toni/IPIN2016
2
0
Fork 0
Code Issues Pull Requests Releases Wiki Activity

final version of paper

Browse Source
This commit is contained in:
toni
2016-06-02 15:57:53 +02:00
parent 0f4435f86a
commit 927bec3e60
14 changed files with 119 additions and 132 deletions
Download Patch File Download Diff File Expand all files Collapse all files

4
tex/chapters/relatedwork.tex
View File

@@ -38,10 +38,10 @@ For example, in \cite{Platzer:2008} a particle smoother is used to reduce multim
%smoothing im bezug auf indoor
Nevertheless, there are some promising approaches for indoor localisation systems as well.
For example \cite{Nurminen2014} deployed a fixed-interval forward-backward smoother to improve the position estimation for non-real-time applications.
For example \cite{Nurminen13-PSI} deployed a fixed-interval forward-backward smoother to improve the position estimation for non-real-time applications.
They combined \docWIFI{}, step and turn detection, a simple line-of-sight model for floor plan restrictions and the barometric change within a particle filter.
The state transition samples a new state based on the heading change, altitude change and a fixed step length.
The experiments of \cite{Nurminen2014} clearly emphasise the benefits of smoothing techniques. The estimation error could be decreased significantly.
The experiments of \cite{Nurminen13-PSI} clearly emphasise the benefits of smoothing techniques. The estimation error could be decreased significantly.
However, a fixed-lag smoother was discussed only in theory.
In the work of \cite{Paul2009} both fixed-interval and fixed-lag smoothing were presented.