Research On Trajectory Optimization And Guidance Method Of Boost-glide Missile In Boost Phase

With the continuous improvement of modern warfare requirements for missile penetration capabilities,a boost-glide missile that combines the characteristics of ballistic missiles and aerodynamic missiles has gradually become a research hotspot.The booster gliding missile has the characteristics of low trajectory and high maneuverability due to its unique ballistic design.By depressing the trajectory,the atmospheric cover reduces the probability of the missile being detected by the enemy’s space-based infrared system.At the same time,the low trajectory uses the curvature of the earth as a cover to shorten the detection range of the enemy’s radar,and greatly shorten the enemy’s defense system reaction time increasing the missile’s penetration probability.Designing a reasonable boost stage trajectory and guiding the guided missile to reach the scheduled handover conditions can provide good glide conditions for boosting gliding missiles.This article aims at the boost stage trajectory optimization method and the boost stage online guidance algorithm of the boost gliding missile.Conducted in-depth research.The trajectory optimization of the boost phase is one of the key links in the overall design of the boost gliding missile.It can give the trajectory that optimizes the performance of the missile according to the given overall parameters,process constraints,terminal constraints,etc.,and provide a reference for the guidance system.The mathematical model of the booster section of the missile is a strongly nonlinear model,which is affected by multiple constraints at the same time,so the trajectory optimization problem of the booster section is actually a nonlinear optimal control problem with multiple constraints.In order to reduce the complexity of the problem,this paper uses particle swarm optimization to optimize the trajectory of the booster segment,and then uses the direct method to obtain the three-level optimal trajectory of the booster segment that meets the constraints.In this paper,the particle swarm trajectory optimization result is taken as the initial value into the direct shooting method of three-level trajectory optimization,which solves the problem that the direct shooting method requires relatively high initial value.Through segmentation optimization,the complexity of the problem is reduced and the performance of trajectory optimization is improved.The early boost stage guidance in various countries all adopted the open-loop guidance method.The open-loop guidance is easy to realize and has good stability,but the accuracy is low and it cannot correct the errors caused by external interference and system deviation,and cannot meet the requirements of boosting gliding missiles.Point high precision requirements.This paper adopts the optimal guidance method according to the guidance accuracy requirements of the booster gliding missile to ensure the current optimal guidance command in each guidance cycle.Although the optimal guidance method has high guidance accuracy,the calculation is complicated and the long solution time does not meet the real-time requirements of guidance.Therefore,this paper uses the neural network’s powerful learning ability for nonlinear mapping,and uses the optimal guidance trajectory as the learning template to train a neural network guide that can satisfy both the guidance accuracy and the guidance efficiency.Finally,the reliability of the neural network guide is verified by Monte Carlo shooting.The simulation results show that the calculation speed of the neural network guide is fast,and the guidance accuracy meets the accuracy requirements of the handover point.