Distributed Multi-Sensor Control for Multi-Target Tracking
Aidan Blair, Amirali Khodadadian Gostar, Ruwan Tennakoon, Alireza Bab‐Hadiashar, Xiaodong Li, Jennifer L. Palmer, Reza Hoseinnezhad · 2022 11th International Conference on Control, Automation and Information Sciences (ICCAIS) · 2022
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.