Algorithm of Reentry Guidance for Hypersonic Vehicle Based on Lateral Maneuverability Prediction

基于侧向机动能力预测的高超声速飞行器再入制导算法研究

¹ School of Astronautics, Northwestern Polytechnical University, Xi'an 710072, China
² Xi'an Institute of Space Radio Technology, Xi'an 710100, China

Received: 5 July 2019

Abstract

Aiming at the problem that the traditional error corridor guidance method has poor adaptability in lateral guidance of predictor-corrector guidance, an algorithm of reentry guidance based on the vehicle lateral maneuverability prediction is proposed without increasing the calculation too much. The lateral component mean value of lift at reentry is calculated by using the bank angle magnitude function obtained from longitudinal guidance. According to the above-mentioned, a crossrange corridor with dynamic boundary constraint is designed to control bank angle reversal timing. Online parameters estimation is introduced to suppress the influence of the atmospheric density and aerodynamic parameters disturbance on the predictor model. The CAV-L, a kind of hypersonic vehicle, is used as an object to carry out reentry guidance simulation. The results show that the guidance algorithm can effectively guide vehicle to target for reentry missions of different range, the landing point error are small and the guidance effect is stable. The simulated results via Monte Carlo method verify that the guidance algorithm has a good adaptability and robustness to initial state deviations and process disturbances.

摘要

针对预测-校正制导中侧向制导使用传统误差走廊制导法自适应能力差的问题，在不过多增加计算量的前提下，提出一种基于飞行器侧向机动能力预测的再入制导算法。利用纵向制导所得倾侧角幅值函数计算飞行器再入时升力侧向分量均值，依此设计边界约束动态变化的横程走廊控制倾侧角反转时机。引入在线参数估计以抑制再入过程中大气密度和飞行器气动参数扰动对预测模型的影响。以CAV-L高超声速飞行器为对象，进行再入制导仿真。结果表明对不同航程的再入任务该制导算法均能有效引导飞行器飞向目标，落点误差小，制导效果稳定。Monte Carlo仿真验证了制导算法对再入初始状态偏差和过程扰动具有良好的自适应性和鲁棒性。