The accuracy of tracking can be enhanced by the incorporation of
prior information in the form of a local road map. For instance,
the performance of ground target tracking algorithms can be
improved by incorporating hard constraints (describing roads and
junctions) into the tracking model. We describe an approach to
enhancing tracking algorithms that uses 'probability fields' to
represent the local road map information. The resulting
'Bayes-filter' equations are solved using particle filters and
compared with a basic particle filter with no additional map
information.
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