Service robots;Servomechanisms;Sonar measurements},
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@ARTICLE{Luo11,
author={Luo, R.C. and Chih-Chia Chang and Chun Chi Lai},
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title={Multisensor Fusion and Integration: Theories, Applications, and its Perspectives},
year={2011},
IGNOREmonth={Dec},
volume={11},
number={12},
pages={3122-3138},
keywords={decision making;inference mechanisms;mechatronics;sensor fusion;autonomous mechatronic system;biomedical applications;classification methods;decision-making processes;estimation methods;inference methods;intelligent robots;microelectromechanical systems;military applications;multiple sensors;multisensor fusion and integration;nanoelectromechanical systems;Classification;Intelligent sensors;Kalman filters;Mechatronics;Robot sensing systems;Sensor fusion;Sensor systems;Classification methods;estimation methods;inference methods;intelligent robotics;mechatronics;multisensor fusion and integration (MFI)},
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title={Information fusion for indoor localization},
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pages={2083-2090},
keywords={belief networks;particle filtering (numerical methods);traffic information systems;Bayesian filter;cartographic constraints;indoor localization;information fusion;particle filter approximation;pedestrian user;proximity beacon measurements;Additive noise;Bayesian methods;Glands;Helium;Information filtering;Information filters;Information resources;Particle measurements;Position measurement;Telecommunications;cartographic constraints;information fusion;particle filtering;pedestrian navigation system (PNS);proximity beacon;ranging beacon},}
@inproceedings{golding99,
author={Golding, A.R. and Lesh, N.},
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title={Indoor Navigation Using a Diverse Set Of Cheap, Wearable Sensors},
year={1999},
IGNOREmonth={Oct},
pages={29-36},
keywords={accelerometers;computerised instrumentation;computerised navigation;force sensors;inference mechanisms;intelligent sensors;learning (artificial intelligence);magnetic sensors;magnetometers;optical sensors;sensor fusion;temperature sensors;user modelling;accelerometers;algorithm performance;context awareness;data cooking module;error rate;high-level features computation;indoor navigation algorithm;information integration;light sensors;machine learning;magnetometers;raw sensor signals;sensor input stream;temperature sensors;user location inference;user state inference;wearable sensors;Accelerometers;Context awareness;Error analysis;Machine learning;Magnetic sensors;Magnetometers;Navigation;Sensor phenomena and characterization;Temperature sensors;Wearable sensors},
doi={10.1109/ISWC.1999.806640},}
@inproceedings{meng11,
author={Wei Meng and Wendong Xiao and Wei Ni and Lihua Xie},
booktitle={Indoor Positioning and Indoor Navigation (IPIN), Int. Conf. on},
title={{Secure and Robust Wi-Fi Fingerprinting Indoor Localization}},
year={2011},
IGNOREmonth={Sept},
pages={1-7},
keywords={fingerprint identification;indoor radio;radio networks;telecommunication security;wireless LAN;K nearest neighbor algorithm;KNN;Wi-Fi wireless networks;access point attacks;distribution estimation;in-building communication infrastructures;indoor positioning;probabilistic fingerprinting localization method;random sample consensus;reference points;robust Wi-Fi fingerprinting indoor localization;secure Wi-Fi fingerprinting indoor localization;weighted-mean method;Accuracy;Distortion measurement;Histograms;IEEE 802.11 Standards;Probabilistic logic;Robustness;Sensors;RANSAC;Wi-Fi;fingerprinting;indoor localization;sensor network;signal strength;wireless network}, }
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author={Boonsriwai, S. and Apavatjrut, A.},
booktitle={Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON), 2013 10th Int. Conf. on},
title={Indoor WIFI localization on mobile devices},
year={2013},
IGNOREmonth={May},
pages={1-5},
keywords={Global Positioning System;buildings (structures);communication complexity;indoor radio;smart phones;wireless LAN;GPS;WIFI localization techniques;WIFI-enable devices;access points;building structures;computational complexity;fingerprinting localization techniques;indoor WIFI localization;localization algorithms;mobile devices;mobile users;multitrilateration;positioning calculation;reference position;signal degradation;smartphone;system resource consumption;wireless device;wireless signal;Accuracy;Buildings;Databases;Distance measurement;IEEE 802.11 Standards;Mobile communication;Mobile handsets},
doi={10.1109/ECTICon.2013.6559592},}
@inproceedings{Mirowsk13,
author={Mirowski, Piotr and Ho, Tin Kam and Saehoon Yi and MacDonald, Michael},
booktitle={Indoor Positioning and Indoor Navigation (IPIN), Int. Conf. on},
title={SignalSLAM: Simultaneous localization and mapping with mixed WiFi, Bluetooth, LTE and magnetic signals},
year={2013},
IGNOREmonth={Oct},
pages={1-10},
keywords={LTE;SLAM;WiFi;crowd-sourcing;kernel methods;localization},
doi={10.1109/IPIN.2013.6817853},}
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booktitle={Robotics and Automation (ICRA), 2010 IEEE Int. Conf. on},
title={WiFi localization and navigation for autonomous indoor mobile robots},
year={2010},
IGNOREmonth={May},
pages={4379-4384},
keywords={constraint theory;graph theory;mobile robots;path planning;sampling methods;signal detection;wireless LAN;WiFi localization;WiFi sensory data;autonomous indoor mobile robots;continuous perceptual model;custom built mobile robot;discrete graph based WiFi signal strength sampling;geometric constraints;Indoor environments;Mobile robots;Robot kinematics;Robot sensing systems;Robotics and automation;Robustness;Signal generators;Skeleton;Solid modeling;Sonar navigation},
doi={10.1109/ROBOT.2010.5509842},
ISSN={1050-4729},
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IGNOREmonth={Dec},
volume={14},
number={6},
pages={969-978},
keywords={collision avoidance;mobile robots;navigation;robot vision;self-adjusting systems;ultrasonic transducers;YAMABICO robot;mobile robot;obstacle avoidance;position correction system;robot vision;self-localization;single-camera vision;ultrasonic sensing;vision-based navigation;Cameras;Computer vision;Image edge detection;Intelligent robots;Laboratories;Mobile robots;Navigation;Orbital robotics;Robot sensing systems;Robot vision systems},
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booktitle={Computer Vision and Pattern Recognition (CVPR), 2010 IEEE Conf. on},
title={Real time motion capture using a single time-of-flight camera},
year={2010},
IGNOREmonth={June},
pages={755-762},
keywords={filtering theory;motion estimation;pose estimation;filtering algorithm;human pose markerless tracking;kinematic chain;local model-based search;monocular depth image;programmable graphics hardware;real time motion capture;single time-of-flight camera;unscented transform;Biological system modeling;Cameras;Computer science;Filtering algorithms;Graphics;Humans;Kinematics;Layout;Motion analysis;Tracking},
doi={10.1109/CVPR.2010.5540141},
ISSN={1063-6919},}
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author = {L. K{\"o}ping and M. Grzegorzek and F. Deinzer},
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doi={10.1109/TPAMI.2007.70770},
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@inproceedings{IAmTheAntenna,
author = {Zhang, Zengbin and Zhou, Xia and Zhang, Weile and Zhang, Yuanyang and Wang, Gang and Zhao, Ben Y. and Zheng, Haitao},
title = {I Am the Antenna: Accurate Outdoor AP Location using Smartphones},
booktitle = {Proc. of the 17th Annu. Int. Conf. on Mobile Computing and Networking},
IGNOREseries = {MobiCom '11},
year = {2011},
isbn = {978-1-4503-0492-4},
location = {Las Vegas, Nevada, USA},
pages = {109--120},
numpages = {12},
REMurl = {http://doi.acm.org/10.1145/2030613.2030626},
doi = {10.1145/2030613.2030626},
acmid = {2030626},
publisher = {ACM},
address = {New York, NY, USA},
keywords = {access point location, smartphones, wifi},
}
@article{IntroductionToRadio,
author={Friis, Harald T.},
journal={IEEE Spectrum},
title={{Introduction to Radio and Radio Antennas}},
year={1971},
volume={8},
number={4},
pages={55-61},
IGNOREdoi={10.1109/MSPEC.1971.5218045},
ISSN={0018-9235},
}
@article{ANoteOnASimpleTransmissionFormula,
author={Friis, Harald T.},
journal={Proc. of the IRE},
title={A Note on a Simple Transmission Formula},
year={1946},
volume={34},
number={5},
pages={254-256},
keywords={Capacitors;Circuits;Hazards;Laboratories;Lightning;Receiving antennas;Shape;Surges;Transmitting antennas;Voltage},
doi={10.1109/JRPROC.1946.234568},
ISSN={0096-8390},
}
@article{PathLossPredictionModelsForIndoor,
author={Seidel, Scott Y. and Rappaport, Theodore S.},
journal={IEEE Transactions on Antennas and Propagation},
title={{914 {MHz} Path Loss Prediction Models for Indoor Wireless Communications in Multifloored Buildings}},
year={1992},
volume={40},
number={2},
pages={207-217},
keywords={electromagnetic wave absorption;mobile radio systems;radiowave propagation;914 MHz;UHF;building layout;concrete walls;contour plots;floor attenuation factors;floors;indoor wireless communications;multifloored buildings;office partitions;path loss prediction models;radiowave propagation;site-specific models;Concrete;Floors;Loss measurement;Measurement standards;Narrowband;Predictive models;Propagation losses;Radio transmitters;Receivers;Wireless communication},
IGNOREdoi={10.1109/8.127405},
ISSN={0018-926X},
}
@book{teschl2,
title={Mathematik Fur Informatiker: Band 2: Analysis und Statistik},
author={Teschl, Gerald and Teschl, Susanne},
isbn={9783540724513},
IGNOREseries={Mathematik f{\"u}r Informatiker},
year={2007},
publisher={Springer},
address={Berlin},
edition={2},
totalpages={387},
}
@book{teschl1,
title={Mathematik Fur Informatiker: Band 1: Diskrete Mathematik und Lineare Algebra},
author={Teschl, Gerald and Teschl, Susanne},
isbn={9783540708247},
IGNOREseries={Mathematik f{\"u}r Informatiker},
year={2007},
publisher={Springer},
address={Berlin},
edition={2},
totalpages={510},
}
@book{WirelessNetworking,
title={Wireless Networking Technology: From Principles to Successful Implementation},
isbn={9780750667883 0750667885},
IGNOREurl={http://www.engineeringvillage.com/controller/servlet/OpenURL?genre=book&isbn=9780750667883},
language={English},
urldate={2013-10-15},
publisher={Elsevier, Newnes},
address={Burlington, {MA}},
author={Rackley, Steve},
year={2007},
}
% questionable....
% http://www.cse.buffalo.edu/srds2009/F2DA.html
@inproceedings{RssiUnreliable,
author={Parameswaran, Ambili T. and Husain, Mohammad I. and Upadhyaya, Shambhu},
title={Is RSSI a Reliable Parameter in Sensor Localization Algorithms: An Experimental Study},
booktitle={Proc. of the Field Failure Data Analysis Workshop (F2DA)},
address={New York, NY, USA},
year={2009},
}
%questionable...
@inproceedings{RssiAlgoComparison,
author = {Zanca, Giovanni and Zorzi, Francesco and Zanella, Andrea and Zorzi, Michele},
title = {Experimental comparison of RSSI-based localization algorithms for indoor wireless sensor networks},
booktitle = {Proc. of the workshop on Real-world wireless sensor networks},
IGNOREseries = {REALWSN '08},
year = {2008},
isbn = {9781605581231},
location = {Glasgow, Scotland},
pages = {1--5},
numpages = {5},
REMurl = {http://doi.acm.org/10.1145/1435473.1435475},
doi = {10.1145/1435473.1435475},
acmid = {1435475},
publisher = {ACM},
address = {New York, NY, USA},
keywords = {RSSI, WSN, experimental, localization, sensors, testbed},
}
@misc{PropagationLosses,
author = {Wilson, Robert},
IGNOREmonth = aug,
school = {University of Southern California},
title = {Propagation Losses Through Common Building Materials 2.4 GHz vs 5 GHz.},
hhowpublished = {\url{http://www.ko4bb.com/Manuals/05%29\_GPS\_Timing/E10589\_Propagation\_Losses\_2\_and\_5GHz.pdf}},
note = {last accessed 15.06.2015},
year = {2002},
}
@article{RssiHumanInteraction,
author = {Graham, Ben and Tachtatzis, Christos and Di Franco, Fabio and Bykowski, Marek and Tracey, David C. and Timmons, Nick F. and Morrison, Jim},
title = {Analysis of the Effect of Human Presence on a Wireless Sensor Network},
journal = {Int. Journal of Ambient Computing and Intelligence (IJACI)},
issue_date = {January 2011},
volume = {3},
number = {1},
IGNOREmonth = jan,
year = {2011},
issn = {1941-6237},
pages = {1--13},
numpages = {13},
REMurl = {http://dx.doi.org/10.4018/jaci.2011010101},
doi = {10.4018/jaci.2011010101},
acmid = {2433177},
publisher = {IGI Global},
address = {Hershey, PA, USA},
keywords = {Built Environment Networks (BENs), Human Presence, Node Placement, Radiation Patterns, Wireless Sensor Networks (WSNs)},
}
@inproceedings{PassiveLocalization,
author = {Youssef, Moustafa and Mah, Matthew and Agrawala, Ashok},
title = {Challenges: Device-free Passive Localization for Wireless Environments},
booktitle = {Proc. of the 13th Annu. Int. Conf. on Mobile Computing and Networking},
IGNOREseries = {MobiCom '07},
year = {2007},
isbn = {9781595936813},
location = {Montr\&\#233;al, Qu\&\#233;bec, Canada},
pages = {222--229},
numpages = {8},
REMurl = {http://doi.acm.org/10.1145/1287853.1287880},
doi = {10.1145/1287853.1287880},
acmid = {1287880},
publisher = {ACM},
address = {New York, NY, USA},
keywords = {device-free localization, passive localization, passive radio map},
}
@book{WirelessCommunications,
address = {Upper Saddle River, NJ, USA},
title = {Wireless Communications: Principles and Practice},
isbn = {0130422320 9780130422323},
shorttitle = {Wireless communications},
language = {English},
publisher = {Prentice Hall {PTR}},
author = {Rappaport, Theodore S.},
year = {2002}
}
@inproceedings{RssiReadingDifference,
author={Lui, Gough and Gallagher, Thomas and Li, Binghao and Dempster, Andrew G. and Rizos, Chris},
booktitle={Int. Conf. on Localization and GNSS},
title={Differences in RSSI Readings Made by Different Wi-Fi Chipsets: A Limitation of WLAN Localization},
year={2011},
pages={53-57},
keywords={UHF integrated circuits;microwave integrated circuits;mobile computing;wireless LAN;RSSI reading;WLAN localization;Wi-Fi chipset;Wi-Fi fingerprinting positioning systems;Wi-Fi location;frequency 2.4 GHz;frequency 5 GHz;received signal strength indicator;Accuracy;Calibration;Fingerprint recognition;IEEE 802.11 Standards;Performance evaluation;Testing;Wireless communication;RSSI differences;WLAN localization;Wi-Fi chipsets;fingerprinting;limitations},
doi={10.1109/ICL-GNSS.2011.5955283},
}
% influence of the human body on signal propagation
@inproceedings{RadiationProperties,
author = {Tuovinen, Tommi and Berg, Markus and Yazdandoost, Kamya Y. and Salonen, Erkki and Linatti, Jari},
title = {Radiation Properties of the Planar UWB Dipole Antenna in the Proximity of Dispersive Body Models},
booktitle = {Proc. of the 7th Int. Conf. on Body Area Networks},
IGNOREseries = {BodyNets '12},
year = {2012},
isbn = {9781936968602},
location = {Oslo, Norway},
pages = {82--88},
numpages = {7},
REMurl = {http://dl.acm.org/citation.cfm?id=2442691.2442713},
acmid = {2442713},
publisher = {Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering (ICST)},
address = {Brussels, Belgium},
keywords = {UWB WBAN systems, UWB dipole antenna, human body effect, reflections},
}
% about all types of antennas
@book{PracticalAntennaHandbook,
title={Practical Antenna Handbook},
author={Carr, Joseph J.},
publisher={McGraw-Hill},
address = {New York, NY, USA},
year={2001},
IGNOREmonth={5},
edition={4},
isbn={9780071374354 0071389318},
totalpages={608},
timestamp={2013.10.16},
}
% reflection, diffraction, gain, scattering, ...
