Algorithms for the incorporation of predictive information in surveillance theory

The paper discusses the problem of tracking a platform given probabilistic information concerning its possible destinations. Using a bayesian approach, we derive an algorithm which optimally incorporates the real-time measurements of the platform position with the predictive information about its destination. This algorithm can be efficiently implemented using some results from optimal smoothing. The results are illustrated by a simple example.

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