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Due to the robustness in sensing, radar has been highlighted, overcomingharsh weather conditions such as fog and heavy snow. In this paper, we presenta novel radar-only place recognition that measures the similarity score byutilizing Radon-transformed sinogram images and cross-correlation in frequencydomain. Doing so achieves rigid transform invariance during place recognition,while ignoring the effects of radar multipath and ring noises. In addition, wecompute the radar similarity distance using mutable threshold to mitigatevariability of the similarity score, and reduce the time complexity ofprocessing a copious radar data with hierarchical retrieval. We demonstrate thematching performance for both intra-session loop-closure detection and globalplace recognition using a publicly available imaging radar datasets. We verifyreliable performance compared to existing stable radar place recognitionmethod. Furthermore, codes for the proposed imaging radar place recognition isreleased for community.

RaPlace: Place Recognition for Imaging Radar using Radon Transform and Mutable Threshold