@book{CertifiedWirelessNetworkAdmin,
title={CWNA Certified Wireless Network Administrator Official Study Guide (Exam PW0-100)},
author={Carpenter, Tom and Barrett, Joel},
publisher={McGraw-Hill Osborne Media},
address={New York, NY, USA},
year={2007},
IGNOREmonth={8},
edition={4},
isbn={9780071494908},
REMurl={http://amazon.com/o/ASIN/0071494901/},
totalpages={644},
timestamp={2013.10.16},
}
% ieee standard for 802.11 (revision 2007)
@Manual{ieee80211,
author={IEEE},
journal={IEEE Std 802.11-2007 (Revision of IEEE Std 802.11-1999)},
INGOREtitle={Standard for Information Technology - Telecommunications and Information Exchange Between Systems - Local and Metropolitan Area Networks - Specific Requirements - Part 11: Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications},
title={Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications},
organization = {Institute of Electrical and Electronics Engineers, Inc.},
year={2007},
pages={1-1076},
publisher={IEEE Computer Society},
address = {New York, NY, USA},
doi={10.1109/IEEESTD.2007.373646},}
}
% ieee standard for 802.11 (revision 2012)
@Manual{ieee80211_2012,
author={IEEE},
journal={IEEE Std 802.11-2012 (Revision of IEEE Std 802.11-2007)},
IGNOREtitle={Standard for Information technology -- Telecommunications and information exchange between systems Local and metropolitan area networks -- Specific requirements - Part 11: Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications},
title={Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications},
organization = {Institute of Electrical and Electronics Engineers, Inc.},
IGNOREmonth={3},
year={2012},
pages={1-2793},
publisher={IEEE Computer Society},
address = {New York, NY, USA},
doi={10.1109/IEEESTD.2012.6178212},
}
% using some phy-layer info of intel cards as fingerprint metric instead of rssi
@inproceedings{PhyLayerFingerprints,
author = {Sen, Souvik and Radunovic, Bo\v{z}idar and Choudhury, Romit Roy and Minka, Tom},
title = {You are facing the Mona Lisa: spot localization using PHY layer information},
booktitle = {Proc. of the 10th Int. Conf. on Mobile Systems, Applications, and Services},
IGNOREseries = {MobiSys '12},
year = {2012},
isbn = {9781450313018},
location = {Low Wood Bay, Lake District, UK},
pages = {183--196},
numpages = {14},
REMurl = {http://doi.acm.org/10.1145/2307636.2307654},
doi = {10.1145/2307636.2307654},
acmid = {2307654},
publisher = {ACM},
address = {New York, NY, USA},
keywords = {application, cross-layer, localization, wireless},
}
% fingerprinting using robots
@inproceedings{robotFingerprinting,
title = {Autonomous RF Surveying Robot for Indoor Localization and Tracking},
author = {Palaniappan, Ravishankar and Mirowski, Piotr and Ho, Tin Kam and Steck, Harald and Whiting, Philip and MacDonald, Michael},
booktitle = {Indoor Positioning and Indoor Navigation (IPIN), Int. Conf. on},
numpages = {4},
year = {2011},
IGNOREmonth = {9},
location = {Guimarães, Portugal},
}
% one of THE two sources for wifi location
@inproceedings{radar,
author={Bahl, Paramvir and Padmanabhan, Venkata N.},
booktitle={Proc. of the 19th Annu. Joint Conf. of the IEEE Computer and Communications Societies},
title={{RADAR: An In-Building RF-based User Location and Tracking System}},
year={2000},
volume={2},
pages={775-784},
}
% 1000 scans per fingerprint, histogram, interpolation
@inproceedings{secureAndRobust,
author={Meng, Wei and Xiao, Wendong and Ni, Wei and Xie, Lihua},
booktitle={Indoor Positioning and Indoor Navigation (IPIN), Int. Conf. on},
title={Secure and Robust Wi-Fi Fingerprinting Indoor Localization},
year={2011},
pages={1-7},
keywords={fingerprint identification;indoor radio;radio networks;telecommunication security;wireless LAN;K nearest neighbor algorithm;KNN;Wi-Fi wireless networks;access point attacks;distribution estimation;in-building communication infrastructures;indoor positioning;probabilistic fingerprinting localization method;random sample consensus;reference points;robust Wi-Fi fingerprinting indoor localization;secure Wi-Fi fingerprinting indoor localization;weighted-mean method;Accuracy;Distortion measurement;Histograms;IEEE 802.11 Standards;Probabilistic logic;Robustness;Sensors;RANSAC;Wi-Fi;fingerprinting;indoor localization;sensor network;signal strength;wireless network},
doi={10.1109/IPIN.2011.6071908},
}
% some attunuation factors, propagation models, etc.
@inproceedings{PropagationModelling,
author={El-Kafrawy, Kareem and Youssef, Moustafa and El-Keyi, Amr and Naguib, Ayman},
booktitle={Vehicular Technology Conf. (VTC)},
title={{Propagation Modeling for Accurate Indoor WLAN RSS-Based Localization}},
year={2010},
pages={1-5},
}
@article{ElectromagneticPropagation,
author={Richalot, Elodie and Bonilla, Matthieu and Wong, Man-Fai and Fouad-Hanna, Victor and Baudrand, Henri and Wiart, Joe},
journal={IEEE Transactions on Microwave Theory and Techniques},
title={Electromagnetic Propagation into Reinforced-Concrete Walls},
year={2000},
volume={48},
number={3},
pages={357-366},
keywords={UHF radio propagation;concrete;electromagnetic wave propagation;finite element analysis;indoor radio;mobile radio;1800 MHz;900 MHz;EM propagation;EM properties;FEM;Floquet modes;angle of arrival;building construction materials;buildings walls;diffused field;electromagnetic properties;expansion of fields;finite-element techniques;reflection characteristics;reinforced-concrete walls;transmission characteristics;wireless communication system design;Building materials;Concrete;Electromagnetic propagation;Electromagnetic reflection;Finite element methods;Fresnel reflection;Ray tracing;Slabs;Steel;Wireless communication},
doi={10.1109/22.826834},
ISSN={0018-9480},
}
% LAN - background
@book{CCNA,
title={CCNA Cisco Certified Network Associate Study Guide (Exam 640-802)},
author={Deal, Richard},
publisher={McGraw-Hill},
address={New York, NY, USA},
isbn={0071643737 9780071643733},
IGNOREseries={Certification Press},
year={2008},
pages={983},
}
@misc{VAP1,
title={Virtual Access Points},
author={Kittappa, Thenu},
IGNOREurl={http://community.arubanetworks.com/aruba/attachments/aruba/115/1358/1/AppNote.MultipleBSSIDs.pdf},
IGNOREnote={\url{http://community.arubanetworks.com/aruba/attachments/aruba/115/1358/1/AppNote.MultipleBSSIDs.pdf}},
howpublished={\url{http://community.arubanetworks.com/aruba/attachments/aruba/115/1358/1/AppNote.MultipleBSSIDs.pdf}},
note={zuletzt abgerufen am 28.11.2013},
pages={13},
year={2006},
}
% reference points to reset errors, automatic floorplan generation, backend-phase
@inproceedings{crowdinside,
author = {Alzantot, Moustafa and Youssef, Moustafa},
title = {CrowdInside: Automatic Construction of Indoor Floorplans},
booktitle = {Proc. of the 20th Int. Conf. on Advances in Geographic Information Systems},
IGNOREseries = {SIGSPATIAL '12},
year = {2012},
isbn = {978-1-4503-1691-0},
location = {Redondo Beach, California},
pages = {99--108},
numpages = {10},
REMurl = {http://doi.acm.org/10.1145/2424321.2424335},
doi = {10.1145/2424321.2424335},
acmid = {2424335},
publisher = {ACM},
address = {New York, NY, USA},
keywords = {alpha-shapes, automatic floorplan construction, crowdsourcing},
}
% gradientenverfahren
@book{NumerischeMethoden,
title={Numerische Methoden: Eine Einführung für Informatiker, Naturwissenschaftler, Ingenieure und Mathematiker},
author={Huckle, Thomas and Schneider, Stefan},
publisher={Springer},
address={Berlin},
year={2006},
IGNOREmonth={3},
edition={2},
isbn={9783540303169},
REMurl={http://amazon.com/o/ASIN/3540303162/},
totalpages={385},
}
% optimization, downhill-simplex
% https://portal.dnb.de/opac.htm?query=978-3-8348-2011-2&method=simpleSearch
@book{GrundlagenDerMathOptimierung,
title={Grundlagen der Mathematischen Optimierung: Diskrete Strukturen, Komplexitätstheorie, Konvexitätstheorie, Lineare Optimierung, Simplex-Algorithmus, Dualität},
author={Gritzmann, Peter},
isbn={9783834820112},
IGNOREseries={Aufbaukurs Mathematik},
year={2013},
publisher={Springer Fachmedien},
address={Wiesbaden},
totalpages={525},
}
% basics on numerical optimization
% https://portal.dnb.de/opac.htm?method=showFullRec.&currentResultId=978-3-8274-2949-0%26any&currentPosition=0
@book{REMNichtlineareOptimierung,
title={Nichtlineare Optimierung: Theorie, Numerik und Experimente},
author={Reinhardt, Rüdiger and Hoffmann, Armin and Gerlach, Tobias},
publisher={Springer},
address={Berlin},
year={2013},
isbn={9783827429490},
totalpages={383},
}
% original downhill-simplex source
@article{downhillSimplex1,
author={Powell, Michael J. D.},
title={An iterative method for finding stationary values of a function of several variables},
issn={1460-2067},
journal={The Computer Journal},
volume={5},
number={2},
pages={147--151},
publisher={Oxford University Press},
year={1962},
IGNOREmonth={8},
}
% modified downhill-simplex source
@article{downhillSimplex2,
title={A Simplex Method for Function Minimization},
author={Nelder, John A. and Mead, Roger},
issn={1460-2067},
journal={The Computer Journal},
volume={7},
number={4},
pages={308--313},
publisher={Oxford University Press},
year={1965},
IGNOREmonth={1},
}
% lateration, linearization, numerical errors, LIST OF OTHER METRICS INSTEAD OF RSSI?
