Multisensor Tasking Using Analytical Rényi Divergence in Labeled Multi-Bernoulli Filtering

What is it about?

A novel multi-sensor tasking method using analytical divergence of LMB is presented for catalog maintenance of GEO objects. The proposed method is formulated in the RFS framework in conjunction with the information theoretic sensor tasking which assigns sensor tasks by maximizing the derived analytical Renyi divergence, and complementary data fusion to combine posteriors from sensor nodes. The proposed method is evaluated using a simulated scenario of large-scale GEO object tracking.

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