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LI J G,CHEN X,DONG Y F,et al. RTPN interception guidance law for maneuvering target based on collaborative filtering trajectory prediction[J]. Journal of Beijing University of Aeronautics and Astronautics,2024,50(1):86-96 (in Chinese) doi: 10.13700/j.bh.1001-5965.2022.0211
Citation: LI J G,CHEN X,DONG Y F,et al. RTPN interception guidance law for maneuvering target based on collaborative filtering trajectory prediction[J]. Journal of Beijing University of Aeronautics and Astronautics,2024,50(1):86-96 (in Chinese) doi: 10.13700/j.bh.1001-5965.2022.0211

RTPN interception guidance law for maneuvering target based on collaborative filtering trajectory prediction

doi: 10.13700/j.bh.1001-5965.2022.0211
Funds:  Shaanxi Natural Science Youth Fund Project (2021JQ-858); Shaanxi Natural Science Fund Key Project (2022JZ-37); Shaanxi Higher Education Teaching Reform Research Project (21BY163); Youth Science Fund (62103441); University-level Research Project (2021KY0210)
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  • Corresponding author: E-mail:912646963@qq.com
  • Received Date: 02 Apr 2022
  • Accepted Date: 09 Sep 2022
  • Available Online: 31 Oct 2022
  • Publish Date: 17 Oct 2022
  • According to the actual requirements of the current air threat target interception, combined with the interceptor’s own maneuverability and based on the full coverage cooperative strategy, a realistic true proportional navigation law (RTPN) guided interception method for collaborative detection is designed. It solves the problem that the traditional RTPN method does not consider the interceptor saturation overload limit and the determination of the acquisition area of any maneuvering target. A distributed cooperative filtering technique is suggested to address the accuracy and robustness of data fusion caused by measurement inaccuracy of target trajectory and packet loss of cooperative detection data during interception. Aiming at the problems of data transmission and the delay of interceptor dynamic response, a track prediction algorithm is proposed. The results of the simulations demonstrate that the suggested approach may successfully address issues with acquisition region identification, dynamic latency under saturation overload, and resilience and accuracy issues brought on by data packet loss in cooperative detection data fusion.

     

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