@inproceedings{LaterationLinear,
author={Li, Zang and Trappe, Wade and Zhang, Yanyong and Nath, Badri},
booktitle={Proc. of the 4th Int. Symp. on Information Processing in Sensor Networks},
title={Robust Statistical Methods for Securing Wireless Localization in Sensor Networks},
year={2005},
pages={91-98},
publisher = {IEEE Press},
address = {Piscataway, NJ, USA},
doi={10.1109/IPSN.2005.1440903},
}
% gps lateration and history
@book{REMSatellitennavigation,
title={Satellitennavigation },
author={Dodel, Hans and Häupler, Dieter},
publisher={Springer},
address={Heidelberg},
year={2010},
edition={2},
isbn={9783540794448},
totalpages={531},
}
% localization without a-priori knowledge
@inproceedings{WithoutThePain,
author = {Chintalapudi, Krishna and Padmanabha Iyer, Anand and Padmanabhan, Venkata N.},
title = {Indoor Localization Without the Pain},
booktitle = {Proc. of the 16th Annu. Int. Conf. on Mobile Computing and Networking},
IGNOREseries = {MobiCom '10},
year = {2010},
isbn = {978-1-4503-0181-7},
location = {Chicago, Illinois, USA},
pages = {173--184},
numpages = {12},
publisher = {ACM},
address = {New York, NY, USA},
}
% about lateration using RSSI and possible errors
@article{PositionEstimationRssi,
author={Pu, Chuan-Chin and Chung, Wan-Young},
title={An Integrated Approach for Position Estimation using RSSI in Wireless Sensor Network},
journal={Journal of Ubiquitous Convergence Technology},
pages={78--87},
volume={2},
number={2},
IGNOREmonth={11},
year={2008},
}
% about lateration, rssi, convenience, errors
% http://www.iaeng.org/publication/IMECS2009/
@inproceedings{AccuracyOfRssi,
title={Accuracy of Location Identification with Antenna Polarization on RSSI},
author={Huang, Xu and Barralet, Mark and Sharma, Dharmendra},
booktitle={Proc. of the Int. MultiConf. of Engineers and Computer Scientists},
year={2009},
volume={1},
publisher={Newswood Limited},
address={Hong Kong},
ISBN={9789881701220},
pages={542--546},
}
% basics about TDOA
@inproceedings{TimeDifferenceOfArrival1,
author={Khanzada, T. J. S. and Ali, A.R. and Omar, A.S.},
title={Time Difference of Arrival estimation using super resolution algorithms to minimize Distance Measurement Error for indoor positioning systems},
booktitle={IEEE Int. Multitopic Conf.},
year={2008},
pages={443-447},
}
% TOA and AOA explained
@inproceedings{TOAAOA,
author = {Deligiannis, Nikos and Louvros, Spiros and Kotsopoulos, Stavros},
title = {Optimizing Location Positioning Using Hybrid TOA-AOA Techniques in Mobile Cellular Networks},
booktitle = {Proc. of the 3rd Int. Conf. on Mobile Multimedia Communications},
IGNOREseries = {MobiMedia '07},
IGNOREmonth={8},
year = {2007},
isbn = {9789630626705},
location = {Nafpaktos, Aitolokarnania, Greece},
IGNOREpages = {20:1--20:7},
articleno = {20},
numpages = {7},
publisher = {ICST},
address = {Brussels, Belgium},
}
% errors during euclid distance, sensor fusion with beeps, antenna-position
@inproceedings{PushTheLimit,
author = {Liu, Hongbo and Gan, Yu and Yang, Jie and Sidhom, Simon and Wang, Yan and Chen, Yingying and Ye, Fan},
title = {Push the Limit of WiFi based Localization for Smartphones},
booktitle = {Proc. of the 18th Annu. Int. Conf. on Mobile Computing and Networking},
IGNOREseries = {Mobicom '12},
year = {2012},
isbn = {9781450311595},
location = {Istanbul, Turkey},
pages = {305--316},
numpages = {12},
acmid = {2348581},
publisher = {ACM},
address = {New York, NY, USA},
}
% lateration and rssi smoothing
@inproceedings{EnhancedRssi,
author = {Lau, Erin-Ee-Lin and Chung, Wan-Young},
title = {Enhanced RSSI-Based Real-Time User Location Tracking System for Indoor and Outdoor Environments},
booktitle = {Proc. of the 2007 Int. Conf. on Convergence Information Technology},
IGNOREseries = {ICCIT '07},
year = {2007},
isbn = {0-7695-3038-9},
pages = {1213--1218},
numpages = {6},
acmid = {1335696},
publisher = {IEEE Computer Society},
address = {Washington, DC, USA},
}
% probabilistic, parzen, histogram, squared error
@article{ProbabilisticWlan,
author={Roos, Teemu and Myllym\"{a}ki, Petri and Tirri, Henry and Misikangas, Pauli and Siev\"{a}nen, Juha},
title={{A Probabilistic Approach to WLAN User Location Estimation}},
journal = {Int. Journal of Wireless Information Networks},
pages = {155--164},
volume={9},
number={3},
IGNOREmonth={7},
year={2002},
}
% the 2nd great source for indoor localization
@inproceedings{horus,
author = {Youssef, Moustafa and Agrawala, Ashok},
title = {The Horus WLAN Location Determination System},
booktitle = {Proc. of the 3rd Int. Conf. on Mobile Systems, Applications, and Services},
IGNOREseries = {MobiSys '05},
year = {2005},
isbn = {1-931971-31-5},
location = {Seattle, Washington},
pages = {205--218},
numpages = {14},
REMurl = {http://doi.acm.org/10.1145/1067170.1067193},
doi = {10.1145/1067170.1067193},
acmid = {1067193},
publisher = {ACM},
address = {New York, NY, USA},
}
% bayes, normal-distribution, histogram, statistical independence of APs, ...
@inproceedings{WlanLocationDetermination,
author = {Youssef, Moustafa A. and Agrawala, Ashok and Shankar, A. Udaya},
title = {WLAN Location Determination via Clustering and Probability Distributions},
booktitle = {Proc. of the First IEEE Int. Conf. on Pervasive Computing and Communications},
IGNOREseries = {PERCOM '03},
year = {2003},
isbn = {0-7695-1893-1},
pages = {143-150},
REMurl = {http://dl.acm.org/citation.cfm?id=826025.826335},
acmid = {826335},
publisher = {IEEE Computer Society},
address = {Washington, DC, USA},
}
% the source for particle filtering and other stuff
@book{robotics,
title={Probabilistic Robotics},
author={Thrun, Sebastian and Burgard, Wolfram and Fox, Dieter},
publisher={The MIT Press},
address = {Cambridge, MA, USA},
year={2005},
IGNOREmonth={8},
isbn={9780262201629},
totalpages={672},
}
% path-loss-reference
@inproceedings{PotentialRisks,
author = {Jung, Wook Rak and Bell, Scott and Petrenko, Anastasia and Sizo, Anton},
title = {Potential Risks of WiFi-based Indoor Positioning and Progress on Improving Localization Functionality},
booktitle = {Proc. of the Fourth ACM SIGSPATIAL Int. Workshop on Indoor Spatial Awareness},
IGNOREseries = {ISA '12},
year = {2012},
isbn = {978-1-4503-1697-2},
location = {Redondo Beach, California},
pages = {13--20},
numpages = {8},
REMurl = {http://doi.acm.org/10.1145/2442616.2442621},
doi = {10.1145/2442616.2442621},
acmid = {2442621},
publisher = {ACM},
address = {New York, NY, USA},
keywords = {SaskEPS, WPS, indoor positioning, map-matching},
}
% some path-loss exponents for the log-distance model
@article{ANewPathLossPrediction,
title={A new path loss prediction statistical model for indoor wireless communications},
author={Polydorou, D. S. and Capsalis, C. N.},
journal={Int. Journal of Infrared and Millimeter Waves},
publisher={Plenum Publishing Corporation},
address={New York, NY, USA},
volume={15},
number={1},
year={1994},
pages={201--228},
}
% signal-strength prediction for coverage, furniture impact, raytracing
@article{PredictingRFCoverage,
author={Rajkumar, A. and Naylor, B. F. and Feisullin, F. and Rogers, L.},
title={{Predicting RF Coverage in Large Environments using Ray-beam Tracing and Partitioning Tree Represented Geometry}},
journal={Wireless Networks},
issue_date={June 1996},
volume={2},
number={2},
IGNOREmonth={6},
year={1996},
issn={1022-0038},
pages={143--154},
numpages={12},
REMurl={http://dx.doi.org/10.1007/BF01225637},
IGNOREdoi={10.1007/BF01225637},
acmid={234826},
publisher={Springer-Verlag New York, Inc.},
address={Secaucus, NJ, USA},
}
@book{IntroductionToRF,
title={Introduction to RF Propagation},
author={Seybold, John S.},
publisher={Wiley-Interscience},
address={Hoboken, NJ, USA},
year={2005},
IGNOREmonth={9},
IGNOREedition={1},
isbn={9780471655961},
REMurl={http://amazon.com/o/ASIN/0471655961/},
totalpages={352},
}
% what to do with missing map APs
@inproceedings{AccuracyCharacterization,
author = {Cheng, Yu-Chung and Chawathe, Yatin and LaMarca, Anthony and Krumm, John},
title = {Accuracy Characterization for Metropolitan-scale Wi-Fi Localization},
booktitle = {Proc. of the 3rd Int. Conf. on Mobile Systems, Applications, and Services},
IGNOREseries = {MobiSys '05},
year = {2005},
isbn = {1-931971-31-5},
location = {Seattle, Washington},
pages = {233--245},
numpages = {13},
REMurl = {http://doi.acm.org/10.1145/1067170.1067195},
doi = {10.1145/1067170.1067195},
acmid = {1067195},
publisher = {ACM},
address = {New York, NY, USA},
}
% THE dsp guide
@book{dsp,
title={The Scientist and Engineer's Guide to Digital Signal Processing},
author={Smith, Steven W.},
publisher={California Technical Publishing},
address={San Diego, CA, USA},
year={1999},
edition={2},
isbn={9780966017649},
REMurl={http://amazon.com/o/ASIN/0966017641/},
totalpages={650},
}
% differential RSSI measurements
@article{differentialRssi,
author={Wang, Jie and Gao, Qinghua and Wang, Hongyu and Chen, Hongyang and Jin, Minglu},
title={Differential radio map-based robust indoor localization},
journal={EURASIP Journal on Wireless Communications and Networking},
publisher={Springer},
address={Heidelberg},
pages={12},
volume={2011},
number={1},
year={2011},
}
% probability, log, noise effects, etc.
% http://books.google.de/books/about/An_introduction_to_the_theory_of_random.html?id=meFSAAAAMAAJ&redir_esc=y
@book{RandomSignalsAndNoise,
title={An Introduction to the Theory of Random Signals and Noise},
author={Davenport, Wilbur B. Jr. and Root, William L.},
publisher={McGraw-Hill},
address = {New York, NY, USA},
year={1958},
totalpages={393},
}
% distance between fingerprints and its impact
@inproceedings{LocatingInFingerprintSpace,
author = {Yang, Zheng and Wu, Chenshu and Liu, Yunhao},
title = {Locating in Fingerprint Space: Wireless Indoor Localization with Little Human Intervention},
booktitle = {Proc. of the 18th Annu. Int. Conf. on Mobile Computing and Networking},
IGNOREseries = {Mobicom '12},
year = {2012},
isbn = {978-1-4503-1159-5},
location = {Istanbul, Turkey},
pages = {269--280},
numpages = {12},
REMurl = {http://doi.acm.org/10.1145/2348543.2348578},
doi = {10.1145/2348543.2348578},
acmid = {2348578},
publisher = {ACM},
address = {New York, NY, USA},
keywords = {RSS fingerprint, floor plan, indoor localization, site survey, smartphones},
}
% different kernel density functions
@article{kernel1,
author = {Gerani, Shima and Carman, Mark and Crestani, Fabio},
title = {Aggregation Methods for Proximity-Based Opinion Retrieval},
journal = {ACM Transactions on Information Systems},
issue_date = {November 2012},
volume = {30},
number = {4},
IGNOREmonth = {11},
year = {2012},
issn = {1046-8188},
IGNOREpages = {26:1--26:36},
articleno = {26},
numpages = {36},
REMurl = {http://doi.acm.org/10.1145/2382438.2382445},
doi = {10.1145/2382438.2382445},
acmid = {2382445},
publisher = {ACM},
address = {New York, NY, USA},
keywords = {Opinion, blog, proximity, retrieval, sentiment},
}
% log probability (scaling)
@inproceedings{LogLinearModels,
author = {Smith, David A. and Eisner, Jason},
title = {Minimum Risk Annealing for Training Log-linear Models},
booktitle = {Proc. of the COLING/ACL on Main Conf. Poster Sessions},
series = {COLING-ACL '06},
year = {2006},
location = {Sydney, Australia},
pages = {787--794},
numpages = {8},
REMurl = {http://dl.acm.org/citation.cfm?id=1273073.1273174},
acmid = {1273174},
publisher = {Association for Computational Linguistics},
address = {Stroudsburg, PA, USA},
}
% explains the additional parameter after the path loss model
@article{empiricalPathLossModel,
author = {Erceg, V. and Greenstein, L. J. and Tjandra, S. Y. and Parkoff, S. R. and Gupta, A. and Kulic, B. and Julius, A. A. and Bianchi, R.},
title = {{An Empirically Based Path Loss Model for Wireless Channels in Suburban Environments}},
journal = {IEEE Journal on Selected Areas in Communications},
issue_date = {September 2006},
volume = {17},
number = {7},
IGNOREmonth = sep,
year = {2006},
issn = {0733-8716},
pages = {1205--1211},
numpages = {7},
REMurl = {http://dx.doi.org/10.1109/49.778178},
IGNOREdoi = {10.1109/49.778178},
acmid = {2313013},
publisher = {IEEE Press},
address = {Piscataway, NJ, USA},
}
% FHWS Journal
@ARTICLE{Koeping14-ILU,
author={K{\"o}ping, Lukas and Ebner, Frank and Grzegorzek, Marcin and Deinzer, Frank},
title={{Indoor Localization Using Step and Turn Detection Together with Floor Map
Information}},
journal={FHWS Science Journal},
publisher={University of Applied Sciences W{\"u}rzburg - Schweinfurt},
address={W{\"u}rzburg},
numpages={9},
volume={},
number={},
year={2014},
}
@inproceedings{Koeping14-PSA,
author = {Lukas K\"{o}ping and Marcin Grzegorzek and Frank Deinzer},
title = {{Probabilistic Step and Turn Detection in Indoor Localization}},
booktitle = {Conf. on Data Fusion and Target Tracking 2014: Algorithms and Applications (DFTT 2014)},
year = {2014},
IGNOREmonth = {April},
address = {Liverpool, UK},
pages = {1-7},
}
@article{Deinzer09:AFF,
author = {Frank Deinzer and Christian Derichs and Heinrich Niemann and Joachim Denzler},
title = {{A Framework for Actively Selecting Viewpoints in Object Recognition}},
journal = {Int. Journal of Pattern Recognition and Artificial Intelligence},
year = {2009},
IGNOREmonth = {June},
volume = {23},
number = {4},
pages = {765-799},
}
@book{Deinzer05:OAI,
author = {Frank Deinzer},
title = {Optimale Ansichtenauswahl in der aktiven Objekterkennung},
publisher = {Logos Verlag Berlin},
series = {Studien zur Mustererkennung},
volume = {20},
year = {2005},
}
@article{Link11:FAM,
author = {Jo Agila Bitsch Link and Paul Smith and Klaus Wehrle},
title = {FootPath: Accurate map-based indoor navigation using smartphones},
journal = {Indoor Positioning and Indoor Navigation (IPIN), Int. Conf. on},
year = {2011},
IGNOREmonth = {September},
pages = {1-8},
}
@inproceedings{gradientDescent,
author={Mofarreh-Bonab, Mostafa and Ghorashi, Seyed Ali},
booktitle={3th Int. eConf. on Computer and Knowledge Engineering (ICCKE)},
title={A low complexity and high speed gradient descent based secure localization in Wireless Sensor Networks},
year={2013},
IGNOREmonth={Oct},
pages={300-303},
keywords={gradient methods;iterative methods;least mean squares methods;telecommunication network routing;telecommunication security;wireless sensor networks;LMdS;WSN;fault probability;gradient based method;gradient descent algorithm;gradient descent based secure localization;high speed gradient descent based secure localization;iterative algorithms;least median square;localization;localization error;monitoring applications;network quality;routing;voting based secure localization;wireless sensor networks;Estimation;Monitoring;Robustness;Wireless sensor networks;gradient based localization;iterative algorithm;secure localization},
