A point cloud processing method of mmWave radar over automotive scenario
Qingmian Wan, Hongli Peng, Xing Liao, Kuayue Liu
TL;DR
This paper presents a method for processing mmWave radar point clouds in automotive scenarios, improving target detection accuracy and efficiency by using radar RA maps and point cloud data to better judge road boundaries and target coordinates.
Contribution
The paper introduces a novel approach combining radar RA maps and point cloud data to enhance target judgment and processing efficiency in automotive radar applications.
Findings
Improved target judgment accuracy using combined radar RA map and point cloud data.
Enhanced processing efficiency of DBSCAN clustering for automotive radar targets.
Effective road boundary detection and target coordinate estimation.
Abstract
This paper introduces in detail the effective method of comprehensive target judgment by using radar RA map and point cloud map. Different output of radar can effectively judge the road boundary of target and the relative coordinates of target, avoid the error of output caused by excessive processing information, and greatly improve the processing efficiency of DBSCAN of the measured target.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsBiometric Identification and Security · Advanced Optical Sensing Technologies · Remote Sensing and LiDAR Applications