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finished wifi. some todos left

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toni
2018-05-17 11:47:26 +02:00
parent a184c5af00
commit 64548fcc21
6 changed files with 166 additions and 28 deletions
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tex/chapters/system.tex
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@@ -18,7 +18,7 @@ The filtering equation to calculated the posterior is given by the recursion
\end{equation}
%
where $\mState$ is the hidden state and $\mObs_t$ provides the corresponding observation vector at time $t$.
As realization of \eqref{equ:bayesInt} we use the well-known CONDENSATION algorithm \cite{Isard98:CCD}.
As realization of \eqref{equ:bayesInt} we use the well-known CONDENSATION particle filter \cite{Isard98:CCD}.
Here, the transition is used as proposal distribution and a resampling step is utilized to handle the phenomenon of weight degeneracy.
The state $\mState$ is given by
@@ -36,6 +36,6 @@ The observation vector is defined as
\end{equation}
%
Here, $\mRssiVec_\text{wifi}$ contains the signal strength measurements of all \docAP{}s currently visible to the phone. $\mObsHeading$ provides the relative angular change and $\mObsSteps$ the number of steps since the last filter-step.
The result of a simple activity recognition using the phone's barometer is given by $\mObsActivity$, which is one of: unknown, standing, walking, walking up the stairs or walking down the stairs.
The result of a simple activity recognition using the phone's barometer is given by $\mObsActivity$, which is one of: standing, walking, walking up or walking down.