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TeX and helper code

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FrankE
2017-04-25 14:48:04 +02:00
parent 8a3de63075
commit fe9c25cde5
3 changed files with 136 additions and 52 deletions
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tex/chapters/experiments.tex
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@@ -4,7 +4,7 @@
alles im FHWS gebäude [korrekte groesse fuer beide gebaeude!] mit nem nexus 6
}
Within all \docWIFI{} observations we only consider the \docAP{}s that are permanently installed
Within all \docWIFI{} observations (offline and online) we only consider the \docAP{}s that are permanently installed
within the building. Temporal and movable transmitters are ignored as they might cause estimation errors.
@@ -51,14 +51,13 @@
% visible APs:
% cnt(121) min(2.000000) max(22.000000) range(20.000000) med(8.000000) avg(9.322314) stdDev(4.386709)
As mentioned earlier we will look at various optimization strategies.
As mentioned in section \ref{sec:optimization}, we will look at various optimization strategies:
{\bf\noOptEmpiric{}} uses the same three parameters \mTXP,\mPLE,\mWAF for each \docAPshort{} in combination
with its position, which is well known from the flooprlan.
{\bf\noOptEmpiric{}} uses the same three empiric parameters \mTXP{}, \mPLE{}, \mWAF{} for each \docAPshort{} in combination
with its position, which is well known from the floorplan.
{\bf\optParamsAllAP{}} is the same as above, except that the three parameters are optimized
based on the reference measurements.
using the reference measurements.
{\bf\optParamsEachAP{}} optimizes the three parameters per \docAP{} instead of using the same
parameters for all.
@@ -67,36 +66,59 @@
(3D position, \mTXP, \mPLE, \mWAF) based on the reference measurements.
{\bf\optPerFloor{}} and {\bf\optPerRegion{}} are just like \optParamsPosEachAP{} except that
there are several instances that are optimized only for one floor / region instead of the whole building.
there are several sub-models that are optimized for one floor / region instead of the whole building.
Figure \ref{fig:wifiModelError} shows the optimization results for all strategies, which are as expected:
The estimation error is indirectly proportional to the number of optimized parameters.
However, even with \optPerRegion{} the maximal error is relatively high due to some locations that do
not fit the model at all. Looking at the optimization results for \mTXP{}, \mPLE{} and \mWAF{} supports
this finding. While the median for those values based on all optimized transmitters is totally sane
(-42, 2.4, 6.0), the minimum and maximum values are clearly outside of the physically possible range.
\begin{figure}
\input{gfx/wifi_model_error_0_95.tex}
\input{gfx/wifi_model_error_95_100.tex}
\label{fig:wifiModelError}%
\caption{%
Comparison between different optimization strategies by examining the error (in \decibel) at each reference measurement.%
The higher the number of variable parameters, the better the model resembles real world conditions. %
}%
\label{fig:wifiModelError}
\caption{
Comparison between different optimization strategies by examining the error (in \decibel) at each reference measurement.
The higher the number of variable parameters, the better the model resembles real world conditions.
}
\end{figure}
%TXP: cnt(34) min(-67.698959) max(4.299183) range(71.998146) med(-41.961170) avg(-41.659286) stdDev(17.742294)
%EXP: cnt(34) min(0.932817) max(4.699000) range(3.766183) med(2.380410) avg(2.546959) stdDev(1.074687)
%WAF: cnt(34) min(-27.764957) max(5.217187) range(32.982143) med(-5.921916) avg(-7.579522) stdDev(5.840527)
%Pos: cnt(34) min(3.032438) max(26.767128) range(23.734690) med(7.342710) avg(8.571227) stdDev(4.801449)
Looking at figure \ref{fig:wifiIndoorOutdoor} indicates the strong attenuation imposed by the metallised
windows installed within our building. Even though the transmitter is only \SI{5}{\meter} away from the reference
measurement, the windows attenuate the signal as much as \SI{50}{\meter} of corridor.
While \optPerRegion{} is able to overcome some of those situations, it requires a profound prior knowledge
when selecting the regions that model should work with.
%Such issues can only be fixed using more appropriate models that consider walls and other obstacles.
\begin{figure}
\centering
\input{gfx/compare-wifi-in-out.tex}
\label{fig:wifiIndoorOutdoor}
\caption{
Measurable signal strengths of a testing \docAPshort{} (black dot).
While the signal diminishes slowly along the corridor (upper rectangle)
the metallised windows (dashed outline) attenuate the signal by over \SI{30}{\decibel} (lower rectangle).
}
\end{figure}
\begin{figure}
\centering
\input{gfx/compare-wifi-in-out.tex}
\caption{
Measurable signal strengths of a testing \docAPshort{} (black dot).
While the signal diminishes slowly along the corridor (upper rectangle)
the metallised windows (dashed outline) attenuate the signal by over \SI{30}{\decibel} (lower rectangle).
}
\end{figure}
fenster sind metallbedampft und schirmen stark ab
siehe beispielgrafik
\todo{
distance between AP pos estimation and real position???
}
BESCHREIBEN
\begin{figure}
\centering
\input{gfx/wifiOptApPosDifference.tex}
\caption{UNNÖTIG?}
\end{figure}
% -------------------------------- number of fingerprints -------------------------------- %
@@ -193,7 +215,7 @@
% -------------------------------- plots indicating optimization issues -------------------------------- %
% -------------------------------- plots indicating walk issues -------------------------------- %
\begin{figure}
\input{gfx/wifiMultimodality.tex}