ASMT: An augmented state-based multi-target tracking algorithm in wireless sensor networks

Kejiang Xiao, Rui Wang, Lei Zhang, Jian Li and Tun Fun

International Journal of Distributed Sensor Networks, 2017, vol. 13, issue 4, 1550147717703115

Abstract: Due to the resource limitation and low performance of sensor node, research works of multi-target tracking became a hot spot in the applications of wireless sensor networks. Here, we propose an algorithm named augmented state-based multi-target tracking algorithm. To augment the state of the target tracking, augmented state-based multi-target tracking algorithm can effectively reduce the computational complexity of data association. Then, multi-target tracking in wireless sensor networks can be implemented by augmented state-based multi-target tracking algorithm as a simplified Bayesian estimation method is adopted. The simulation of multi-target tracking in wireless sensor networks demonstrates that augmented state-based multi-target tracking algorithm has less computation and higher accuracy than traditional method, especially in the implementation of maneuvering targets with intersection.

Keywords: Wireless sensor networks; multi-target tracking; data association; Bayesian estimation (search for similar items in EconPapers)
Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:sae:intdis:v:13:y:2017:i:4:p:1550147717703115

DOI: 10.1177/1550147717703115

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