基于贝叶斯推断的高超声速滑翔目标轨迹预测方法

A method of predicting for trajectory of hypersonic gliding targets based on Bayesian inference

针对高超声速滑翔飞行器因其强机动性、高灵活性,轨迹难以预测的问题,提出一种基于贝叶斯推断的高超声速滑翔飞行器轨迹预测方法.首先,根据高超声速滑翔飞行器攻击某目标的意图信息和战场态势信息,设计意图代价函数量化其攻击意图;然后,采用贝叶斯推断迭代递推目标的机动模式和运动状态;最后,利用蒙特卡洛序贯滤波方法计算目标状态分布进而预测其轨迹.仿真实验结果表明:所提出方法能够有效预测高超声速滑翔飞行器的轨迹,当有多个目标时能够给出各目标被攻击的概率,为防御方提供决策参考.

In order to solve the current issue that it’s difficult to predict the trajectories of a hypersonic gliding reentry vehicle(HGRV)due to its strong maneuverability and flexibility,a trajectory prediction method of the HGRV based on Bayesian inference is proposed.The method is based on the information that the HGRV is going to attack a place and the battlefield situation,designing the intention cost function to quantify its intention.Adopting the Bayesian inference to iteratively deduce the maneuvering mode and motion state of the HGRV,and finally using the Monte Carlo sequential filtering method to compute the target’s state distribution and predicting its trajectory.Simulation results show that the proposed method can effectively predict the trajectory of the HGRV and provide the probability of each target being attacked when there are multiple targets,which can give a reference to the defense to make decisions.