• 中国科技核心期刊
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Volume 31 Issue 3
Jun  2023
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Article Contents
CHENG Chunyan, LI Yaan. Applications of EKF and UKF Algorithms in Bearings-only Target Tracking with a Double Observation Stations[J]. Journal of Unmanned Undersea Systems, 2023, 31(3): 388-397. doi: 10.11993/j.issn.2096-3920.202203014
Citation: CHENG Chunyan, LI Yaan. Applications of EKF and UKF Algorithms in Bearings-only Target Tracking with a Double Observation Stations[J]. Journal of Unmanned Undersea Systems, 2023, 31(3): 388-397. doi: 10.11993/j.issn.2096-3920.202203014

Applications of EKF and UKF Algorithms in Bearings-only Target Tracking with a Double Observation Stations

doi: 10.11993/j.issn.2096-3920.202203014
  • Received Date: 2022-03-28
  • Rev Recd Date: 2022-05-24
  • Available Online: 2022-07-25
  • For tracking underwater moving targets in real time, a bearings-only tracking system with a stationary double observation station was investigated. By combining the extended Kalman filter(EKF) algorithm and the unscented Kalman filter(UKF) algorithm, the bearings-only tracking system based on the EKF and UKF algorithms was simulated and compared. The results demonstrated that the double observation station system based on the two algorithms can be applied to real-time tracking of underwater moving targets, but the latter shows faster convergence and better robustness. The influence of the distance between the two stations and bearings measurement error on the real-time tracking effect was also analyzed. Simulation results showed that the effect of target tracking is reduced if the distance between the two observation stations is too small or too large. The double observation stations system based on EKF and UKF algorithms can achieve satisfactory tracking results when the distance between the two stations is 800 m; with the increase in the bearing measurement error, the tracking performance of the double observation stations system based on the two algorithms decreases, but the UKF algorithm still exhibits better tracking performance when the EKF algorithm fails to track.

     

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