doi={10.1109/ICCKE.2013.6682841},}
@article{Godsill04:MCS,
author = {Simon J. Godsill and Arnaud Doucet and Mike West},
title = {{Monte Carlo Smoothing for Nonlinear Time Series}},
journal = {Journal of the American Statistical Association},
year = {2004},
IGNOREmonth = {March},
volume = {99},
number = {465},
pages = {156-168},
}
@inproceedings{Mizell03-UGT,
author={Mizell, D.},
booktitle={Wearable Computers, 2003. Proc. of the Seventh IEEE Int. Symp. on},
title={{Using gravity to estimate accelerometer orientation}},
year={2003},
IGNOREmonth={October},
pages={252-253},
}
@inproceedings{Kunze09-WWA,
author={Kunze, K. and Lukowicz, P. and Partridge, K. and Begole, B.},
booktitle={Wearable Computers, 2009. ISWC '09. Int. Symp. on},
title={{Which Way Am I Facing: Inferring Horizontal Device Orientation from an Accelerometer Signal}},
year={2009},
IGNOREmonth={September},
pages={149-150},
}
@inproceedings{Steinhoff10-DRF,
author={Steinhoff, U. and Schiele, B.},
booktitle={Pervasive Computing and Communications (PerCom), 2010 IEEE Int. Conf. on},
title={{Dead reckoning from the Pocket - An Experimental Study}},
year={2010},
IGNOREmonth={March},
pages={162-170},
}
@inproceedings{Binghao13-UBI,
author={Binghao Li and Harvey, B. and Gallagher, T.},
booktitle={Indoor Positioning and Indoor Navigation (IPIN), Int. Conf. on},
title={{Using Barometers to Determine the Height for Indoor Positioning}},
year={2013},
IGNOREmonth={Oct},
pages={1-7},
}
@inproceedings{Nurminen13-PSI,
author={Nurminen, H. and Ristimaki, A. and Ali-Loytty, S. and Piche, R.},
booktitle={Indoor Positioning and Indoor Navigation (IPIN), Int. Conf. on},
title={{Particle Filter and Smoother for Indoor Localization}},
year={2013},
IGNOREmonth={October},
pages={1-10},
}
@inproceedings{Willemsen15,
author={Willemsen, T. and Keller, F. and Sternberg, H.},
booktitle={Indoor Positioning and Indoor Navigation (IPIN), Int. Conf. on},
title={A Topological Approach with MEMS in Smartphones based on Routing-Graph},
year={2015},
IGNOREmonth={October},
pages={1-6},
}
@inproceedings{Muralidharan14-BPS,
author = {Muralidharan, Kartik and Khan, Azeem Javed and Misra, Archan and Balan, Rajesh Krishna and Agarwal, Sharad},
title = {Barometric Phone Sensors: More Hype Than Hope!},
booktitle = {Proc. of the 15th Workshop on Mobile Computing Systems and Applications},
year = {2014},
isbn = {978-1-4503-2742-8},
location = {Santa Barbara, California},
pages = {12:1--12:6},
}
@inproceedings{Graph1,
author={Tian, J. and H{\"a}hner, J. and Becker, C. and Stepanov, I. and Rothermel, K.},
booktitle={Simulation Symp., 2002. Proc. of the 35th Annu.},
title={Graph-based Mobility Model for Mobile ad-hoc Network Simulation},
year={2002},
IGNOREmonth={April},
pages={337-344},
keywords={graph theory;mobile communication;mobile computing;protocols;telecommunication network routing;ad hoc routing protocols;graph-based mobility model;mobile ad hoc network;mobile ad hoc networks;random walk model;realistic movement;routing protocols;spatial constraints;Brain modeling;Cities and towns;Electronic mail;Mobile ad hoc networks},
doi={10.1109/SIMSYM.2002.1000171},
ISSN={1082-241X},}
@inproceedings{Brajdic-WDS13,
author = {Brajdic, Agata and Harle, Robert},
title = {Walk Detection and Step Counting on Unconstrained Smartphones},
booktitle = {Proc. of the 2013 ACM Conf. on Ubiquitous Computing},
year = {2013},
IGNOREmonth = {September},
isbn = {978-1-4503-1770-2},
location = {Zurich, Switzerland},
pages = {225--234},
}
@inproceedings{Li12-ARA,
author = {Li, Fan and Zhao, Chunshui and Ding, Guanzhong and Gong, Jian and Liu, Chenxing and Zhao, Feng},
title = {{A reliable and accurate indoor localization method using phone inertial sensors}},
booktitle = {Proc. of the 2012 ACM Conf. on Ubiquitous Computing},
year = {2012},
IGNOREmonth = {September},
pages = {421--430},
}
@article{Woodman08-PLF,
author = {Oliver Woodman and Robert Harle},
title = {{Pedestrian Localisation for Indoor Environments}},
journal = {Proc. of the 10th Int. Conf. on Ubiquitous Computing},
year = {2008},
IGNOREmonth = {September},
pages = {114-123},
}
@inproceedings{Blanchert09-IFF,
author={Blanchart, P. and Liyun He and Le Gland, F.},
title={{Information Fusion for Indoor Localization}},
booktitle={Proc. of the 12th Int. Conf. on Information Fusion},
year={2009},
IGNOREmonth={July},
pages={2083--2090},
}
@inproceedings{Hilsenbeck14-GBD,
author = {Hilsenbeck, Sebastian and Bobkov, Dmytro and Schroth, Georg and Huitl, Robert and Steinbach, Eckehard},
title = {{Graph-based Data Fusion of Pedometer and WiFi Measurements for Mobile Indoor Positioning}},
booktitle = {Proc. of the 2014 ACM Int. Joint Conf. on Pervasive and Ubiquitous Computing},
year = {2014},
pages = {147--158},
}
@book{Forbes11-SD,
title={Statistical Distributions},
author={Catherine Forbes and Merran Evans and Nicholas Hastings and Brian Peacock},
isbn={978-0470390634},
series={Wiley Series in Probability and Statistics},
year={2011},
publisher={Wiley},
address={New Jersey},
edition={4},
totalpages={230},
}
@inproceedings{Deinzer01-CIV,
author = {Deinzer, Frank and Denzler, Joachim and Niemann, Heinrich},
title = {On Fusion of Multiple Views for Active Object Recognition},
year = {2001},
pages = {239-245},
booktitle = {Pattern Recognition -- Proc. of the 23rd DAGM Symp.},
IGNOREmonth = {9},
editor = {B. Radig},
series = {LNCS},
volume = {2191},
address = {Heidelberg},
publisher = {Springer}
}
@inproceedings{Mohssen14-ITH,
author = {Mohssen, Nesma and Momtaz, Rana and Aly, Heba and Youssef, Moustafa},
title = {{It's the Human That Matters: Accurate User Orientation Estimation for Mobile Computing Applications}},
booktitle = {Proc. of the 11th Int. Conf. on Mobile and Ubiquitous Systems: Computing, Networking and Services},
year = {2014},
pages = {70--79},
numpages = {10},
}
@inproceedings{Fetzer14,
author={Fetzer, Toni and Deinzer, Frank and K{\"o}ping, Lukas and Grzegorzek, Marcin},
booktitle={Indoor Positioning and Indoor Navigation (IPIN), Int. Conf. on},
title={Statistical Indoor Localization Using Fusion of Depth-Images and Step Detection},
year={2014},
IGNOREmonth={October},
pages={1-9}}
@inproceedings{Ebner14,
author={Ebner, Frank and Deinzer, Frank and K{\"o}ping, Lukas and Grzegorzek, Marcin},
booktitle={Indoor Positioning and Indoor Navigation (IPIN), Int. Conf. on},
title={{R}obust {S}elf-{L}ocalization using {W}i-{F}i, {S}tep/{T}urn-{D}etection and {R}ecursive {D}ensity {E}stimation},
year={2014},
IGNOREmonth={October},
pages={1-9}}
@phdthesis{mautz2012indoor,
title={Indoor positioning technologies},
author={Mautz, Rainer},
year={2012},
school={Habilitationsschrift ETH Z{\"u}rich, 2012}
}
@inproceedings{Parviainen-08,
author={Parviainen, J. and Kantola, J. and Collin, J.},
booktitle={Position, Location and Navigation Symp., 2008 IEEE/ION},
title={Differential barometry in personal navigation},
year={2008},
IGNOREmonth={May},
pages={148-152},
keywords={barometers;height measurement;microsensors;pressure sensors;satellite navigation;MEMS barometer data;altitude information;differential barometry;personal navigation;satellite navigation systems;Costs;Floors;Global Positioning System;Internet;Least squares methods;Micromechanical devices;Satellite navigation systems;Seismic measurements;TCPIP;Ventilation},
doi={10.1109/PLANS.2008.4570051},}
@inproceedings{wang2006fusion,
title={Fusion of barometric sensors, WLAN signals and building information for 3-D indoor/campus localization},
author={Wang, Hui and Lenz, Henning and Szabo, Andrei and Hanebeck, Uwe D and Bamberger, Joachim},
booktitle={Proc. of Int. Conf. on Multisensor Fusion and Integration for Intelligent Systems (MFI 2006), S},
pages={426--432},
year={2006},
}
@inproceedings{Ebner-15,
author={Ebner, Frank and Fetzer, Toni and K{\"o}ping, Lukas and Grzegorzek, Marcin and Deinzer, Frank},
booktitle={Indoor Positioning and Indoor Navigation (IPIN), Int. Conf. on},
title={{Multi Sensor 3D Indoor Localisation}},
year={2015},
publisher = {IEEE},
address = {Banff, Canada},
IGNOREmonth={October},
pages={},
}
@inproceedings{Ebner-16,
author={Ebner, Frank and Fetzer, Toni and Grzegorzek, Marcin and Deinzer, Frank},
booktitle={19th Int. Conf. on Information Fusion (FUSION)},
title={{On Prior Navigation Knowledge in Multi Sensor
Indoor Localisation}},
year={2016},
IGNOREmonth={October},
pages={1-8},
}
@article{Ebner-17,
author = {Ebner, Frank and Fetzer, Toni and Deinzer, Frank and Grzegorzek, Marcin},
title = {{On Wi-Fi Model Optimizations for Smartphone-Based Indoor Localization}},
journal = {ISPRS International Journal of Geo-Information},
volume = {6},
year = {2017},
month = {August},
number = {8},
pages={233-250},
}
@book{condon1967handbook,
title={Handbook of physics},
author={Condon, E.U. and Odishaw, H.},
lccn={66020002},
series={McGraw-Hill handbooks},
year={1967},
publisher={McGraw-Hill},
}
@book{btle,
title={Specification of the Bluetooth System v4.2},
publisher={Bluetooth Special Interest Group},
year={2014},
}
@article{smith1997scientist,
title={The scientist and engineer's guide to digital signal processing},
author={Smith, Steven W and others},
year={1997},
publisher={California Technical Pub. San Diego}
}
@article{Hazas04-LAW,
author={Hazas, M. and Scott, J. and Krumm, J.},
journal={Computer},
title={{Location-aware Computing Comes of Age}},
year={2004},
IGNOREmonth={February},
volume={37},
number={2},
pages={95-97},
}
@article{Dhar11-CAB,
author = {Dhar, Subhankar and Varshney, Upkar},
title = {{Challenges and Business Models for Mobile Location-based Services and Advertising}},
journal = {Communications of the ACM},
volume = {54},
number = {5},
IGNOREmonth = {May},
year = {2011},
pages = {121--128},
}
@article{Kaasinen03-UNF,
author = {Kaasinen, Eija},
title = {{User Needs for Location-aware Mobile Services}},
journal = {Personal and Ubiquitous Computing},
volume = {7},
number = {1},
IGNOREmonth = {May},
year = {2003},
pages = {70--79},
}
@inproceedings{Macvean12-IAS,
author = {Macvean, Andrew and Robertson, Judy},
title = {{iFitQuest: A School Based Study of a Mobile Location-aware Exergame for Adolescents}},
booktitle = {Proc. of the 14th Int. Conf. on Human-computer Interaction with Mobile Devices and Services},
series = {MobileHCI '12},
year = {2012},
pages = {359--368},
}
@inproceedings{Kaminskas13-LAM,
author = {Kaminskas, Marius and Ricci, Francesco and Schedl, Markus},
title = {{Location-aware Music Recommendation Using Auto-tagging and Hybrid Matching}},
booktitle = {Proc. of the 7th ACM Conf. on Recommender Systems},
series = {RecSys '13},
year = {2013},
pages = {17--24},
}
@article{Perera14-CAC,
author={Perera, C. and Zaslavsky, A. and Christen, P. and Georgakopoulos, D.},
journal={Communications Surveys Tutorials, IEEE},
title={{Context Aware Computing for The Internet of Things: A Survey}},
year={2014},
IGNOREmonth={First Quarter},
volume={16},
number={1},
pages={414-454},
}
@inproceedings{Nurminen2014,
abstract = {This article presents a training-free probabilistic pedestrian motion model that uses indoor map information represented as a set of links that are connected by nodes. This kind of structure can be modelled as a graph. In the proposed model, as a position estimate reaches a link end, the choice probabilities of the next link are proportional to the total link lengths (TLL), the total lengths of the subgraphs accessible by choosing the considered link alternative. The TLLs can be computed off-line using only the graph, and they can be updated if training data are available. A particle filter in which all the particles move on the links following the TLL-based motion model is formulated. The TLL-based motion model has advantageous theoretical properties compared to the conventional models. Furthermore, the real-data WLAN positioning tests show that the positioning accuracy of the algorithm is similar or in many cases better than that of the conventional algorithms. The TLL-based model is found to be advantageous especially if position measurements are used infrequently, with 10-second or more time intervals.},
author = {Nurminen, Henri and Koivisto, Mike and Ali-Loytty, Simo and Piche, Robert},
booktitle = {Int. Conf. on Indoor Positioning and Indoor Navigation (IPIN)},
doi = {10.1109/IPIN.2014.7275539},
file = {:home/toni/Documents/literatur/fusion16/Motion model for positioning with graph-based indoor map.pdf:pdf},
isbn = {978-1-4673-8054-6},
keywords = {Atmospheric measurements,Computational modeling,Particle measurements,Position measurement,Proposals,TLL,Training data,Wireless LAN,graph,graph theory,graph-based indoor map,indoor navigation,indoor positioning,map-matching,motion model,particle filter,particle filtering (numerical methods),position measurement,radio links,real-data WLAN positioning test,total link length,training-free probabilistic pedestrian motion mode,wireless LAN},
IGNOREmonth = {oct},
pages = {646--655},
publisher = {IEEE},
shorttitle = {Indoor Positioning and Indoor Navigation (IPIN), 2},
title = {{Motion Model for Positioning with Graph-based Indoor Map}},
year = {2014}
}
@book{albrecht2013computer,
title={Computer Algebra: Symbolic and Algebraic Computation},
author={Albrecht, Rudolf and Buchberger, Bruno and Collins, George Edwin and Loos, Rudiger},
volume={4},
year={2013},
publisher={Springer Science \& Business Media}
}
@book{bernardo2009bayesian,
title={Bayesian Theory},
author={Bernardo, Jos{\'e} M and Smith, Adrian FM},
volume={405},
year={2009},
publisher={John Wiley \& Sons}
}
@book{sarkka2013bayesian,
title={Bayesian Filtering and Smoothing},
author={S{\"a}rkk{\"a}, Simo},
number={3},
year={2013},
publisher={Cambridge University Press}
}
@book{rinne2008taschenbuch,
title={Taschenbuch der Statistik},
author={Rinne, Horst},
year={2008},
publisher={Harri Deutsch Verlag}
}
@article{aldrich1997ra,
title={RA Fisher and the Making of Maximum Likelihood 1912-1922},
author={Aldrich, John and others},
journal={Statistical Science},
volume={12},
number={3},
pages={162--176},
year={1997},
publisher={Institute of Mathematical Statistics}
}
@Misc{kypraios12,
author = {Kypraios, Theo},
