second draft finish - false images
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@@ -134,6 +134,7 @@ Given the above, we are now able to implement two different localisation schemes
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The graph-based transition keeps the localisation error low by using a very realistic propagation model, while being prone to sample impoverishment.
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On the other hand, the simple transition provides a high diversity with a robust, but uncertain position estimation.
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Both are evaluating a state $\mStateVec_{t}$ using \eqref{eq:evalBayes}.
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In the upcoming, the filter using the graph-based transition is refereed to as \textit{graph-based filter} and the filter using the simple transition as \textit{simple filter}.
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%
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%In the following, two very different transition models, each providing one of this abilities, are presented.
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