refactored sample impoverishment a littel
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@@ -102,10 +102,13 @@ For this, the state transition model is extended.
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Compared to the resampling step, as used by the first method, the transition $p(\mStateVec_{t} \mid \mStateVec_{t-1}, \mObsVec_{t-1})$ enables us to use prior measurements, which is obviously necessary for all \docWIFI{} related calculations.
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As described in chapter \ref{sec:transition}, our transition method only allows to sample particles at positions, that are actual feasible for a humans within a building e.g. no walking trough walls.
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If a particle targets a position which is not walk-able e.g. behind a wall, we draw a new position within a very small, but reachable area around its current position.
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%To prevent sample impoverishment we extend our transition method.
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Instead of such a small are or even the complete building, as suggested in method one, we now define a sphere.
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\todo{radius ist falsch! all connected triangles... warte aber noch aufs franks transition teil.}
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The radius is given by $D_\text{KL} \cdot q(\mObsVec_t^{\mRssiVec_\text{wifi}})$ and particles are drawn uniformly on the mesh enclosed by the sphere.
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%
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%Instead of such a small area or even the complete building, as suggested in method one, we now define a sphere.
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To prevent sample impoverishment we extend this transition method by making the reachable area depended upon $D_\text{KL}$ and the \docWIFI{} quality factor.
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Particles are thus drawn uniformly on a sub-region of the mesh, given by a radius $ r_\text{sub} = D_\text{KL} \cdot q(\mObsVec_t^{\mRssiVec_\text{wifi}})$.
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The sub-region consists of all walk-able and connected triangles within $r_\text{sub}$, including stairs and elevators.
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%\todo{radius ist falsch! all connected triangles... warte aber noch aufs franks transition teil.}
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%The radius is given by $D_\text{KL} \cdot q(\mObsVec_t^{\mRssiVec_\text{wifi}})$ and particles are drawn uniformly on the mesh enclosed by the sphere.
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This allows to increase the diversity of particles by the means of \docWIFI{}, allowing to ignore any restrictions made by the system, as long as the difference between $\probGrid_{t, \text{wifi}}$ and the posterior is high.
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The subsequent evaluation step of the particle filter then reweights the particles, so that only those in proper regions will survive the resampling.
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