Optimal guidance for lunar soft landing with dynamic low-resolution image sequences

To relieve the burden of obtaining high-precision lunar surface information during lunar soft landing, a new guidance algorithm based on dynamic low-resolution image sequences is proposed. The integrated procedure of dynamic descent stage considering obstacle-avoiding requirement without the hover measurement is designed, which enables the spacecraft to optimize the final landing site by rolling in orbit. A small number of points are used to obtain the variance, slope and roughness of the field of vision subarea, and the shortest distance spiral search algorithm is used to determine the safest landing point. In order to reduce unnecessary control, an acceptance domain algorithm of alternative landing sites is designed to judge whether or not to accept the change of landing sites in dynamic low-precision image sequences. Assuming that the control acceleration is adjustable, the non-singular fast terminal sliding mode (NFTSM) controller based on terminal attractor is adopted and improved, and the stability of the closed-loop system is also proved. The validity, reliability and effectiveness of the proposed guidance algorithm are verified by numerical simulation on the case with disturbance and large sample data. The results demonstrate that the image information required for stable lunar soft landing is far less than that of the traditional methods, which can greatly reduce the burden of the onboard computer. (C) 2022 COSPAR. Published by Elsevier B.V. All rights reserved.

Automated summary

A new guidance algorithm based on dynamic low-resolution image sequences is proposed to reduce the burden of obtaining high-precision lunar surface information during lunar soft landing. The algorithm utilizes a integrated procedure of dynamic descent stage and an acceptance domain algorithm to optimize the final landing site and reduce the burden on the onboard computer. Numerical simulation results confirm the validity, reliability, and effectiveness of the proposed algorithm.