基于协同估计的三维多导弹博弈制导律

Three-dimensional Multi-missile Game Guidance Law based on Cooperative Estimation

针对三维空间中多导弹协同拦截机动目标的挑战,基于广义零控脱靶量概念,提出一种新的多导弹协同博弈性能目标函数和分布式抗饱和扩张状态观测器。首先,建立一个三维多导弹拦截机动目标的非线性模型,并提出了一种精确的零控脱靶量计算方法。基于此方法,构建了多导弹协同拦截的博弈性能目标函数,并设计了基于信息融合理论的分布式抗饱和扩张状态观测器对机动目标的机动加速度进行协同估计。最后采用了哈里斯鹰粒子群优化算法来计算制导指令,旨在以最优的燃料消耗实现最优的拦截效果。通过对4种不同交战场景的仿真实验,验证了该协同博弈制导律的优越性和有效性。

In response to the challenge of synergistically intercepting maneuvering targets in three-dimensional space with multiple missiles,a cooperative game performance objective function based on the notion of a generalized zero-control off-target distance is proposed.Initially,an accurate nonlinear model for the cooperative interception of maneuvering targets by multiple missiles in three-dimensional space is constructed,and an accurate method for calculating the zerocontrol off-target distance is developed.Based on this method,the construction of the game performance objective function for cooperative multi-missile interception is furthered.Additionally,a distributed anti-saturation expansion state observer(ESO)based on information fusion theory is designed to estimate the maneuver acceleration of a maneuvering target.The guidance commands are calculated using the Harris hawk particle swarm optimization algorithm,with the aim of achieving the optimal interception effect along with optimal fuel consumption.The superiority and effectiveness of the guidance law for three-dimensional cooperative games based on the Harris hawk particle swarm optimization algorithm are confirmed through simulation experiments on three distinct engagement scenarios.