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FrankE
2017-05-08 19:30:53 +02:00
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tex/chapters/experiments.tex
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@@ -542,10 +542,15 @@
Removing this (valid) information will increase the error for such situations.
However, incorporating additional knowledge provided by virtual \docAP{}s (see section \ref{sec:vap}) mitigated this issues.
If only one out of six virtual networks is seen, this observation is likely to be erroneous, no matter
what the corresponding signal strength indicates. This approach improved the location estimation especially
for areas where a transmitter was hardly seen within the reference measurements and its optimization is thus
expected to be inaccurate.
If e.g. only one out of six virtual networks is seen, this observation is likely to be erroneous, no matter
what the corresponding signal strength indicates.
As those occasions are relatively seldom, the impact is a minor one.
Nevertheless, depending on the used prediction model, a handful of major estimation errors were prevented.
Additionally, among all examined models and walks, there was none where this approached lead to increased error values.
%This approach improved the location estimation especially
%for areas where a transmitter was hardly seen within the reference measurements and its optimization is thus
%expected to be inaccurate.
Using a smaller $\sigma$ or a stricter exponential distribution for the model vs. scan comparison in \refeq{eq:wifiProb}
had a positive effect on the misclassification error for some of the walks, but also slightly increased the overall estimation error.