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现存大多数固定翼无人机(UAV)跟踪地面目标的方法需要一个或多个严格的假设,限制了实际应用,针对此问题,提出一种基于四阶动力学建模和随机最优控制的UAV跟踪方法。使用四阶动力学方程对UAV随机动态和目标进行初始化建模;通过一个适当的状态转换概率函数帮助UAV为每一个滚转动作画出蒙特卡罗样本;通过随机优化控制问题的解决确定最优控制反馈策略。仿真实验结果验证了该方法在实际应用中的有效性,与其他优秀方法相比,提出的方法的UAV仰角没有超出瞬时视场角(-152°~32°)的范围,目标没有逃离UAV的视线之外,而其他方法会使目标逃离UAV视线一次或两次。另外,能容忍的最高平稳风速最高达6 m/s,高于其他方法。
The existing methods of tracking the ground targets of most UAVs require one or more rigorous assumptions, which limit the practical application. To solve this problem, a method based on fourth-order dynamic modeling and stochastic optimal control UAV tracking method. The fourth-order kinetic equation is used to initialize the UAV stochastic dynamics and the target. A suitable state transition probability function is used to help the UAV to draw Monte Carlo samples for each tumbling motion. The stochastic optimization control problem is solved to determine the optimum Control feedback strategy. The simulation results verify the effectiveness of this method in practical application. Compared with other excellent methods, the UAV elevation angle of the proposed method does not exceed the range of instantaneous viewing angle (-152 ° ~ 32 °) and the target does not escape from the UAV Out of sight, and other methods can cause the target to escape the UAV’s sight once or twice. In addition, the maximum steady wind speed that can be tolerated is up to 6 m / s, higher than other methods.