A Distributed Underwater Multi-Target Tracking Algorithm Based on Two-Layer Particle Filter

Underwater multi-target tracking is one of the key technologies for military missions, including patrol and combat in the crucial area. Since the underwater environment is complex and targets’ trajectories may intersect when they are in a dense area, it is challenging to guarantee the precision of o...

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Vydáno v:	Journal of marine science and engineering Ročník 11; číslo 4; s. 858
Hlavní autoři:	Kou, Kunhu, Li, Bochen, Ding, Lu, Song, Lei
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Basel MDPI AG 01.04.2023
Témata:	Accuracy Algorithms Analysis Communication complex noise Constraint modelling Geometric constraints Localization Military aspects Military operations Monitoring systems multi-target tracking Multiple target tracking particle filter Performance degradation Probability theory Resource allocation Underwater underwater monitoring network Workloads
ISSN:	2077-1312, 2077-1312
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Abstract	Underwater multi-target tracking is one of the key technologies for military missions, including patrol and combat in the crucial area. Since the underwater environment is complex and targets’ trajectories may intersect when they are in a dense area, it is challenging to guarantee the precision of observed information. In order to provide high-precision underwater localization and tracking services over an underwater monitoring network, a dynamic network resource allocation mechanism and an underwater multi-target tracking algorithm based on a two-layer particle filter with distributed probability fusion (TLPF-DPF) are proposed. The position estimation model based on geometric constraints and the dynamic allocation mechanism of network resources based on prior position estimation are designed. Using the improved filtering algorithm with known initial states, the reliable tracking of multiple targets with trajectory intersection in a small area under complex noises is achieved. In the non-Gaussian environment, the average positioning error of TLPF-DPF is less by nearly 30% than alternative algorithms. When switching from a Gaussian environment to a non-Gaussian environment, the performance degradation of TLPF-DPF is less than 12%, which exhibits stability compared with other algorithms when targets are close to each other with crossing trajectories.
AbstractList	Underwater multi-target tracking is one of the key technologies for military missions, including patrol and combat in the crucial area. Since the underwater environment is complex and targets’ trajectories may intersect when they are in a dense area, it is challenging to guarantee the precision of observed information. In order to provide high-precision underwater localization and tracking services over an underwater monitoring network, a dynamic network resource allocation mechanism and an underwater multi-target tracking algorithm based on a two-layer particle filter with distributed probability fusion (TLPF-DPF) are proposed. The position estimation model based on geometric constraints and the dynamic allocation mechanism of network resources based on prior position estimation are designed. Using the improved filtering algorithm with known initial states, the reliable tracking of multiple targets with trajectory intersection in a small area under complex noises is achieved. In the non-Gaussian environment, the average positioning error of TLPF-DPF is less by nearly 30% than alternative algorithms. When switching from a Gaussian environment to a non-Gaussian environment, the performance degradation of TLPF-DPF is less than 12%, which exhibits stability compared with other algorithms when targets are close to each other with crossing trajectories.
Audience	Academic
Author	Li, Bochen Ding, Lu Song, Lei Kou, Kunhu
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SubjectTerms	Accuracy Algorithms Analysis Communication complex noise Constraint modelling Geometric constraints Localization Military aspects Military operations Monitoring systems multi-target tracking Multiple target tracking particle filter Performance degradation Probability theory Resource allocation Underwater underwater monitoring network Workloads
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Title	A Distributed Underwater Multi-Target Tracking Algorithm Based on Two-Layer Particle Filter
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