Distributed Multi-Sensor Control for Multi-Target Tracking

Aidan Blair, Amirali Khodadadian Gostar, Ruwan Tennakoon, A. Bab-Hadiashar, Xiaodong Li, Jennifer Palmer, R. Hoseinnezhad
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Abstract

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.
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多目标跟踪的分布式多传感器控制
针对分布式传感器网络中的多目标跟踪问题,提出了一种新的传感器控制算法。在多目标跟踪应用中,大多数传感器控制算法都是为集中式传感器网络设计的,在这种网络中存在一个计算效率低下的中央处理节点。本文首先给出了基于随机有限集滤波器和传感器融合的多传感器多目标跟踪框架的概念和数学概述。我们还将提供现有传感器控制方法的概述。然后,我们探索了基于坐标下降的传感器控制,并引入了一种利用坐标下降和信息论目标函数的全分布式算法。该方法在合成数据上进行了测试,并与其他方法进行了比较。结果表明,该方法优于等效的独立多传感器控制方法。
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