Volume 50 Issue 3
Mar.  2024
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FU J B,ZHANG D,ZHAO J M,et al. On-line co-location method of distributed missile swarms for maneuvering targets[J]. Journal of Beijing University of Aeronautics and Astronautics,2024,50(3):1027-1036 (in Chinese) doi: 10.13700/j.bh.1001-5965.2022.0361
Citation: FU J B,ZHANG D,ZHAO J M,et al. On-line co-location method of distributed missile swarms for maneuvering targets[J]. Journal of Beijing University of Aeronautics and Astronautics,2024,50(3):1027-1036 (in Chinese) doi: 10.13700/j.bh.1001-5965.2022.0361

On-line co-location method of distributed missile swarms for maneuvering targets

doi: 10.13700/j.bh.1001-5965.2022.0361
Funds:  National Natural Science Foundation of China (61933010,61903301)
More Information
  • Corresponding author: E-mail:zhangdong@nwpu.edu.cn
  • Received Date: 16 May 2022
  • Accepted Date: 08 Jul 2022
  • Publish Date: 22 Jul 2022
  • High-precision co-location of maneuvering targets is the key to coordinated strikes, and co-location through distributed bomb swarms is a current research hotspot. This paper proposes a distributed online co-location strategy for swarms to solve the real-time problem of co-location under the condition of limited swarm communication. Aiming at the characteristics of model nonlinearity and non-Gaussian distribution of noise in target state estimation, a volumetric Kalman is proposed. Particle filter algorithm, a constant-speed turning model (constant turn, CT) with adaptive turning rate is designed, and the existing 2D CT model is extended to 3D, which solves the problem of inconsistency in positioning accuracy caused by the fixed turning rate of the existing CT model. An interactive multi-model method of adaptive model transition probability is designed, and the Markov transition probability is corrected in real time, which solves the problem of low positioning accuracy of single-model filtering. The effectiveness and accuracy of the method proposed in this paper are verified by simulation.

     

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