近地小行星探测任务月球借力逃逸转移混合优化方法

Hybrid optimization method for lunar gravity assist transfer trajectory to near-Earth asteroids

利用月球借力能够提升送入深空的有效载荷的质量。设计月球借力深空逃逸轨道主要有两种方法:正向法将借力轨道参数化后,利用全局优化算法进行优化,该方法思路直观,但优化参数多,导致计算耗时长,收敛稳定性差;反向法先确定日心段最优轨道,再拼接月球借力地心段轨道,该方法计算耗时少,但模型精度差,并且不容易收敛到全局最优解。为了快速求解月球借力深空逃逸轨道,本文在已有方法基础上提出混合优化方法。提出的混合优化方法充分利用反向法收敛速度快和正向法精度高的优点,先以反向法的多目标优化Pareto解集为参考轨道,再在参考轨道附近开展局部优化,利用正向法使用全局搜索算法,快速获得最优转移轨道。以探测近地小行星1989 ML和2003 SM84为例进行了数值仿真,仿真结果显示混合优化法解的收敛稳定性和计算效率相比正向法提升显著,改进后解的收敛稳定性提升至原来的3~4倍,计算时间缩短50%。仿真结果表明混合优化法对解的收敛稳定性和收敛效率提升效果显著。

The payload launched to deep space can be increased by using lunar gravity assist(LGA).There are two main methods for designing LGA transfer trajectory.The forward patched method firstly parameterizes the constrained orbit and then optimizes the orbit with the global optimization algorithm.The forward method is intuitive,but has many optimization parameters,which causes time-consuming calculation and poor convergence stability.The backward patched method firstly determines the optimal orbit of the heliocentric segment and then calculates the geocentric LGA.The backward patched method consumes less calculation time,but with poor accuracy,and it is not easy to converge to the global optimal solution.To solve the LGA escape trajectory in a short time,this paper proposes a hybrid optimization method based on the existing methods.The proposed hybrid optimization method makes full use of the advantages of fast convergence speed of backward patched method and high precision of forward patched method.The method takes the trajectory corresponding to the Pareto solution set of the multi-objective optimization of the backward patched method as the reference trajectory,and carries out local optimization near the reference trajectory.Then,the forward method is applied to quickly obtain the optimal transfer trajectory by using the global search algorithm.Numerical simulation was carried out for the detection of near-Earth asteroids 1989 ML and 2003 SM84.The results show that compared with the forward patched method,the hybrid optimization method improved the convergence stability and computational efficiency effectively.The convergence stability of the solution was improved to 3-4 times,and the calculation time was reduced by 50%.The results indicate that the hybrid optimization method excels in convergence stability and computational efficiency.