A large number of roadside Millimeter-Wave Radars (MMRs) serve Intelligent Transportation Systems (ITS), where adaptive calibration is a crucial foundation for long-term roadside ITS services. In distributed radar pairs, overlapping regions between two radars complement each other's information, thereby rapidly expanding coverage. We propose a novel adaptive distributed radar pair calibration method, which considers the similarity between trajectory and road geometry, and vehicle motion consistency, employing a stepwise calibration approach in a simplified transformation model. The mean of residuals standard deviation (MRSD) metric is applied to assess the calibration effectiveness in both lateral and longitudinal directions. The results demonstrate that our proposed algorithm not only achieves high accuracy but also exhibits relatively efficient convergence speed, and we elucidate the mechanism of each module in the final ablation experiment. The dataset in this paper is available online at: https://github.com/tuqing123/radarpairs-calibration-data-share
A Novel Adaptive Calibration Method for Distributed Roadside Millimeter-Wave Radar Pairs
2024-09-24
4682934 byte
Conference paper
Electronic Resource
English
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