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It is difficult to track multiple maneuvering targets of which the number is unknown and time-varying, especially when there is range ambiguity. The random finite sets (RFS) based probability hypothesis density filter (PHDF) is an effective solution to the problem of multiple targets tracking. However, when tracking multiple targets via the range ambiguous radar, the problem of range ambiguity has...
Ronald Mahler's probability hypothesis density (PHD) provides a framework for the passive coherent location of targets observed via a T/R-R type passive radar measurements. We apply a particle filter implementation of the Bayesian PHD filter to target tracking using bearing and velocity measurements from a transmit/receive antenna and receiver pair (T/R-R). The tracking results are compared to those...
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