Recent advances inmultisensormultitarget tracking using random finite set
Kai DA , Tiancheng LI , Yongfeng ZHU , Hongqi FAN , Qiang FU
Front. Inform. Technol. Electron. Eng ›› 2021, Vol. 22 ›› Issue (1) : 5 -24.
In this study, we provide an overview of recent advances in multisensor multitarget tracking based on the random finite set (RFS) approach. The fusion that plays a fundamental role in multisensor filtering is classified into data-level multitarget measurement fusion and estimate-level multitarget density fusion, which share and fuse local measurements and posterior densities between sensors, respectively. Important properties of each fusion rule including the optimality and sub-optimality are presented. In particular, two robust multitarget density-averaging approaches, arithmetic- and geometric-average fusion, are addressed in detail for various RFSs. Relevant research topics and remaining challenges are highlighted.
Multitarget tracking / Multisensor fusion / Average fusion / Random finite set / Optimal fusion
Zhejiang University Press
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