基于意图推断的高超声速滑翔目标贝叶斯轨迹预测

为解决高超声速滑翔目标机动给探测防御造成的困难，研究基于意图推断的贝叶斯轨迹预测方法。首先对目标进行动力学建模，利用气动参数设计机动模式集。假定高超声速滑翔目标必定攻击某目标，结合飞行意图合理构造意图代价函数，借鉴贝叶斯理论迭代推导机动模式和运动状态递推公式。通过蒙特卡洛采样实现轨迹预测算法。仿真结果表明，算法能有效提高目标机动不确定条件下轨迹预测的精度，当多目标可能被打击时，通过对预测轨迹进行在线重新规划，降低目标误判给轨迹预测造成的不利影响。

Bayesian Trajectory Prediction for a Hypersonic Gliding Reentry Vehicle Based on Intent Inference

 In order to solve the problems of an interception caused by a maneuver of a hypersonic gliding reentry vehicle, a Bayesian trajectory prediction method based on the intent inference is studied. First, the dynamic model of the target is modeled and maneuvering mode set is designed by the aerodynamic parameters. Then it assumes that the hypersonic glide reentry vehicle will attack a certain target and a intention cost function is constructed according to the flight intention. The Bayesian theory is used to deduce the recursion formula of the maneuvering mode and motion state. Finally the trajectory prediction algorithm is realized through the Monte Carlo sampling. Simulation results show that the proposed algorithm can effectively improve the accuracy of the trajectory prediction under the uncertain maneuvering in the future. When multiple targets are likely to be hit, the negative impact of misjudgment to the target on trajectory prediction can be reduced by reprogramming the predicted trajectory online.