title = {Introduction to Bayesian Statistics},
year = {2012},
IGNOREmonth = {10},
note = {Lecture Presentation},
url = {https://www.maths.nottingham.ac.uk/personal/tk/files/talks/Cran_10_12.pdf [\today]}
}
@article{ghahramani2001introduction,
title={An Introduction to Hidden Markov Models and Bayesian Networks},
author={Ghahramani, Zoubin},
journal={Int. Journal of Pattern Recognition and Artificial Intelligence},
volume={15},
number={01},
pages={9--42},
year={2001},
publisher={World Scientific}
}
@article{rabiner1989tutorial,
title={A Tutorial on Hidden Markov Models and Selected Applications in Speech Recognition},
author={Rabiner, Lawrence R},
journal={Proc. of the IEEE},
volume={77},
number={2},
pages={257--286},
year={1989},
publisher={IEEE}
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title={Collapsed variational Bayesian Inference for Hidden Markov Models},
author={Wang, Pengyu and Blunsom, Phil},
booktitle={Proc. of the Sixteenth Int. Conf. on Artificial Intelligence and Statistics},
pages={599--607},
year={2013}
}
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title={Statistical Inference for Probabilistic Functions of Finite State Markov Chains},
author={Baum, Leonard E and Petrie, Ted},
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year={1966},
publisher={JSTOR}
}
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title={Markov Chain Monte Carlo},
author={Gilks, Walter R},
year={2005},
publisher={Wiley Online Library}
}
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title={A Unifying Review of Linear Gaussian Models},
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year={1999},
publisher={MIT Press}
}
@article{chen2003bayesian,
title={{Bayesian Filtering: From Kalman Filters to Particle Filters, and Beyond}},
author={Chen, Zhe},
journal={Statistics},
volume={182},
number={1},
pages={1--69},
year={2003}
}
@book{gelman2014bayesian,
title={Bayesian Data Analysis},
author={Gelman, Andrew and Carlin, John B and Stern, Hal S and Rubin, Donald B},
volume={2},
year={2014},
publisher={Taylor \& Francis}
}
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title={Prior Probabilities},
author={Jaynes, Edwin T},
journal={Systems Science and Cybernetics, IEEE Transactions on},
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publisher={IEEE}
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title={The Selection of Prior Distributions by Formal Rules},
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title={Probability Theory: The Logic of Science},
author={Jaynes, Edwin T},
year={2003},
publisher={Cambridge university press}
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author = {Jeffreys, Harold},
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}
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title={New Extension of the Kalman Filter to Nonlinear Systems},
author={Julier, Simon J and Uhlmann, Jeffrey K},
booktitle={AeroSense'97},
pages={182--193},
year={1997},
organization={Int. Society for Optics and Photonics}
}
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title={A Central Limit Theorem and a Strong Mixing Condition},
author={Rosenblatt, Murray},
journal={Proc. of the National Academy of Sciences of the United States of America},
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title={A New Approach to Linear Filtering and Prediction Problems},
author={Kalman, Rudolph Emil},
journal={Journal of Fluids Engineering},
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publisher={American Society of Mechanical Engineers}
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author = "John H. Halton",
title = "A Retrospective and Prospective Survey of the {Monte
Carlo} Method",
journal = j-SIAM-REVIEW,
volume = "12",
number = "1",
pages = "1--63",
year = "1970",
CODEN = "SIREAD",
DOI = "http://dx.doi.org/10.1137/1012001",
ISSN = "0036-1445 (print), 1095-7200 (electronic)",
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acknowledgement = ack-nhfb,
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@incollection{Platzer:2008,
year={2008},
isbn={978-3-540-78639-9},
booktitle={Bildverarbeitung f\"ur die Medizin 2008},
series={Informatik Aktuell},
IGNOREeditor={Tolxdorff, Thomas and Braun, J\"urgen and Deserno, Thomas M. and Horsch, Alexander and Handels, Heinz and Meinzer, Hans-Peter},
doi={10.1007/978-3-540-78640-5_58},
title={{3D Blood Flow Reconstruction from 2D Angiograms}},
publisher={Springer Berlin Heidelberg},
author={Platzer, Esther-S. and Deinzer, Frank and Paulus, Dietrich and Denzler, Joachim},
pages={288--292},
language={English},
}
@article{haugh2004monte,
title={The Monte Carlo Framework, Examples from Finance and Generating Correlated Random Variables},
author={Haugh, Martin},
journal={Course Notes},
year={2004}
}
@misc{orhan2012particle,
title={Particle Filtering},
author={Orhan, Emin},
note={Technical Report},
howpublished={\url{http://www.cns.nyu.edu/~eorhan/} (Visited: 27.11.2015)},
year={2012}
}
@article{doucet2000,
year={2000},
issn={0960-3174},
journal={Statistics and Computing},
volume={10},
number={3},
doi={10.1023/A:1008935410038},
title={{On Sequential Monte Carlo Sampling Methods for Bayesian Filtering}},
publisher={Kluwer Academic Publishers},
keywords={Bayesian filtering; nonlinear non-Gaussian state space models; sequential Monte Carlo methods; particle filtering; importance sampling; Rao-Blackwellised estimates},
author={Doucet, Arnaud and Godsill, Simon and Andrieu, Christophe},
pages={197-208},
language={English}
}
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title={Sequential Imputations and Bayesian Missing Data Problems},
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journal={Journal of the American Statistical Association},
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pages={278--288},
year={1994},
publisher={Taylor \& Francis}
}
@inproceedings{douc2005comparison,
title={Comparison of Resampling Schemes for Particle Filtering},
author={Douc, Randal and Capp{\'e}, Olivier},
booktitle={Image and Signal Processing and Analysis, 2005. ISPA 2005. Proc. of the 4th Int. Symp. on},
pages={64--69},
year={2005},
organization={IEEE}
}
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title={An Introduction to the Bootstrap},
author={Efron, Bradley and Tibshirani, Robert J},
year={1994},
publisher={CRC press}
}
@article{arulampalam2002tutorial,
title={A Tutorial on Particle Filters for Online Nonlinear/Non-Gaussian Bayesian Tracking},
author={Arulampalam, M Sanjeev and Maskell, Simon and Gordon, Neil and Clapp, Tim},
journal={Signal Processing, IEEE Transactions on},
volume={50},
number={2},
pages={174--188},
year={2002},
publisher={IEEE}
}
@ARTICLE{Gordon93,
author={Gordon, N.J. and Salmond, D.J. and Smith, A.F.M.},
journal={Radar and Signal Processing, IEE Proc. F},
title={Novel Approach to Nonlinear/Non-Gaussian Bayesian State Estimation},
year={1993},
volume={140},
number={2},
pages={107-113},
keywords={Bayes methods;Kalman filters;filtering and prediction theory;state estimation;tracking;Gaussian noise;algorithm;bearings only tracking problem;bootstrap filter;extended Kalman filter;measurement model;nonGaussian Bayesian state estimation;nonlinear Bayesian state estimation;random samples;recursive Bayesian filters;simulation;state transition model;state vector density},
ISSN={0956-375X},
IGNOREmonth={Apr},
}
@article{DBLP:LiSSC13,
author = {Tiancheng Li and
Shudong Sun and
Tariq P. Sattar and
Juan M. Corchado},
title = {Fighting against Sample Degeneracy and Impoverishment in Particle
Filters: Particularly on Intelligent Choices},
journal = {CoRR},
volume = {abs/1308.2443},
year = {2013},
url = {http://arxiv.org/abs/1308.2443},
timestamp = {Tue, 10 Dec 2013 12:03:02 +0100},
biburl = {http://dblp.uni-trier.de/rec/bib/journals/corr/LiSSC13},
bibsource = {dblp computer science bibliography, http://dblp.org}
}
@PHDTHESIS{blanco2009phd,
author = {Blanco, Jos{\'{e}}-Luis},
IGNOREmonth = {{nov}},
title = {Contributions to Localization, Mapping and Navigation in Mobile Robotics},
year = {2009},
school = {PhD. in Electrical Engineering, University of Malaga},
url = {http://www.mrpt.org/Paper:J.L._Blanco_Phd_Thesis}
}
@article{kunsch2005recursive,
title={Recursive Monte Carlo Filters: Algorithms and Theoretical Analysis},
author={K{\"u}nsch, Hans R},
journal={Ann. of Statistics},
pages={1983--2021},
year={2005},
publisher={JSTOR}
}
@article{rekleitis2004particle,
title={A Particle Filter Tutorial for Mobile Robot Localization},
author={Rekleitis, Ioannis M},
journal={Centre for Intelligent Machines, McGill University, Tech. Rep. TR-CIM-04-02},
year={2004}
}
@article{cappe2007overview,
title={An Overview of Existing Methods and Recent Advances in Sequential Monte Carlo},
author={Capp{\'e}, Olivier and Godsill, Simon J and Moulines, Eric},
journal={Proc. of the IEEE},
volume={95},
number={5},
pages={899--924},
year={2007},
publisher={IEEE}
}
@article{chen2000mixture,
title={Mixture Kalman Filters},
author={Chen, Rong and Liu, Jun S},
journal={Journal of the Royal Statistical Society: Series B (Statistical Methodology)},
volume={62},
number={3},
pages={493--508},
year={2000},
publisher={Wiley Online Library}
}
@inproceedings{van2000unscented,
title={The unscented Particle Filter},
author={Van Der Merwe, Rudolph and Doucet, Arnaud and De Freitas, Nando and Wan, Eric},
booktitle={NIPS},
pages={584--590},
year={2000}
}
@inproceedings{wan2000unscented,
title={The unscented Kalman filter for nonlinear estimation},
author={Wan, Eric and Van Der Merwe, Ronell and others},
booktitle={Adaptive Systems for Signal Processing, Communications, and Control Symp. 2000. AS-SPCC. The IEEE 2000},
pages={153--158},
year={2000},
organization={IEEE}
}
@inproceedings{Muller:2003:PFS,
author = {M\"{u}ller, Matthias and Charypar, David and Gross, Markus},
title = {Particle-based Fluid Simulation for Interactive Applications},
booktitle = {Proc. of the 2003 ACM SIGGRAPH/Eurographics Symp. on Computer Animation},
series = {SCA '03},
year = {2003},
isbn = {1-58113-659-5},
location = {San Diego, California},
pages = {154--159},
numpages = {6},
url = {http://dl.acm.org/citation.cfm?id=846276.846298},
acmid = {846298},
publisher = {Eurographics Association},
address = {Aire-la-Ville, Switzerland, Switzerland},
}
@incollection{isard1998smoothing,
title={{A Smoothing Filter for Condensation}},
author={Isard, Michael and Blake, Andrew},
booktitle={Computer Vision—ECCV'98},
pages={767--781},
year={1998},
publisher={Springer},
}
@inproceedings{klaas2006fast,
title={{Fast Particle Smoothing: If I had a Million Particles}},
author={Klaas, Mike and Briers, Mark and De Freitas, Nando and Doucet, Arnaud and Maskell, Simon and Lang, Dustin},
booktitle={Proc. of the 23rd Int. Conf. on Machine learning},
pages={481--488},
year={2006},
organization={ACM}
}
@article{kitagawa1996monte,
title={{Monte Carlo Filter and Smoother for non-Gaussian nonlinear State Space Models}},
author={Kitagawa, Genshiro},
journal={Journal of Computational and Graphical Statistics},
volume={5},
number={1},
pages={1--25},
year={1996},
publisher={Taylor \& Francis}
}
@inproceedings{achtelik2009visual,
title={Visual Tracking and Control of a Quadcopter using a Stereo Camera System and Inertial Sensors},
author={Achtelik, Markus and Zhang, Tianguang and K{\"u}hnlenz, Kolja and Buss, Martin},
booktitle={Mechatronics and Automation, 2009. ICMA 2009. Int. Conf. on},
pages={2863--2869},
year={2009},
organization={IEEE}
}
@book{simonoff2012smoothing,
title={Smoothing Methods in Statistics},
author={Simonoff, Jeffrey S},
year={2012},
publisher={Springer Science \& Business Media}
}
@book{sachs2013angewandte,
title={Angewandte Statistik: Anwendung statistischer Methoden},
author={Sachs, Lothar},
year={2013},
publisher={Springer-Verlag}
}
@book{simon2006optimal,
title={Optimal State Estimation: Kalman, H-infinity, and Nonlinear Approaches},
author={Simon, Dan},
year={2006},
publisher={John Wiley \& Sons}
}
@article{briers2010smoothing,
title={Smoothing Algorithms for State-Space Models},
author={Briers, Mark and Doucet, Arnaud and Maskell, Simon},
journal={Ann. of the Institute of Statistical Mathematics},
volume={62},
number={1},
pages={61--89},
year={2010},
publisher={Springer}
}
@article{fearnhead2010sequential,
title={{A Sequential Smoothing Algorithm with Linear Computational Cost}},
author={Fearnhead, Paul and Wyncoll, David and Tawn, Jonathan},
journal={Biometrika},
volume={97},
number={2},
pages={447--464},
year={2010},
publisher={Biometrika Trust}
}
@article{kitagawa1987non,
title={{Non-Gaussian State-Space Modeling of Nonstationary Time Series}},
author={Kitagawa, Genshiro},
journal={Journal of the American Statistical Association},
volume={82},
number={400},
pages={1032--1041},
year={1987},
publisher={Taylor \& Francis Group}
}
@article{mayne1966solution,
title={A Solution of the Smoothing Problem for Linear Dynamic Systems},
author={Mayne, DQ},
journal={Automatica},
volume={4},
number={2},
pages={73--92},
year={1966},
publisher={Elsevier}
}
@TECHREPORT{briers2004smoothing,
AUTHOR = {Briers, Mark and Doucet, Arnaud and Maskell, Simon},
TITLE = {Smoothing Algorithms for State-Space Models},
NUMBER = {CUED/F-INFENG/TR.498},
INSTITUTION = {Cambridge University Engineering Department},
YEAR = {2004},
}
@inproceedings{Robertson:2009:SLM,
author = {Robertson, Patrick and Angermann, Michael and Krach, Bernhard},
title = {Simultaneous Localization and Mapping for Pedestrians Using Only Foot-mounted Inertial Sensors},
booktitle = {Proc. of the 11th Int. Conf. on Ubiquitous Computing},
series = {UbiComp '09},
year = {2009},
isbn = {978-1-60558-431-7},
location = {Orlando, Florida, USA},
pages = {93--96},
numpages = {4},
publisher = {ACM},
address = {New York, NY, USA},
keywords = {ins-based positioning, odometry, indoor positioning, pedestrian navigation, simultaneous localization and mapping},
}
@inproceedings{jensen-09,
author={Jensen, Christian S. and Hua Lu and Bin Yang},
booktitle={Mobile Data Management: Systems, Services and Middleware, 2009. MDM '09. Tenth Int. Conf. on},
title={Graph Model Based Indoor Tracking},
year={2009},
pages={122-131},
