控制与信息技术Issue(1)：82-88,7.DOI:10.13889/j.issn.2096-5427.2026.01.011
基于小视场固态激光雷达的融合定位研究
Research on Fusion Localization Based on Solid-State LiDAR with Narrow Field of View
摘要
Abstract
Solid-state LiDAR with narrow fields of view(FOV)faces challenges in GNSS-denied environments due to irregular scanning patterns and limited FOV,including poor feature extraction and low matching robustness.To address these limitations,this paper proposes a real-time robust localization algorithm that fuses LiDAR and an inertial measurement unit(IMU).The algorithm optimizes point cloud processing through scan-line reconstruction and adaptive spatial geometric feature extraction,employs an unscented Kalman filter(UKF)for efficient state estimation,and enhances matching accuracy using pre-built maps.Experimental results demonstrate that the algorithm achieves a maximum positioning error of 0.22 m(mean 0.14 m)in subway tunnel scenarios and further reduced errors to 0.09 m(mean 0.07 m)in open autonomous-rail rapid transit(ART)environments,with per-frame computation time below 50 ms,meeting real-time requirements.The research findings provide an effective solution for high-precision localization in intelligent and autonomous operation applications in the rail transit sector.关键词
小视场/固态激光雷达/融合定位/轨道交通Key words
narrow field of view/solid-state LiDAR/fusion localization/rail transit分类
信息技术与安全科学引用本文复制引用
潘文波,黄文宇,陈志伟,寇晨晨..基于小视场固态激光雷达的融合定位研究[J].控制与信息技术,2026,(1):82-88,7.基金项目
湖南省自然科学基金(2025JJ50726,2025JJ50735) （2025JJ50726,2025JJ50735）
