A Method for Generating Occupancy Grid Maps Based on 4D Millimeter-Wave Radar Point Cloud Characteristics
4D millimeter wave radar is a high-resolution sensor that has a strong perception ability of the surrounding environment. This paper uses millimeter wave radar point cloud to establish a static probabilistic occupancy grid map for static environment modeling. In order to obtain a clean occupancy grid map, we classify the point cloud according to the result of dynamic point clustering and project the classified point cloud into the grid map. Based on the distribution and category of millimeter wave radar point cloud, we propose a calculation model of grid occupancy probability. After obtaining the occupancy probability according to the calculation model, we calculate the posterior occupancy probability by using the motion law of self-vehicle and Bayesian filtering, and construct a stable probabilistic occupancy grid map. We test the method on real roads, and the results show that the proposed method can effectively suppress the influence of noise points on the quality of grid map, and improve the effect of grid map in long-distance range.
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/issn/01487191
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Supplemental Notes:
- Abstract reprinted with permission of SAE International.
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Authors:
- Liu, Chang
- Lu, Xinfei
- Xue, Dan
- Wu, Li
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Conference:
- SAE 2023 Intelligent and Connected Vehicles Symposium
- Location: Nanchang , China
- Date: 2023-9-22 to 2023-9-23
- Publication Date: 2023-12-20
Language
- English
Media Info
- Media Type: Web
- Features: References;
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Serial:
- SAE Technical Paper
- Publisher: Society of Automotive Engineers (SAE)
- ISSN: 0148-7191
- EISSN: 2688-3627
- Serial URL: http://papers.sae.org/
Subject/Index Terms
- TRT Terms: Actuators; Fabrication; Logistics; Noise; Radar; Roads; Sensors; Simulation
- Subject Areas: Highways; Vehicles and Equipment;
Filing Info
- Accession Number: 01903757
- Record Type: Publication
- Source Agency: SAE International
- Report/Paper Numbers: 2023-01-7047
- Files: TRIS, SAE
- Created Date: Dec 29 2023 10:29AM