Distributed Multi-Sensor Control for Multi-Target Tracking

被引:1
作者
Blair, Aidan [1 ]
Gostar, Amirali Khodadadian [1 ]
Tennakoon, Ruwan [1 ]
Bab-Hadiashar, Alireza [1 ]
Li, Xiaodong [1 ]
Palmer, Jennifer [1 ]
Hoseinnezhad, Reza [1 ]
机构
[1] RMIT Univ, Melbourne, Vic, Australia
来源
2022 11TH INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION AND INFORMATION SCIENCES (ICCAIS) | 2022年
基金
澳大利亚研究理事会;
关键词
distributed sensor network; sensor control; co-ordinate descent; random finite sets; multi-target tracking; MULTI-BERNOULLI FILTER; SENSOR MANAGEMENT;
D O I
10.1109/ICCAIS56082.2022.9990364
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper proposes a new sensor control algorithm for multi-target tracking applications within distributed sensor networks. In multi-target tracking applications, most sensor control algorithms are designed for centralized sensor networks, where there is a central processing node that is computationally inefficient. This paper first provides a conceptual and mathematical overview of the multi-sensor multi-target tracking framework, using random finite set (RFS) filters and sensor fusion. We will also provide an overview of the existing sensor control methods. We then explore coordinate descent-based sensor control and introduce a fully distributed algorithm utilizing coordinate descent and an information-theoretic objective function. This method is tested on synthetic data and compared to alternative methods. The results show that the proposed method outperforms equivalent independent multi-sensor control methods.
引用
收藏
页码:231 / 239
页数:9
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