Aiming at Unmanned Aerial Vehicle (UAV) target state estimation, a dynamic space model between the electro-optical platform and the target is established, and a target state estimation method by fusing game reasoning is proposed. The payoff matrix is defined according to the game concept. Then, the proposed density distribution function of particle swarm is established, and the particle filter method is improved by fusing the game reasoning. The state of the moving target can be accurately estimated by the retained effective particles. Through simulation experiments, the validity of state estimation results of moving target under different moving trajectories is analyzed and verified. The research in this paper can meet the requirements of the current UAV velocity measurement of maneuvering targets in terms of real-time and reliability.

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A UAV Target State Estimation Method by Fusing Game Reasoning to Eliminate Negative Particles

  • Wei Han,
  • Guang Yang,
  • Ling Luo,
  • Jingwei Dong,
  • Peng Xu,
  • Xuefei Sun

摘要

Aiming at Unmanned Aerial Vehicle (UAV) target state estimation, a dynamic space model between the electro-optical platform and the target is established, and a target state estimation method by fusing game reasoning is proposed. The payoff matrix is defined according to the game concept. Then, the proposed density distribution function of particle swarm is established, and the particle filter method is improved by fusing the game reasoning. The state of the moving target can be accurately estimated by the retained effective particles. Through simulation experiments, the validity of state estimation results of moving target under different moving trajectories is analyzed and verified. The research in this paper can meet the requirements of the current UAV velocity measurement of maneuvering targets in terms of real-time and reliability.