An algorithm for multi-target tracking in low-signal-to-clutter-ratio underwater acoustic scenes
Year: 2024
Type: article
Abstract: To simplify the computational complexity of the Joint Probabilistic Data Association (JPDA) algorithm for multi-target tracking in low-signal-to-clutter-ratio underwater acoustic scenes, and to solve the problem of unstable tracking caused by poor measurement accuracy of active sonar, a trajectory information-based JPDA optimization algorithm (TJPDA) is designed to meet the real-time and stability requirements of practical engineering. The false alarm rate is reduced by accumulating correlated target trajectories in multiple frames, and the influence factor is introduced to modify the correlation probability and simplify the confirmation matrix splitting process. This effectively solves the problem of information combination explosion and trajectory divergence caused by adjacent target interference in low signal-to-clutter-ratio underwater acoustic scenes. The simulation results show that compared with the JPDA algorithm, the TJPDA algorithm not only improves target-tracking accuracy but also reduces computation time, making it more suitable for practical engineering applications.
Source: AIP Advances
DOI: 10.1063/5.0221725
Authors: Qiang Chen, Pingbo Wang, Hongkai Wei
Institution: Naval University of Engineering
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $1,350
OpenAlex ID: W4403431407