keywords={graph theory;radio tracking;radiofrequency identification;radionavigation;telecommunication network topology;RFID-based positioning;base graph model;indoor navigation;indoor positioning technologies;indoor tracking;specific reader deployment graph model;symbolic positioning technologies;uniform data management infrastructure;Bluetooth;Computer science;Data structures;Mobile computing;Navigation;Partitioning algorithms;Radiofrequency identification;Space technology;Technology management;Topology},
doi={10.1109/MDM.2009.23},
IGNOREmonth={May},}
@MastersThesis{Ebner:Thesis:2013,
author = {Frank Ebner},
title = {{Statistische Selbstlokalisation mittels WiFi SLAM}},
school = {University of Applied Sciences W{\"u}rzburg - Schweinfurt},
address = {W{\"u}rzburg},
year = {2013},
}
@article{shortestPath:96,
year={1996},
issn={0025-5610},
journal={Mathematical Programming},
volume={73},
number={2},
doi={10.1007/BF02592101},
title={Shortest Paths Algorithms: Theory and Experimental Evaluation},
url={http://dx.doi.org/10.1007/BF02592101},
publisher={Springer-Verlag},
keywords={Graph algorithms; Network optimization; Shortest paths; Theory and experimental evaluation of algorithms},
author={Cherkassky, Boris V. and Goldberg, Andrew V. and Radzik, Tomasz},
pages={129-174},
language={English}
}
@inproceedings{werner2014homotopy,
Title = {Homotopy and Alternative Routes in Indoor Navigation Scenarios},
Author = {Martin Werner and Sebastian Feld},
Booktitle = {Indoor Positioning and Indoor Navigation (IPIN), Int. Conf. on},
Year = {2014},
Pages = {1-9},
}
@inproceedings{Li2015,
abstract = {This paper presents an indoor navigation algorithm that uses multiple kinds of sensors and technologies, such as MEMS sensors (i.e., gyros, accelerometers, magnetometers, and a barometer), WiFi, and magnetic matching. The corresponding real-time software on smartphones includes modules such dead-reckoning, WiFi positioning, and magnetic matching. DR is used for providing continuous position solutions and for the blunder detection of both WiFi fingerprinting and magnetic matching. Finally, WiFi and magnetic matching results are passed into the position-tracking module as updates. Meanwhile, a barometer is used to detect floor changes, so as to switch floors and the WiFi and magnetic databases. This algorithm was tested during the 5th EvAAL indoor navigation competition. Position errors on three quarters (75 {\%}) of test points (totally 62 test points were selected to evaluate the algorithm) were under 6.6 m.},
author = {Li, You and Zhang, Peng and Niu, Xiaoji and Zhuang, Yuan and Lan, Haiyu and El-Sheimy, Naser},
booktitle = {Int. Conf. on Indoor Positioning and Indoor Navigation (IPIN)},
doi = {10.1109/IPIN.2015.7346966},
file = {:home/toni/Documents/literatur/fusion16/Real-time indoor navigation using smartphone sensors.pdf:pdf},
isbn = {978-1-4673-8402-5},
keywords = {5th EvAAL indoor navigation competition,Fingerprint recognition,IEEE 802.11 Standard,Indoor navigation,Localisation System,MEMS sensors,Magnetometers,Position measurement,Sensors,WiFi fingerprinting,WiFi positioning,accelerometers,barometer,barometers,dead-reckoning,floor change detection,gyros,gyroscopes,indoor navigation,magnetic features,magnetic matching,magnetometers,micromechanical devices,position-tracking module,radionavigation,real-time indoor navigation,smart phones,smartphone,smartphone sensors,wireless LAN},
mendeley-tags = {Localisation System},
IGNOREmonth = {oct},
pages = {1--10},
publisher = {IEEE},
shorttitle = {Indoor Positioning and Indoor Navigation (IPIN), 2},
title = {{Real-time Indoor Navigation using Smartphone Sensors}},
year = {2015}
}
@article{Yang2015,
author = {Yang, Zheng and Wu, Chenshu and Zhou, Zimu and Zhang, Xinglin and Wang, Xu and Liu, Yunhao},
doi = {10.1145/2676430},
file = {:home/toni/Documents/literatur/fusion16/Mobility Increases Localizability$\backslash$: A Survey on Wireless Indoor.pdf:pdf},
issn = {03600300},
journal = {ACM Computing Surveys},
keywords = {Mobility,smartphones,wireless indoor localization},
IGNOREmonth = {apr},
number = {3},
pages = {1--34},
publisher = {ACM},
title = {{Mobility Increases Localizability: A Survey on Wireless Indoor Localization using Inertial Sensors}},
volume = {47},
year = {2015}
}
@article{Gu2009,
abstract = {Recently, indoor positioning systems (IPSs) have been designed to provide location information of persons and devices. The position information enables location-based protocols for user applications. Personal networks (PNs) are designed to meet the users' needs and interconnect users' devices equipped with different communications technologies in various places to form one network. Location-aware services need to be developed in PNs to offer flexible and adaptive personal services and improve the quality of lives. This paper gives a comprehensive survey of numerous IPSs, which include both commercial products and research-oriented solutions. Evaluation criteria are proposed for assessing these systems, namely security and privacy, cost, performance, robustness, complexity, user preferences, commercial availability, and limitations. We compare the existing IPSs and outline the trade-offs among these systems from the viewpoint of a user in a PN.},
author = {Gu, Yanying and Lo, Anthony and Niemegeers, Ignas},
doi = {10.1109/SURV.2009.090103},
file = {:home/toni/Documents/literatur/fusion16/A Survey of Indoor Positioning Systems for.pdf:pdf},
isbn = {1553-877X},
issn = {1553877X},
journal = {IEEE Communications Surveys and Tutorials},
keywords = {Indoor positioning systems,Location techniques,Personal networks},
number = {1},
pages = {13--32},
shorttitle = {Communications Surveys {\&} Tutorials, IEEE},
title = {{A Survey of Indoor Positioning Systems for Wireless Personal Networks}},
volume = {11},
year = {2009}
}
@article{Khaleghi2013,
abstract = {There has been an ever-increasing interest in multi-disciplinary research on multisensor data fusion technology, driven by its versatility and diverse areas of application. Therefore, there seems to be a real need for an analytical review of recent developments in the data fusion domain. This paper proposes a comprehensive review of the data fusion state of the art, exploring its conceptualizations, benefits, and challenging aspects, as well as existing methodologies. In addition, several future directions of research in the data fusion community are highlighted and described.},
author = {Khaleghi, Bahador and Khamis, Alaa and Karray, Fakhreddine O. and Razavi, Saiedeh N.},
doi = {10.1016/j.inffus.2011.08.001},
file = {:home/toni/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Khaleghi et al. - 2013 - Multisensor data fusion A review of the state-of-the-art.pdf:pdf},
issn = {15662535},
journal = {Information Fusion},
keywords = {Fusion methodologies,Multisensor data fusion,Taxonomy},
IGNOREmonth = {jan},
number = {1},
pages = {28--44},
title = {{Multisensor data fusion: A review of the state-of-the-art}},
volume = {14},
year = {2013}
}
@inproceedings{Liao2003,
abstract = { Tracking the activity of people in indoor environments has gained considerable attention in the robotics community over the last years. Most of the existing approaches are based on sensors, which allow to accurately determining the locations of people but do not provide means to distinguish between different persons. In this paper we propose a novel approach to tracking moving objects and their identity using noisy, sparse information collected by id-sensors such as infrared and ultrasound badge systems. The key idea of our approach is to use particle filters to estimate the locations of people on the Voronoi graph of the environment. By restricting particles to a graph, we make use of the inherent structure of indoor environments. The approach has two key advantages. First, it is by far more efficient and robust than unconstrained particle filters. Second, the Voronoi graph provides a natural discretization of human motion, which allows us to apply unsupervised learning techniques to derive typical motion patterns of the people in the environment. Experiments using a robot to collect ground-truth data indicate the superior performance of Voronoi tracking. Furthermore, we demonstrate that EM-based learning of behavior patterns increases the tracking performance and provides valuable information for high-level behavior recognition.},
author = {Liao, Lin and Fox, D. and Hightower, J. and Kautz, H. and Schulz, D.},
booktitle = {Proc. 2003 IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS 2003)},
doi = {10.1109/IROS.2003.1250715},
file = {:home/toni/Documents/literatur/fusion16/Voronoi .pdf:pdf},
isbn = {0-7803-7860-1},
keywords = {Computer science,Humans,Indoor environments,Particle filters,Pattern recognition,Robot sensing systems,Robustness,State-space methods,Ultrasonic imaging,Voronoi graph,Voronoi tracking,Working environment noise,array signal processing,computational geometry,high-level behavior recognition,human motion,indoor environments,infrared badge system,mobile robots,motion estimation,noisy sensor data,particle filters,robot,tracking,tracking moving objects,ultrasound badge systems,unsupervised learning techniques},
pages = {723--728},
publisher = {IEEE},
shorttitle = {Intelligent Robots and Systems, 2003. (IROS 2003).},
title = {{Voronoi Tracking: Location Estimation Using Sparse and Noisy Sensor Data}},
volume = {1},
year = {2003}
}
@article{Afyouni2012,
author = {Afyouni, Imad and Ray, Cyril and Claramunt, Christophe},
issn = {1948-660X},
journal = {Journal of Spatial Information Science},
keywords = {context-awareness,indoor spatial data models,location-dependent queries,navigation systems and wayfinding,qualitative spatial representation,quantitative spatial representation},
language = {en},
IGNOREmonth = {Jun},
number = {4},
pages = {85--123},
title = {{Spatial Models for Context-Aware Indoor Navigation Systems: A Survey}},
volume = {1},
year = {2012}
}
@inproceedings{Hilsenbeck2014,
address = {New York, NY, USA},
author = {Hilsenbeck, Sebastian and Bobkov, Dmytro and Schroth, Georg and Huitl, Robert and Steinbach, Eckehard},
booktitle = {Proc. of the 2014 ACM Int. Joint Conf. on Pervasive and Ubiquitous Computing - UbiComp '14 Adjunct},
IGNOREmonth = {sep},
pages = {147--158},
publisher = {ACM Press},
title = {{Graph-based Data Fusion of Pedometer and WiFi Measurements for Mobile Indoor Positioning}},
year = {2014}
}
@article{hotelling1933,
title={{Analysis of a Complex of Statistical Variables into Principal Components.}},
author={Hotelling, Harold},
journal={Journal of educational psychology},
volume={24},
number={6},
pages={417},
year={1933},
publisher={Warwick \& York}
}
@article{Thrun2003,
abstract = {This article describes a new algorithm for acquiring occupancy grid maps with mobile robots. Existing occupancy grid mapping algorithms decompose the high-dimensional mapping problem into a collection of one-dimensional problems, where the occupancy of each grid cell is estimated independently. This induces conflicts that may lead to inconsistent maps, even for noise-free sensors. This article shows how to solve the mapping problem in the original, high-dimensional space, thereby maintaining all dependencies between neighboring cells. As a result, maps generated by our approach are often more accurate than those generated using traditional techniques. Our approach relies on a statistical formulation of the mapping problem using forward models. It employs the expectation maximization algorithm for searching maps that maximize the likelihood of the sensor measurements.},
author = {Thrun, Sebastian},
doi = {10.1023/A:1025584807625},
file = {:home/toni/Documents/literatur/fusion16/thrun.iros01-occmap.pdf:pdf},
isbn = {0-7803-6612-3},
issn = {09295593},
journal = {Autonomous Robots},
keywords = {Bayesian techniques,Mapping,Mobile robotics,Probabilistic inference,Robot navigation,SLAM},
language = {en},
number = {2},
pages = {111--127},
pmid = {563334},
publisher = {Kluwer Academic Publishers},
title = {{Learning Occupancy Grid Maps with Forward Sensor Models}},
volume = {15},
year = {2003}
}
@article{Li2010,
abstract = {While recent years have witnessed noticeable development of indoor GIS, there is still a lack of clear consensus on the modeling principles that should support such applications. The objective of the research presented in this paper is to represent two-dimensional (2D) indoor spaces with a grid graph-based model that takes into account the structural and spatial properties of an indoor space. The model developed considers a built environment as a frame of reference at different levels of granularity using a grid graph-based representation. The advantage of the modeling approach is that it combines structural and topological properties as well as implicitly taking into account the metric of space, this being often overlooked by most existing indoor space models. Several types of indoor space analysis are employed to illustrate the potential of the proposed model, such as route and diffusion analysis, centrality and topological analysis.},
author = {Li, Xiang and Claramunt, Christophe and Ray, Cyril},
doi = {10.1016/j.compenvurbsys.2010.07.006},
file = {:home/toni/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Li, Claramunt, Ray - 2010 - A grid graph-based model for the analysis of 2D indoor spaces.pdf:pdf},
issn = {01989715},
journal = {Computers, Environment and Urban Systems},
keywords = {Grid graph-based representation,Indoor spaces,Network,Structural-based modeling},
IGNOREmonth = {nov},
number = {6},
pages = {532--540},
title = {{A grid graph-based model for the analysis of 2D indoor spaces}},
volume = {34},
year = {2010}
}
@article{elfes1989using,
title={{Using Occupancy Grids for Mobile Robot Perception and Navigation}},
author={Elfes, Alberto},
journal={Computer},
volume={22},
number={6},
pages={46--57},
year={1989},
publisher={IEEE}
}
@article{GarciaPuyol2014,
