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sensors, baro + wifi druebergeschaut

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toni
2016-02-11 20:17:03 +01:00
parent b1da0de3f9
commit 05d97b1c19
3 changed files with 40 additions and 43 deletions
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8
tex/chapters/system.tex
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@@ -41,8 +41,6 @@ By assuming statistical independence of all sensor models, the probability densi
\begin{equation}
\begin{split}
&p(\vec{o}_t \mid \vec{q}_t, \vec{q}_{t-1}) = \\
&p(\vec{o}_t \mid \vec{q}_t, \vec{q}_{t-1})_\text{turn}
\,p(\vec{o}_t \mid \vec{q}_t, \vec{q}_{t-1})_\text{step} \\
&p(\vec{o}_t \mid \vec{q}_t)_\text{baro}
\,p(\vec{o}_t \mid \vec{q}_t)_\text{ib}
\,p(\vec{o}_t \mid \vec{q}_t)_\text{wifi}
@@ -50,9 +48,9 @@ By assuming statistical independence of all sensor models, the probability densi
\label{eq:evalBayes}
\end{equation}
%
\commentByFrank{die zeile in der mitte (step/turn) faellt ganz weg. also generell kein $q_{t-1}$ mehr}
%
Here, every single component refers to a probabilistic sensor model.
The heading information is evaluated using $p(\vec{o}_t \mid \vec{q}_t, \vec{q}_{t-1})_\text{turn}$, the step length using a step detection process by $p(\vec{o}_t \mid \vec{q}_t, \vec{q}_{t-1})_\text{step}$, using $p(\vec{o}_t \mid \vec{q}_t)_\text{baro}$ the barometer evaluates the current floor, whereby absolute position information is given by $p(\vec{o}_t \mid \vec{q}_t)_\text{ib}$ for iBeacons and by $p(\vec{o}_t \mid \vec{q}_t)_\text{wifi}$ for Wi-Fi.
The barometer information is evaluated using $p(\vec{o}_t \mid \vec{q}_t)_\text{baro}$, whereby absolute position information is given by $p(\vec{o}_t \mid \vec{q}_t)_\text{ib}$ for iBeacons and by $p(\vec{o}_t \mid \vec{q}_t)_\text{wifi}$ for Wi-Fi.
\todo{art unseres particle filters hier einfuehren. transition als proposal. dann kann man spaeter bei step und turn besser begruenden warum wir es in die transition ziehen.}