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Volume 32 Issue 2
Apr  2024
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ZHANG Hongrui, SU Jun, LI Qian, LI Bin, KOU Xiaoming. Calculation Method for UKF Target Motion Elements Based on Detection Information of Active and Passive Sonars[J]. Journal of Unmanned Undersea Systems, 2024, 32(2): 354-361. doi: 10.11993/j.issn.2096-3920.2023-0045
Citation: ZHANG Hongrui, SU Jun, LI Qian, LI Bin, KOU Xiaoming. Calculation Method for UKF Target Motion Elements Based on Detection Information of Active and Passive Sonars[J]. Journal of Unmanned Undersea Systems, 2024, 32(2): 354-361. doi: 10.11993/j.issn.2096-3920.2023-0045

Calculation Method for UKF Target Motion Elements Based on Detection Information of Active and Passive Sonars

doi: 10.11993/j.issn.2096-3920.2023-0045
  • Received Date: 2023-04-26
  • Accepted Date: 2023-06-12
  • Rev Recd Date: 2023-05-28
  • The target motion element is important information in anti-submarine warfare, and its calculation results have a great influence on the hitting probability of the target, thus affecting combat decision-making. At present, active sonar is the main source of information in the calculation method for target motion elements in anti-submarine warfare of surface ships. However, active sonar uses a fixed number of sending periods, and there are gaps in the target information during the continuous tracking process. As a result, there are large errors and slow convergence in the calculation results of the target motion elements. In order to obtain the target motion elements more quickly and accurately, the detection information of passive sonar was added to the filtering process. The unscented Kalman filter(UKF) method was used to simulate the information detection methods using only active sonar and both active and passive sonars, and the results were compared. The simulation results show that under the same conditions, the proposed method can significantly improve the convergence accuracy and speed compared with the traditional method. It can improve the calculation accuracy of speed, azimuth, and heading angle by 33.55%, 38.99%, and 35.29% on average, verifying its effectiveness.

     

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