Pinpoint Lunar Landing Navigation using Crater Detection and Matching: Design and Laboratory Validation

Abstract

Space agencies have an increasing interest in highly accurate (200 m) autonomous landing on the Moon. This challenging requirement cannot be met using purely inertial navigation. The techniques currently investigated consist in detecting features in the images of the surface taken in real-time during the orbit and/or the descent phase of the mission in order to match them into a geo-referenced database. This information, fused with inertial and star-tracker measurements using an estimation filter, leads to accurate position estimation. This paper presents the derivation of an innovative navigation system based on crater detection and matching. It also presents the validation of the algorithm using software simulations and laboratory experiments conducted with an industrial robot equipped with flight-like hardware and moving over a lunar surface mock-up.