Optical Navigation Method and Error Analysis for the Descending Landing Phase in Planetary Exploration

Abstract

To solve the problem of high-precision optical navigation for the descent landing of lunar and planetary probes, an optical navigation method based on the spatial position distribution model is proposed. The method is based on crater detection, and an imaging cosine equivalent mathematical model based on the correspondence of crater objects is constructed, The geometric distribution of the probe spatial position is described to form an Abelian Lie group spatial torus to achieve absolute positioning for parametric optical navigation, Finally, the effect of the measurement error of crater detection on the positioning and attitude of the optical navigation system is discussed, with a fitted ellipse used as a typical analysis object. The effects of different crater distribution configurations and different detection errors on the performance of the proposed optical navigation algorithm are analyzed. The results of Monte Carlo simulation experiments showed that the algorithm proposed in this paper had the advantages of high stability, high accuracy, and good real-time performance, compared with existing methods.

Adaptive Convex Optimization Guidance for Lunar Landing

“…In addition, various lunar surface sensors, such as cameras and lidars, typically do not work when the lander is further away from the moon, which means that the lander has no attitude constraints at this time. However, as the powered descent phase comes to an end and the lander gets close enough to the moon, it is usually desired that the lander has a specific attitude so that it can obtain images and measurements from various sensors for obstacle avoidance and navigation [9,[35][36][37][38] and a specific thrust magnitude for a smooth transition to the subsequent phase [10,39].…”

Optimal Landing Zone Selection and Online Trajectory Programming Method for Lunar Lander

“…In addition, many recognition algorithms are developed based on the lunar surface craters, an obstacle with typical morphological characteristics. For example, Peng Wu and other scholars proposed a fast extraction algorithm for craters based on the bright and dark edges generated by craters, and simulation results show that the algorithm can adapt to different lighting conditions and improve the computational efficiency as well as the crater detection ratio compared to the classical algorithm [4][5].…”