期刊
IEEE SIGNAL PROCESSING LETTERS
卷 24, 期 9, 页码 1313-1317出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/LSP.2017.2723924
关键词
Information divergence; labeled multi-Bernoulli; poisson point process; random finite sets
资金
- Linkage Projec - Australian Research Council [LP160101081]
- Australian Research Council [LP160101081] Funding Source: Australian Research Council
A constrained sensor control method is presented for multiobject tracking using labeled multi-Bernoulli filters. The proposed framework is based on a novel approximation of theCauchySchwarz divergence between the labeled multi-Bernoulli prior and posterior densities, which does not need Monte Carlo sampling of random sets in the multiobject space. The void probability functional is also formulated for labeled multi-Bernoulli distributions and used within our proposed method to form a constrained sensor control solution. Numerical studies demonstrate that reasonably acceptablemovements are decided for the controlled sensor by our sensor control method, with the advantage that the void probability constraint is formally considered as part of the sensor control optimization algorithm.
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