A Multiplatform Underwater Target Association and Tracking Method Based on Bearing and Frequency Measurements
Zhang Yiao, Tingting Teng, Hu Zhejian · 2024
In the field of underwater target information fusion, target association and tracking are tasks that are challenging to carry out. To address the problem of commonly used bearings-only target association and tracking algorithm, this study proposes a bearing-frequency target association and tracking algorithm. The proposed algorithm constructs an unbiased center frequency estimator and a hypothesis test criterion by introducing the nearest neighbor algorithm. Additionally, the algorithm fuses the bearing and frequency information, and a new target motion tracking model is established. On the one hand, the proposed algorithm adheres to the characteristic that different platforms observe the same target with the same center frequency, avoiding false targets. On the other hand, the unbiased center frequency estimator can estimate the center frequency, which addresses the problem of unknown center frequency in the traditional tracking algorithm. To verify the feasibility of the proposed algorithm, simulation and sea trials are carried out. The results reveal that the proposed algorithm has a good target association and tracking performance.