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2017-05-02 13:34:13 +02:00

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\section{Indoor Positioning System}
\label{sec:system}
Our smartphone-based indoor localization system estimates a pedestrian's current location and heading
using recursive density estimation seen in \refeq{eq:recursiveDensity}.
\begin{equation}
%\arraycolsep=1.2pt
%\begin{array}{ll}
p(\mStateVec_{t} \mid \mObsVec_{1:t}) \propto\\
\underbrace{p(\mObsVec_{t} \mid \mStateVec_{t})}_{\text{evaluation}}
\int \underbrace{p(\mStateVec_{t} \mid \mStateVec_{t-1}, \mObsVec_{t-1})}_{\text{transition}}
\underbrace{p(\mStateVec_{t-1} \mid \mObsVec_{1:t-1})d\vec{q}_{t-1}}_{\text{recursion}} \enspace,
%\end{array}
\label{eq:recursiveDensity}
\end{equation}
A movement model, based on random walks on a graph, samples only those transitions,
that are allowed by the buildings floorplan.
%$p(\mStateVec_{t} \mid \mStateVec_{t-1}, \mObsVec_{t-1})$
The smartphone's accelerometer, gyroscope, magnetometer, GPS- and \docWIFI{}-module provide
the observations for both, the transition and the following evaluation step to infer the hidden state,
namely the pedestrian's location and heading
\cite{Ebner2016OPN, Fetzer2016OMC}.
This hidden state $\mStateVec$ is given by
\begin{equation}
\mStateVec = (x, y, z, \mStateHeading),\enskip
x, y, z, \mStateHeading \in \R \enspace,
\end{equation}
%
where $x, y, z$ represent the pedestrian's position in 3D space
and $\mStateHeading$ his current (absolute) heading.
The corresponding observation vector is defined as
%
\begin{equation}
\mObsVec = (\mRssiVecWiFi{}, \mObsSteps, \mObsHeadingRel, \mObsHeadingAbs, \mPressure, \mObsGPS) \enspace.
\end{equation}
%
$\mRssiVecWiFi$ contains the signal strength measurements of all \docAP{}s (\docAPshort{}s) currently visible to the smartphone,
$\mObsSteps$ describes the number of steps detected since the last filter-step,
$\mObsHeadingRel$ the (relative) angular change since the last filter-step,
$\mObsHeadingAbs$ the current, vague absolute heading,
$\mPressure$ the ambient pressure in hPa and
$\mObsGPS = ( \mObsGPSlat, \mObsGPSlon, \mObsGPSaccuracy)$ the current location (if available) given by the GPS.
Assuming statistical independence, the state-evaluation density can be written as
%
\begin{equation}
p(\vec{o}_t \mid \vec{q}_t) =
p(\vec{o}_t \mid \vec{q}_t)_\text{wifi}\enskip
p(\vec{o}_t \mid \vec{q}_t)_\text{gps}\enskip
p(\vec{o}_t \mid \vec{q}_t)_\text{abshead}\enskip
p(\vec{o}_t \mid \vec{q}_t)_\text{activity}\enskip
\enspace.
\label{eq:evalDensity}
\end{equation}
%
Absolute location information is provided by $p(\vec{o}_t \mid \vec{q}_t)_\text{wifi}$ and
$p(\vec{o}_t \mid \vec{q}_t)_\text{gps}$, if available.
The vague absolute heading provided by
the smartphone's magnetometer is included using a simple heuristic for
$p(\vec{o}_t \mid \vec{q}_t)_\text{abshead}$. Finally, the barometer is used
to distinguish between normal walking and climbing stairs within
$p(\vec{o}_t \mid \vec{q}_t)_\text{activity}$.
%
The remaining observations, derived from aforementioned smartphone sensors,
namely: detected steps, and relative heading are
used within the transition model, where potential movements
$p(\mStateVec_{t} \mid \mStateVec_{t-1}, \mObsVec_{t-1})$
are not only constrained by the buildings floorplan but also by
those additional observations.
As this work focuses on \docWIFI{} optimization, not all parts of
the localization system are discussed in detail.
For missing explanations please refer to \cite{Ebner2016OPN}.
%
Compared to this reference, absolute heading and GPS have been added as additional sensors
to further enhance the localization. Their values are incorporated by simply
comparing the sensor readings against a distribution that models the sensor's uncertainty.
%\todo{neues resampling? je nach dem was sich noch in der eval zeigt}
As GPS will only work outdoors, e.g. when moving from one building into another,
the system's absolute position indoors is solely provided by \docWIFI{}.
Therefore its crucial for this component to supply location estimations
that are as accurate as possible, while ensuring fast setup and
maintenance times.
\todo{ueberleitung holprig?}