Yonghui Wei
ABSTRACT
Millimeter-wave (MMW) radar Simultaneous Localization and Mapping (SLAM) technology is a powerful tool for vehicle detection with limited vision in fire scenario caused by underground road vehicle accident. Current approaches based on the maximum likelihood radar movement locus estimation showed promising results. However, the random error of radar azimuth angle measurement is accumulated and took into radar movement locus estimation due to coordinate transformation and a regular radar scattering pattern distribution caused by a regular radar movement pattern. It also makes an anamorphic occupancy grid map leading to a worse target detection performance. This paper attempts to integrate a prior rail-motion model into the current approach for reducing the accumulated error. This algorithm is validated by the test data measured by a MMW radar mounted on a rail-guided robot in a tunnel. Two cars on fire were set as the targets. The experiment proves the effectiveness of the approach and the error of radar movement locus estimation is less than 0.1m (radar LOS direction) and 1.8m (radar movement direction) respectively.
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Index Terms
- Research on Underground Road Vehicle Location and Mapping Using MMW Radar
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