Lunar Crater Matching With Triangle-Based Global Second-Order Similarity for Precision Navigation

Precision navigation and positioning are essential for lunar landing exploration missions. Terrain-relative navigation based on crater matching provides an effective means for lander position estimation as craters are distinguishing features on lunar. However, challenges arise from the lack of a one-to-one correspondence between image-detected craters and the crater database, as well as the inconsistency of the coordinate system of craters in the image and those in the database, which complicates the matching process. This article has proposed a lunar crater matching method with triangle-based global second-order similarity for precision navigation. First, craters are constructed as triangles as the basic matching primitives, and the topological relationships between craters are transformed into a graph structure. Then, geometric constraints and triangle removal rules are designed to retain high-quality triangles that satisfy the first-order similarity. Next, a second-order similarity metric is introduced to evaluate the consistency of the topology of crater distributions from a global perspective. The global optimal crater matching is determined by constructing a second-order similarity score matrix. The proposed method is validated by comprehensive experiments using both simulation data and Chang’E-6 landing phase data. The experimental results show that the proposed method has achieved the highest accuracy and robustness among the comparison methods, and the average position estimation accuracies are 0.44% and 0.41% of flight altitude for orbiting and landing scenarios.

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Publication Details

Journal
IEEE Transactions on Geoscience and Remote Sensing
Published
2025-01-01
DOI
https://doi.org/10.1109/tgrs.2025.3598104
Primary Topic
Planetary Science and Exploration
Type
article
Field-Weighted Citation Impact
0.00

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article

Lunar Crater Matching With Triangle-Based Global Second-Order Similarity for Precision Navigation

Huan Xie, Guanghan Chu, Zhaojun Deng, Qian Huang et al.
IEEE Transactions on Geoscience and Remote Sensing
Planetary Science and Exploration
article

Lunar Crater Matching With Triangle-Based Global Second-Order Similarity for Precision Navigation

Huan Xie, Guanghan Chu, Zhaojun Deng, Qian Huang, Xiaohua Tong, Changjiang Xiao, Shijie Liu, Tao Li, Xu Chen, Baocheng Hua
article en

Abstract

Precision navigation and positioning are essential for lunar landing exploration missions. Terrain-relative navigation based on crater matching provides an effective means for lander position estimation as craters are distinguishing features on lunar. However, challenges arise from the lack of a one-to-one correspondence between image-detected craters and the crater database, as well as the inconsistency of the coordinate system of craters in the image and those in the database, which complicates the matching process. This article has proposed a lunar crater matching method with triangle-based global second-order similarity for precision navigation. First, craters are constructed as triangles as the basic matching primitives, and the topological relationships between craters are transformed into a graph structure. Then, geometric constraints and triangle removal rules are designed to retain high-quality triangles that satisfy the first-order similarity. Next, a second-order similarity metric is introduced to evaluate the consistency of the topology of crater distributions from a global perspective. The global optimal crater matching is determined by constructing a second-order similarity score matrix. The proposed method is validated by comprehensive experiments using both simulation data and Chang’E-6 landing phase data. The experimental results show that the proposed method has achieved the highest accuracy and robustness among the comparison methods, and the average position estimation accuracies are 0.44% and 0.41% of flight altitude for orbiting and landing scenarios.

IEEE Transactions on Geoscience and Remote SensingVol. 63
Tongji University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 85%
Planetary Science and Exploration
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