Constrained Sensor Control for Labeled Multi-Bernoulli Filter Using Cauchy-Schwarz Divergence

被引:52
作者
Gostar, Amirali K. [1 ]
Hoseinnezhad, Reza [1 ]
Rathnayake, Tharindu [1 ]
Wang, Xiaoying [2 ]
Bab-Hadiashar, Alireza [1 ]
机构
[1] RMIT Univ, Sch Engn, Melbourne, Vic 3000, Australia
[2] Changshu Inst Technol, Suzhou 215500, Peoples R China
基金
澳大利亚研究理事会;
关键词
Information divergence; labeled multi-Bernoulli; poisson point process; random finite sets; RANDOM FINITE SETS; MULTITARGET TRACKING; SELECTION; PHD;
D O I
10.1109/LSP.2017.2723924
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
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.
引用
收藏
页码:1313 / 1317
页数:5
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