abstract = {Pedestrian navigation is an important ingredient for efficient multimodal transportation, such as guidance within large transportation infrastructures. A requirement is accurate positioning of people in indoor multistory environments. To achieve this, maps of the environment play a very important role. FootSLAM is an algorithm based on the simultaneous localization and mapping (SLAM) principle that relies on human odometry, i.e., measurements of a pedestrian's steps, to build probabilistic maps of human motion for such environments and can be applied using crowdsourcing. In this paper, we extend FootSLAM to multistory buildings following a Bayesian derivation. Our approach employs a particle filter and partitions the map space into a grid of adjacent hexagonal prisms with eight faces. We model the vertical component of the odometry errors using an autoregressive integrated moving average (ARIMA) model and extend the geographic tree-based data structure that efficiently stores the probabilistic map, allowing real-time processing. We present the multistory FootSLAM maps that were created from three data sets collected in different buildings (one large office building and two university buildings). Hereby, the user was only carrying a single foot-mounted inertial measurement unit (IMU). We believe the resulting maps to be strong evidence of the robustness of FootSLAM. This paper raises the future possibility of crowdsourced indoor mapping and accurate navigation using other forms of human odometry, e.g., obtained with the low-cost and nonintrusive sensors of a handheld smartphone.},
author = {{Garcia Puyol}, Maria and Bobkov, Dmytro and Robertson, Patrick and Jost, Thomas},
doi = {10.1109/TITS.2014.2303115},
file = {:home/toni/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Garcia Puyol et al. - 2014 - Pedestrian simultaneous localization and mapping in multistory buildings using inertial sensors.pdf:pdf},
issn = {15249050},
journal = {IEEE Transactions on Intelligent Transportation Systems},
keywords = {Indoor pedestrian navigation,inertial navigation,multistory localization and mapping,simultaneous localization and mapping (SLAM)},
IGNOREmonth = {aug},
number = {4},
pages = {1714--1727},
shorttitle = {Intelligent Transportation Systems, IEEE Transacti},
title = {{Pedestrian Simultaneous Localization and Mapping in Multistory Buildings using Inertial Sensors}},
volume = {15},
year = {2014}
}
@article{Bandi2000,
abstract = {This paper presents an efficient and robust technique for generating global motion paths for a human model in virtual environments. Initially, a scene is discretized using raster hardware to generate an environment map. An obstacle-free cell path sub-optimal according to Manhattan metric is generated between any two cells. Unlike 2D techniques present in literature, the proposed algorithm works for complex 3D environments suitable for video games and architectural walk-throughs. For obstacle avoidance, the algorithm considers both physical dimensions of the human and actions such as jumping, bending, etc. Path smoothening is carried out to keep the cell path as closely as possible to Euclidean straight-line paths.},
author = {Bandi, Srikanth and Thalmann, Daniel},
doi = {10.1016/S0925-7721(99)00046-2},
file = {:home/toni/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Bandi, Thalmann - 2000 - Path finding for human motion in virtual environments.pdf:pdf},
issn = {09257721},
journal = {Computational Geometry},
keywords = {Cellular paths,Heuristic search,Obstacle avoidance,Path planning,Pathfinding,Virtual walk-throughs},
mendeley-tags = {Pathfinding},
number = {1-3},
pages = {103--127},
title = {{Path finding for human motion in virtual environments}},
volume = {15},
year = {2000}
}
@inproceedings{tan2014agent,
title={Agent-based simulation of building evacuation using a grid graph-based model},
author={Tan, Lu and Lin, Hui and Hu, Mingyuan and Che, Weitao},
booktitle={IOP Conf. Series: Earth and Environmental Science},
volume={18},
number={1},
year={2014},
organization={IOP Publishing}
}
@inproceedings{Sun2011,
abstract = {At present, application of GIS is in a process of transition from macro space to micro space, such as indoor space, a kind of micro environment that has a smaller scale than outdoor space. There have been some applications for indoor space, covering issues like path finding, emergency planning, object tracking, etc. Behind these applications, indoor spatial models are needed to illustrate how built environments are spatially represented. Although some modeling approaches have been proposed, most of them focus only on either structural or topological properties. In view of this problem, recently a grid graph-based modeling approach considering a built environment as a continuous framework is presented, which is able to combine both geometrical and structural properties. In this paper, we employ this approach to implement route analysis based on a hotel floor plan. The result might be applied to the planning for evacuation routes.},
author = {Sun, Jing and Li, Xiang},
booktitle = {Proc. - 2011 19th Int. Conf. on Geoinformatics, Geoinformatics 2011},
doi = {10.1109/GeoInformatics.2011.5980680},
isbn = {9781612848488},
issn = {9781612848495},
keywords = {evacuation planning,grid graph-based model,indoor space},
IGNOREmonth = {jun},
pages = {1--4},
publisher = {IEEE},
shorttitle = {Geoinformatics, 2011 19th Int. Conf.},
title = {{Indoor Evacuation Routes Planning with a Grid Graph-based Model}},
year = {2011}
}
@inproceedings{Brogan2003,
abstract = {Pedestrian navigation is a complex function of human dynamics, a desired destination, and the presence of obstacles. People cannot stop and start instantaneously and their turning abilities are influenced by kinematic and dynamical constraints. A realistic model of human walking paths is an important development for entertainment applications and many classes of simulations. We present a novel behavioral model of path planning that extends previous models through its significant use of pedestrian performance statistics that were obtained during a suite of experiments. We develop an original interpretation of quantitative metrics for measuring a model’s accuracy, and use it to compare our path planning approach to a popular contemporary method. Results indicate that this new path planning model better fits natural human behavior than previous models.},
author = {Brogan, D. C. and Johnson, N. L.},
booktitle = {Proc. - IEEE Workshop on Program Comprehension},
doi = {10.1109/CASA.2003.1199309},
file = {:home/toni/Documents/literatur/Realistic human walking paths.pdf:pdf},
isbn = {0769519342},
issn = {10928138},
keywords = {Air safety,Animation,Humans,Kinematics,Legged locomotion,Navigation,Path planning,Robots,Testing,Turning},
pages = {94--101},
publisher = {IEEE Comput. Soc},
shorttitle = {Computer Animation and Social Agents, 2003. 16th I},
title = {{Realistic human walking paths}},
volume = {2003-Janua},
year = {2003}
}
@article{Cover1967,
abstract = {The nearest neighbor decision rule assigns to an unclassified sample point the classification of the nearest of a set of previously classified points. This rule is independent of the underlying joint distribution on the sample points and their classifications, and hence the probability of errorRof such a rule must be at least as great as the Bayes probability of errorR{\^{}}{\{}$\backslash$ast{\}}--the minimum probability of error over all decision rules taking underlying probability structure into account. However, in a large sample analysis, we will show in theM-category case thatR{\^{}}{\{}$\backslash$ast{\}} $\backslash$leq R $\backslash$leq R{\^{}}{\{}$\backslash$ast{\}}(2 --MR{\^{}}{\{}$\backslash$ast{\}}/(M-1)), where these bounds are the tightest possible, for all suitably smooth underlying distributions. Thus for any number of categories, the probability of error of the nearest neighbor rule is bounded above by twice the Bayes probability of error. In this sense, it may be said that half the classification information in an infinite sample set is contained in the nearest neighbor.},
author = {Cover, T. M. and Hart, P. E.},
doi = {10.1109/TIT.1967.1053964},
isbn = {0018-9448},
issn = {15579654},
journal = {IEEE Transactions on Information Theory},
keywords = {Pattern classification},
IGNOREmonth = {jan},
number = {1},
pages = {21--27},
pmid = {21919855},
shorttitle = {Information Theory, IEEE Transactions on},
title = {{Nearest Neighbor Pattern Classification}},
volume = {13},
year = {1967}
}
@article{Perez2004,
author = {P{\'{e}}rez, Patrick and Vermaak, Jaco and Blake, Andrew},
doi = {10.1109/JPROC.2003.823147},
isbn = {0018-9219},
issn = {00189219},
journal = {Proceedings of the IEEE},
keywords = {Color,Data fusion,Motion,Particle filters,Sound,Visual tracking},
IGNOREmonth = {mar},
number = {3},
pages = {495--513},
shorttitle = {Proceedings of the IEEE},
title = {{Data Fusion for Visual Tracking with Particles}},
volume = {92},
year = {2004}
}
@article{Hu2014,
abstract = {This work addresses the problem of predicting the Remaining Useful Life (RUL) of components for which a mathematical model describing the component degradation is available, but the values of the model parameters are not known and the observations of degradation trajectories in similar components are unavailable. The proposed approach solves this problem by using a Particle Filtering (PF) technique combined with a kernel smoothing (KS) method. This PF-KS method can simultaneously estimate the degradation state and the unknown parameters in the degradation model, while significantly overcoming the problem of particle impoverishment. Based on the updated degradation model (where the unknown parameters are replaced by the estimated ones), the RUL prediction is then performed by simulating future particles evolutions. A numerical application regarding prognostics for Lithium-ion batteries is considered. Various performance indicators measuring precision, accuracy, steadiness and risk of the obtained RUL predictions are computed. The obtained results show that the proposed PF-KS method can provide more satisfactory results than the traditional PF methods.},
author = {Hu, Yang and Baraldi, Piero and {Di Maio}, Francesco and Zio, Enrico},
doi = {10.1016/j.ress.2014.10.003},
file = {:home/toni/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Hu et al. - 2015 - A particle filtering and kernel smoothing-based approach for new design component prognostics.pdf:pdf},
issn = {09518320},
journal = {Reliability Engineering and System Safety},
keywords = {Battery,Kernel smoothing,Parameter estimation,Particle filtering,Prognostics,Remaining useful life},
IGNOREmonth = {feb},
pages = {19--31},
title = {{A Particle filtering and Kernel Smoothing-Based Approach for New Design Component Prognostics}},
volume = {134},
year = {2014}
}
@article{Paul2009,
abstract = {Solutions for indoor tracking and localization have become more critical with recent advancement in context and location-aware technologies. The accuracy of explicit positioning sensors such as global positioning system (GPS) is often limited for indoor environments. In this paper, we evaluate the feasibility of building an indoor location tracking system that is cost effective for large scale deployments, can operate over existing Wi-Fi networks, and can provide flexibility to accommodate new sensor observations as they become available. This paper proposes a sigma-point Kalman smoother (SPKS)-based location and tracking algorithm as a superior alternative for indoor positioning. The proposed SPKS fuses a dynamic model of human walking with a number of low-cost sensor observations to track 2-D position and velocity. Available sensors include Wi-Fi received signal strength indication (RSSI), binary infra-red (IR) motion sensors, and binary foot-switches. Wi-Fi signal strength is measured using a receiver tag developed by Ekahau, Inc. The performance of the proposed algorithm is compared with a commercially available positioning engine, also developed by Ekahau, Inc. The superior accuracy of our approach over a number of trials is demonstrated.},
author = {Paul, Anindya S. and Wan, Eric A.},
doi = {10.1109/JSTSP.2009.2032309},
isbn = {1932-4553},
issn = {19324553},
journal = {IEEE Journal on Selected Topics in Signal Processing},
keywords = {Bayesian inference,Indoor tracking,Received signal strength indication (RSSI)-based localization,Sigma-point Kalman filter,Sigma-point Kalman smoother,State estimation},
IGNOREmonth = {oct},
number = {5},
pages = {860--873},
shorttitle = {IEEE Journal of Selected Topics in Signal Processi},
title = {{RSSI-Based Indoor Localization and Tracking using Sigma-Point Kalman Smoothers}},
volume = {3},
year = {2009}
}
@article{Li2014,
abstract = {During the last two decades there has been a growing interest in Particle Filtering (PF). However, PF suffers from two long-standing problems that are referred to as sample degeneracy and impoverishment. We are investigating methods that are particularly efficient at Particle Distribution Optimization (PDO) to fight sample degeneracy and impoverishment, with an emphasis on intelligence choices. These methods benefit from such methods as Markov Chain Monte Carlo methods, Mean-shift algorithms, artificial intelligence algorithms (e.g.; Particle Swarm Optimization, Genetic Algorithm and Ant Colony Optimization), machine learning approaches (e.g.; clustering, splitting and merging) and their hybrids, forming a coherent standpoint to enhance the particle filter. The working mechanism, interrelationship, pros and cons of these approaches are provided. In addition, approaches that are effective for dealing with high-dimensionality are reviewed. While improving the filter performance in terms of accuracy, robustness and convergence, it is noted that advanced techniques employed in PF often causes additional computational requirement that will in turn sacrifice improvement obtained in real life filtering. This fact, hidden in pure simulations, deserves the attention of the users and designers of new filters. ?? 2013 Elsevier Ltd. All rights reserved.},
author = {Li, Tiancheng and Sun, Shudong and Sattar, Tariq Pervez and Corchado, Juan Manuel},
doi = {10.1016/j.eswa.2013.12.031},
file = {:home/toni/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Li et al. - 2014 - Fight sample degeneracy and impoverishment in particle filters A review of intelligent approaches.pdf:pdf},
isbn = {0957-4174},
issn = {09574174},
journal = {Expert Systems with Applications},
keywords = {Artificial intelligence,Impoverishment,Machine learning,Markov Chain Monte Carlo,Particle filter,Sequential Monte Carlo},
mendeley-groups = {IPIN 2017},
number = {8},
pages = {3944--3954},
title = {{Fight Sample Degeneracy and Impoverishment in Particle Filters: A Review of Intelligent Approaches}},
volume = {41},
year = {2014}
}
@article{Driessen2005,
