New crater-pattern matching using a projective invariant for lost-in-space scenario

Abstract

This paper addresses the challenge of crater matching in lost-in-space scenarios. An innovative algorithm is designed for robust and efficient crater matching by utilizing projective invariant values. Unlike other existing approaches, the proposed algorithm generates grid-shape patterns as a distinctive feature, thereby significantly enhancing recognition accuracy. Notably, the algorithm employs a stepwise matching process involving filtering, matching, and verification to ensure fast and reliable matching. Extensive numerical simulations have been conducted to assess the algorithm’s performance across various scenarios, including variations in crater center positions, shape distortions, and the presence of false craters. The outcomes demonstrate that the proposed algorithm significantly surpasses previous crater matching techniques, delivering superior stability and consistent accuracy even under challenging lost-in-space conditions.