Enhanced Integrity of Lidar Localization: A Study on Feature Extraction Techniques

Kana Nagai and Boris Pervan

Abstract:	This study develops a methodology to minimize extraction faults in landmark-based Lidar localization using a map. The analysis begins by addressing the integrity risks associated with Lidar navigation systems in self-driving cars and identifying the causes of incorrect extractions. Example Lidar-fault integrity requirements are introduced to establish a basis for data point selection using the Neyman-Pearson criterion. Weighted least squares estimation, combined with a chi-square residual test, is then applied for landmark extraction. Experimental results confirm that the methodology reduces landmark extraction errors to centimeter-level.
Published in:	Proceedings of the 37th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2024) September 16 - 20, 2024 Hilton Baltimore Inner Harbor Baltimore, Maryland
Pages:	1491 - 1505
Cite this article:	Nagai, Kana, Pervan, Boris, "Enhanced Integrity of Lidar Localization: A Study on Feature Extraction Techniques," Proceedings of the 37th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2024), Baltimore, Maryland, September 2024, pp. 1491-1505. https://doi.org/10.33012/2024.19735
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