An Improved Tracking Method for Distributed Passive Sonar System
Pengfei Shao, Qing Li, Bin Zhou · 2022 7th International Conference on Signal and Image Processing (ICSIP) · 2022
Underwater target tracking by distributed passive sonar system can be regarded as a time-sequence target state parameter estimation problem with multiple observation equations. Currently, the commonly used Bayesian tracking methods mainly include Kalman filter tracking and particle filter tracking methods. However, When the target is maneuvering or located in the fuzzy region of array direction finding, the performance of traditional tracker will decrease sharply and even become invalid. Aiming at the target tracking problem of passive distributed sonar observation system under the above situation, a Bayesian tracking method with radial velocity constraint is described in this paper, and an improved tracking algorithm is proposed, which is verified by simulation and SWELLEx-96 experiment data.