fixed baraomter issue (skip first few readings due to sensor errors)

added new eval using shortest-path + plotting
removed compiler warnings for clean-code
fixed some minor issues
added new TeX code and new graphics

tex/chapters/experiments.tex

@@ -21,3 +21,6 @@
 mit pfad laeuft es falsch, weil die andere treppe kuerzer zum ziel ist und das wlan dort besser passt}
 
 \commentByFrank{zu grosser einfluss vom pfad ist also kein allheilmittel.. kann, wie beim treppenhaus, auch nach hinten los gehen}
+
+
+\commentByFrank{path1: bad start due to nearby AP and bad parameters (path-loss too high)}

tex/chapters/grid.tex

@@ -12,3 +12,9 @@
 \subsection{Weighting}
 
 \subsection{Pathfinding}
+
+	\commentByFrank{describe the multi-path version}
+	
+	\commentByFrank{describe the single-path version}
+	\commentByFrank{exp-dist for distance to the path. more distance = less-likely}
+	\commentByFrank{lambda-factor controls the allowed deviation from the shortest-path}

tex/chapters/sensors.tex

@@ -6,26 +6,41 @@
 		preferred over absolute ones. However, due to noisy sensors \todo{cite oder grafik? je nach platz}, one
 		single reading is not enough as a relative base. Harnessing the usual setup time of a navigation-system (
 		route calculation, user checking the route) we use the average of all barometer readings during this
-		timeframe as realtive base $\overline{\mPressure}$.
+		timeframe as realtive base $\overline{\mObsPressure}$. However, it is often necessary to omit the first few
+		sensors readings, as the sensor needs some time to settle and the estimated base would otherwise be far off
+		the real values (see fig. \ref{fig:baroSetupError}). Besides, we use the system's setup time to estimate the
+		sensors uncertainty $\sigma_\text{baro}$ for later use within the evaluation.
 		
-		During each transition from $\mStateVec_{t-1}$ to $\mStateVec_t$, the predicted pressure $\mStatePressure$ is
-		adjusted according to the resulting $z$-change, if any:
+		\begin{figure}
+			\include{gfx/baro/baro_setup_issue}
+			\caption{Sometimes the barometer provides erroneous \SI{}{\hpa} readings during the first seconds. Those
+			need to be omitted before $\sigma_\text{baro}$ and $\overline{\mObsPressure}$ are estimated.}
+			\label{fig:baroSetupError}
+		\end{figure}
+		
+		During each transition from $\mStateVec_{t-1}$ to $\mStateVec_t$, we need a corresponding, relative pressure
+		prediction $\mStatePressure$ which is adjusted according to the resulting $z$-change, if any:
 		
 		\begin{equation}
 			\mState_{t}^{\mStatePressure} = \mState_{t-1}^{\mStatePressure} + \Delta z \cdot \SI{0.105}{\hpa}
 			,\enskip
 			\Delta z = \mState_{t-1}^{z} - \mState_{t}^z
 			.
+			\label{eq:baroTransition}
 		\end{equation}
 		
-		Within the evaluation bla bla
+		The evaluation following the transition then compares the predicted relative pressure with the observed one
+		using a normal distribution with the previously estimated $\sigma_\text{baro}$:
 		
 		\begin{equation}
-			xx
+			p(\mObsVec_t \mid \mStateVec_t)_\text{baro} = \mathcal{N}(\mObs_t^{\mObsPressure} \mid \mState_t^{\mStatePressure}, \sigma_\text{baro}).
+			\label{eq:baroEval}
 		\end{equation}
 		
-		we use the system's setup time to not only determine the relative base but also for estimating the barometers
-		uncertainty \sigma_\text{baro} used within the evaluation.
+		
+		
+		
+		
 		
 	\subsection{Wi-Fi \& iBeacons}
 		For additional absolute location hints, we use the Smartphones Wi-Fi and iBeacon sensor to measure the signal-strengths
@@ -40,7 +55,7 @@
 		and calculate the resulting probability as described in \cite{ipin2015}:
 		
 		\begin{equation}
-			\mProb(\mObsVec \mid \mStateVec)_\text{wifi} =
+			\mProb(\mObsVec_t \mid \mStateVec_t)_\text{wifi} =
 			\prod\limits_{i=1}^{n} \mathcal{N}(\mRssi_\text{wifi}^{i} \mid P_{r}(\mMdlDist_{i}, \Delta{f_{i}}), \sigma_{\text{wifi}}^2).
 			\label{eq:wifiTotal}
 		\end{equation}
@@ -56,6 +71,9 @@
 		Again, $\mPLE$ is determined emprically. \todo{faellt hier meist kleiner aus, weil ja kuerzere reichweite etc}
 	
 	
+	
+	
+	
 	\subsection{Step- \& Turn-Detection}
 		
 		To prevent degradation within the particle-filter \cite{??} due to downvoting of particles with increased