some new TeX aspects

This commit is contained in:
2016-02-05 20:20:52 +01:00
parent 593f4d582b
commit 9e9b6882cd
4 changed files with 79 additions and 7 deletions

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@@ -95,6 +95,7 @@
\newcommand{\percent}{\%}
\newcommand{\decibel}{dB}
\newcommand{\dB}{dB}
\newcommand{\hpa}{hPa}
\newcommand{\degree}{\ensuremath{^{\circ}}}
% missing math operators

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@@ -8,7 +8,56 @@
route calculation, user checking the route) we use the average of all barometer readings during this
timeframe as realtive base $\overline{\mPressure}$.
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{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
.
\end{equation}
\subsection{Wi-Fi \& iBeacons}
For additional absolute location hints, we use the Smartphones Wi-Fi and iBeacon sensor to measure the signal-strengths
of nearby transmitters. As the positions of both \docAP{}s and and \docIBeacon{}s are known beforehand, we compare
each measurement with its corresponding signal strength prediction which is defined by the 3D distance $d$
and the number of floors $\Delta f$ between the \docAPshort{} and the particle
\begin{equation}
P_r(d, \Delta f) = \mTXP - 10 \mPLE \log_{10}{\frac{\mMdlDist}{\mMdlDist_0}} + \Delta{f} \mWAF,
\end{equation}
and calculate the resulting probability as described in \cite{ipin2015}:
\begin{equation}
\mProb(\mObsVec \mid \mStateVec)_\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}
For the \docWIFI{} component we thus need two parameters per \docAPshort{}: $\mTXP$ measured at a distance
$\mMdlDist_0$ (usually \SI{1}{\meter}) and the path-loss exponent $\mPLE$ describing the environment.
To reduce complexity and system setup time, we use the same values for all \docAP{}s at the cost of accuracy.
While, $\mTXP$ is best determined using averaged measurements at a single location,
a good estimation of $\mPLE$ requires several measurements and numerical optimization \cite{etwas_aus_der_MA}.
$\mPLE$ is thus chosen empirically.
For the \docIBeacon{} component we also use \refeq{eq:wifiTotal} but $\mTXP$ is transmitted by each beacon.
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
heading deviation, we incorporate the turn-detection as control-data directly into the transition
$p(\mStateVec_{t} \mid \mStateVec_{t-1}, \mObsVec_{t-1})$.
\cite{thrun?}\cite{lukas2014?} to get a more directed sampling instead of a truly random one.
\commentByFrank{todo: wie wird die unsicherheit in der transition eingebracht, sigma, ..}

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@@ -1,7 +1,24 @@
\section{Indoor Localisation System}
\section{Recursive Density Estimation}
\subsection{Overview}
\subsection{Transition}
\subsection{Evaluation}
\commentByFrank{particle-filter wie bei lukas mit $\vec{o}_{t}$ in transition und $\vec{q}_{t-1}$ in eval??}
\commentByFrank{brauchen wir in der observation ueberhaupt noch $q_{t-1}$??}
\commentByFrank{das ist die basis fuer unser system}
\begin{equation}
p(\mStateVec_{t} \mid \langle \mObsVec \rangle_{t}) = \\
p(\mObsVec_{t} \mid \mStateVec_{t})
\int
p(\mStateVec_{t} \mid \mStateVec_{t-1}, \mObsVec_{t})
p(\mStateVec_{t-1} \mid \langle \mObsVec \rangle_{t-1}
d\mStateVec_{t-1}
\end{equation}
\begin{equation}
\mObsVec = (\mRssiVec_\text{wifi}, \mRssiVec_\text{ib}, \mObsHeading, \mObsPressure)
\end{equation}
\begin{equation}
\mStateVec = (x, y, z, \mObsHeading, \mStatePressure),\enskip
x,y,z,\mStatePressure \in \R
\end{equation}

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@@ -28,7 +28,12 @@
\newcommand{\mMovingAvgWithSize}[1]{\ensuremath{\text{avg}_{#1}}}
\newcommand{\mPressure}{\rho} % symbol for pressure readings
\newcommand{\mPressure}{\rho}
\newcommand{\mObsPressure}{\mPressure_\text{rel}} % symbol for observation pressure
\newcommand{\mStatePressure}{\hat{\mPressure}_\text{rel}} % symbol for state pressure
\newcommand{\mHeading}{\theta}
\newcommand{\mObsHeading}{\Delta\mHeading} % symbol used for the observation heading
\newcommand{\mStateHeading}{\mHeading} % symbol used for the state heading
%\newcommand{\docIBeacon}{iBeacon}