abstract = {An efficient particle filtering algorithm is presented for state estimation of jump Markov nonlinear systems. The standard particle filter can easily suffer from particle degeneracy around mode changes. The new algorithm allows the user to fully control the number of particles in a certain mode, without distorting or violating the Markov property. This property can be exploited to prevent the filter degenerating.},
author = {Driessen, H. and Boers, Y.},
doi = {10.1049/ip-rsn:20045075},
file = {:home/toni/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Driessen, Boers - 2005 - Efficient particle filter for jump Markov nonlinear systems.pdf:pdf},
issn = {1350-2395},
journal = {Radar, Sonar and Navigation, IEE Proceedings -},
mendeley-groups = {IPIN 2017},
number = {5},
pages = {323--326},
title = {{Efficient Particle Filter for Jump Markov Nonlinear Systems}},
volume = {152},
year = {2005}
}
@article{Li2015b,
abstract = {Two decades ago, with the publication of [1], we witnessed the rebirth of particle filtering (PF) as a methodology for sequential signal processing. Since then, PF has become very popular because of its ability to process observations represented by nonlinear state-space models where the noises of the model can be non-Gaussian. This methodology has been adopted in various fields, including finance, geophysical systems, wireless communications, control, navigation and tracking, and robotics [2]. The popularity of PF has also spurred the publication of several review articles [2]-[6].},
author = {Li, Tiancheng and Boli{\'{c}}, Miodrag and Djuri{\'{c}}, Petar M.},
doi = {10.1109/MSP.2014.2330626},
issn = {10535888},
journal = {IEEE Signal Processing Magazine},
number = {3},
pages = {70--86},
title = {{Resampling Methods for Particle Filtering: Classification, Implementation, and Strategies}},
volume = {32},
year = {2015}
}
@article{Sun2013,
author = {Sun, S. and Li, T. and Sattar, T.P.},
IGNOREdoi = {10.1049/el.2013.0233},
isbn = {1350-911X},
issn = {0013-5194},
journal = {Electronics Letters},
mendeley-groups = {IPIN 2017},
number = {12},
pages = {740--742},
title = {{Adapting Sample Size in Particle Filters through KLD-resampling}},
volume = {49},
year = {2013}
}
@inproceedings{Xiaoqin2008,
abstract = {Visual tracking usually involves an optimization process for estimating the motion of an object from measured images in a video sequence. In this paper, a new evolutionary approach, PSO (particle swarm optimization), is adopted for visual tracking. Since the tracking process is a dynamic optimization problem which is simultaneously influenced by the object state and the time, we propose a sequential particle swarm optimization framework by incorporating the temporal continuity information into the traditional PSO algorithm. In addition, the parameters in PSO are changed adaptively according to the fitness values of particles and the predicted motion of the tracked object, leading to a favourable performance in tracking applications. Furthermore, we show theoretically that, in a Bayesian inference view, the sequential PSO framework is in essence a multilayer importance sampling based particle filter. Experimental results demonstrate that, compared with the state-of-the-art particle filter and its variation - the unscented particle filter, the proposed tracking algorithm is more robust and effective, especially when the object has an arbitrary motion or undergoes large appearance changes.},
author = {Xiaoqin, Zhang and Weiming, Hu and Maybank, S and Xi, Li and Mingliang, Zhu},
booktitle = {Computer Vision and Pattern Recognition, 2008. CVPR 2008. IEEE Conference on},
doi = {10.1109/CVPR.2008.4587512},
file = {:home/toni/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Xiaoqin Zhang et al. - 2008 - Sequential particle swarm optimization for visual tracking.pdf:pdf},
isbn = {1063-6919},
issn = {1063-6919},
keywords = {Bayes methods,Bayesian inference view,Bayesian methods,Inference algorithms,Monte Carlo methods,Motion measurement,Nonhomogeneous media,Particle filters,Particle swarm optimization,Particle tracking,Video sequences,image sampling,image sequences,importance sampling,motion estimation,multilayer importance sampling,particle filtering (numerical methods),particle swarm optimisation,sequential particle swarm optimization,temporal continuity information,unscented particle filter,video sequence,video signal processing,visual tracking},
mendeley-groups = {IPIN 2017},
pages = {1--8},
publisher = {IEEE},
title = {{Sequential Particle Swarm Optimization for Visual Tracking}},
year = {2008}
}
@inproceedings{Zhang2013,
abstract = {This paper presents a wireless network infrastructure based localization system using ultrasonic transmitter and receiver for obtaining accurate TDOA measurements and Interacting Multiple Model (IMM) estimator for calculating the actual position of the target by running two filters, i.e. extended Kalman filter (EKF) and robust extended Kalman filter (REKF), which offers the protection against the noise in both line-of-sight (LOS) and non-line-of-sight (NLOS) environments. The experiment results showed that the system utilized the advantages of EKF and REKF for different environments and thus was able to provide a localization solution with high accuracy.},
author = {Zhang, Rui and H{\"{o}}flinger, Fabian and Reindl, Leonhard},
booktitle = {IEEE Transactions on Instrumentation and Measurement},
doi = {10.1109/TIM.2013.2256713},
file = {:home/toni/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Zhang, Hoflinger, Reindl - 2013 - TDOA-Based Localization Using Interacting Multiple Model Estimator and Ultrasonic TransmitterReceiver.pdf:pdf},
isbn = {9781467315906},
issn = {00189456},
keywords = {Indoor localization,Kalman filter,M-estimator,interacting multiple model (IMM),time difference of arrival (TDOA),ultrasound},
mendeley-groups = {IPIN 2017},
number = {8},
pages = {2205--2214},
title = {{TDOA-Based Localization using Interacting Multiple Model Estimator and Ultrasonic Transmitter/Receiver}},
volume = {62},
year = {2013}
}
@article{Bar-Shalom1988,
abstract = {An important problem is the estimation of the state of a linear system with Markovian switching coefficients. In this problem, the dynamics of the system is represented by multiple models which are hypothesized to be correct. The Interacting Multiple Model (IMM) algorithm is a novel approach to merging the different model hypotheses. In the IMM algorithm, the state estimate is computed under each possible model hypothesis over the most recent sampling period with each model using a different combination of previous model-conditioned estimates. In this paper, the second order Interacting Multiple Model (IMM2) algorithm is developed for estimating the state of a linear system with Markovian switching coefficients. In the IMM2 algorithm, the state estimate is computed under each possible model hypothesis over the two most recent sampling periods with each model hypothesis using a different combination of the previous model-conditioned estimates. Simulation results are given for a target tracking example to demonstrate the performance of the IMM2 algorithm relative to that of the IMM and second order Generalized Pseudo-Bayesian algorithms.},
author = {Bar-Shalom, Yaakov},
doi = {10.1109/9.1299},
file = {:home/toni/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Blom, Bar-Shalom - 1988 - The interacting multiple model algorithm for systems with Markovian switching coefficients.pdf:pdf},
isbn = {0-7803-0860-3},
issn = {00189286},
journal = {IEEE Transactions on Automatic Control},
mendeley-groups = {IPIN 2017},
number = {8},
pages = {780--783},
title = {{Interacting Multiple Model Algorithm for Systems with Markovian Switching Coefficients.}},
volume = {33},
year = {1988}
}
@article{Boers2003,
abstract = {A new method for multiple model particle (nonlinear) filtering for Markovian switching systems is presented. This new method is a combination of the interacting multiple model (IMM) filter and a (regularised) particle filter. The mixing and interaction is similar to that in a conventional IMM filter. However, in every mode a regularised particle filter is running. The regularised particle filter probability density is a mixture of Gaussian probability densities. The proposed method is able to deal with nonlinearities and non-Gaussian noise. Furthermore, the new method keeps a fixed number of particles in each mode, and therefore it does not suffer from the potential drawbacks of existing multiple model particle filters for Markovian switching systems.},
author = {Boers, Y and Driessen, J N},
doi = {10.1049/ip-rsn},
file = {:home/toni/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Boers, Driessen - 2003 - Interacting multiple model particle filter.pdf:pdf},
issn = {13502395},
journal = {October},
mendeley-groups = {IPIN 2017},
number = {5},
pages = {344--349},
title = {{Interacting Multiple Model Particle Filter}},
volume = {150},
year = {2003}
}
@inproceedings{Fetzer-16,
author = {T. Fetzer and F. Ebner and L. K{\"o}ping and M. Grzegorzek and F. Deinzer},
title = {{On Monte Carlo Smoothing in Multi Sensor Indoor Localisation}},
booktitle = {Indoor Positioning and Indoor Navigation (IPIN), Int. Conf. on},
editor = {},
year = {2016},
publisher = {IEEE},
pages = {},
address = {Madrid, Spain},
issn = {}
}
@INPROCEEDINGS{Fetzer-17,
author={T. Fetzer and F. Ebner and F. Deinzer and M. Grzegorzek},
booktitle={Indoor Positioning and Indoor Navigation (IPIN), Int. Conf. on},
title={{Recovering from Sample Impoverishment in Context of Indoor Localisation}},
year={2017},
volume={},
address = {Sapporo, Japan},
publisher = {IEEE},}
@misc{Rothenburg,
author = {H. M{\"o}hring},
title = {{Reichsstadtmuseum Rothenburg}},
note = {\url{http://reichsstadtmuseum.rothenburg.de}, Accessed: 2018-03-22},
address = {{Rothenburg, Germany}},
}
@article{farid2013recent,
title={{Recent Advances in Wireless Indoor Localization Techniques and System}},
author={Farid, Zahid and Nordin, Rosdiadee and Ismail, Mahamod},
journal={Journal of Computer Networks and Communications},
volume={2013},
year={2013},
publisher={Hindawi}
}
@inproceedings{Bullmann-18,
author={Bullmann, Markus and Fetzer, Toni and Ebner, Frank and Grzegorzek, Marcin and Deinzer, Frank},
booktitle={21th Int. Conf. on Information Fusion (FUSION)},
title={{Fast Kernel Density Estimation using Gaussian Filter Approximation}},
year={2018},
IGNOREmonth={October},
pages={1245-1252}
}
@book{goldberg89,
added-at = {2017-04-11T02:23:13.000+0200},
author = {Goldberg, D. E.},
biburl = {https://www.bibsonomy.org/bibtex/2af6ec8ef88eb576d7ecc8ac3a84126a3/geovani},
interhash = {79bb58f1d9d57b042cf0f771784d4adb},
intrahash = {af6ec8ef88eb576d7ecc8ac3a84126a3},
keywords = {},
owner = {gregor},
publisher = {Addison-Wesley},
timestamp = {2017-04-11T02:23:13.000+0200},
title = {Genetic Algorithms in Search, Optimization, and Machine Learning},
year = 1989
}
@ARTICLE{Kirkpatrick83optimizationby,
author = {S. Kirkpatrick and C. D. Gelatt and M. P. Vecchi},
title = {{Optimization by Simulated Annealing}},
journal = {Science},
year = {1983},
volume = {220},
number = {4598},
pages = {671--680}
}
@article{silverman1982algorithm,
title={{Algorithm AS 176: Kernel Density Estimation using the Fast Fourier Transform}},
author={Silverman, BW},
journal={Journal of the Royal Statistical Society. Series C (Applied Statistics)},
volume={31},
number={1},
pages={93--99},
year={1982},
publisher={JSTOR}
}
@misc{Wemos,
title = {{WEMOS Electronics}},
note = {\url{https://www.wemos.cc/}, Accessed: 2018-03-22},
address = {{Rothenburg, Germany}},
}
@article{torres2017smartphone,
title={The Smartphone-Based Offline Indoor Location Competition at IPIN 2016: Analysis and Future Work},
author={Torres-Sospedra, Joaqu{\'\i}n and Jim{\'e}nez, Antonio R and Knauth, Stefan and Moreira, Adriano and Beer, Yair and Fetzer, Toni and Ta, Viet-Cuong and Montoliu, Raul and Seco, Fernando and Mendoza-Silva, Germ{\'a}n M and others},
journal={Sensors},
volume={17},
number={3},
pages={557},
year={2017},
publisher={Multidisciplinary Digital Publishing Institute}
}
@phdthesis{navMesh1,
author = {Arkin, Ronald Craig},
year = {1987},
REM_month = {9},
REM_pages = {336},
school = {University of Massachusetts},
title = {{Towards Cosmopolitan Robots : Intelligent Navigation in Extended Man-made Environments}}
}
@article{davidson2017survey,
title={{A Survey of Selected Indoor Positioning Methods for Smartphones}},
author={Davidson, Pavel and Pich{\'e}, Robert},
journal={IEEE Communications Surveys \& Tutorials},
volume={19},
number={2},
pages={1347--1370},
year={2017},
publisher={IEEE}
}
@INPROCEEDINGS{navMeshAlg1,
author={W. van Toll and A. F. Cook and R. Geraerts},
booktitle={2011 IEEE/RSJ International Conference on Intelligent Robots and Systems},
title={Navigation meshes for realistic multi-layered environments},
year={2011},
REM_volume={},
REM_number={},
pages={3526-3532},
REM_keywords={mesh generation;navigation;virtual reality;navigation meshes;realistic multilayered environments;virtual characters;path planning;airport;multistorey building;two-dimensional polygons;Navigation;Data structures;Complexity theory;Buildings;Airports;Path planning;Graphics},
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volume={11},
number={3},
pages={19-21},
keywords={IEEE standards;radio spectrum management;wireless LAN;working group;IEEE Local Area Network Metropolitan Area Network Standards Committee;IEEE LAN-Metropolitan Area Network Standards Committee;IEEE LMSC;wireless LANs;WLAN;unlicensed spectrum;IEEE 802.11mc;IEEE 802.11ai;frequency 2.4 GHz;frequency 5 GHz;frequency 60 GHz;IEEE 802.11 Standard;Protocols;Throughput;Next generation networking;Wireless LAN;Timing},
doi={10.1109/MVT.2016.2586398},
ISSN={1556-6080},
month={Sep.},}
@misc{Android_RTT,
title={Wi-Fi location: ranging with RTT},
author={{Google and Open Handset Alliance}},
note={(Visited: 17.01.2020)},
howpublished={\url{https://developer.android.com/guide/topics/connectivity/wifi-rtt}},
year={2019}
}
@inproceedings{banin2016wifi,
title={WiFi FTM and map information fusion for accurate positioning},
author={Banin, Leor and Schatzberg, Uri and Amizur, Yuval},
booktitle={2016 International Conference on Indoor Positioning and Indoor Navigation (IPIN)},
year={2016}
}
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