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added heading and step detection to transition

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toni
2018-09-20 10:24:23 +02:00
parent 09188dd32e
commit 3fd79ed899
7 changed files with 44 additions and 25 deletions
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tex/chapters/abstract.tex
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@@ -1,8 +1,8 @@
\abstract{
Within this work we present an updated version of our award-winning indoor localization system for smartphones.
The current position is given by means of recursive state estimation using a particle filter to incorporate different probabilistic sensor models.
Absolute positioning information is given by a comparison between recent \docWIFI{} measurements of nearby access-points and signal strength predictions.
Instead of using time-consuming approaches like classic fingerprinting or measuring the exact positions of access-points, we use an optimization scheme based on a few reference measurements to estimate a corresponding \docWIFI{} model.
Absolute positioning information is given by a comparison between recent \docWIFI{} measurements of nearby access points and signal strength predictions.
Instead of using time-consuming approaches like classic fingerprinting or measuring the exact positions of access points, we use an optimization scheme based on a few reference measurements to estimate a corresponding \docWIFI{} model.
To model the pedestrian's movement, which is constrained by walls and other obstacles, we propose a state transition based upon navigation meshes, modeling only the building's walkable areas.
Continuous and smooth floor changes are enabled by using a simple activity recognition.
Our rapid computation scheme of the kernel density estimation allows to find an exact estimation of the pedestrian's current position.