Risley-prism-based multi-beam scanning LiDAR for high-resolution three-dimensional imaging

• Published in: Optics and lasers in engineering Vol. 150; p. 106836
• Main Authors: Li, Anhu, Liu, Xingsheng, Sun, Jianfeng, Lu, Zhiyong
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.03.2022
• Subjects: Light detection and ranging; Multi-beam scanning; Point cloud processing; Risley prisms; Three-dimensional information acquisition; Light detection and ranging; Point cloud processing; Multi-beam scanning; Three-dimensional information acquisition; Risley prisms
• ISSN: 0143-8166; 1873-0302
• DOI: 10.1016/j.optlaseng.2021.106836

•Coherent light detection and ranging architecture for three-dimensional imaging.•Risley-prism-based multi-beam scanning enables high-resolution spatial sampling.•Multi-mode integrated point cloud filtering method for efficient outlier removal.•Coarse-fine coupled alignment strategy for multi-channel point cloud registration. Light detection and ranging (LiDAR) as a significant approach to three-dimensional perception has increasingly suffered from challenges for compact structure, high resolution and strong adaptability. This paper presents a versatile LiDAR system that incorporates multi-beam scanning using Risley prisms and coherent detection based on triangular frequency modulation. By combining Risley-prism-based multi-beam steering model with simultaneous distance and velocity measurements, the LiDAR architecture for three-dimensional imaging is theoretically demonstrated. A unified LiDAR point cloud processing framework is developed, where the multi-mode integrated filtering method is proposed for outlier removal using point cloud characteristics. The coarse-fine coupled strategy is also formulated to combine statistical modeling with iterative optimization for multi-channel point cloud registration. It is experimentally validated that our LiDAR can achieve high-resolution three-dimensional information acquisition against long range, and the proposed point cloud processing technique can fully reconstruct the spatial form of object while preserving sufficient details.