  Due to the robustness in sensing, radar has been highlighted, overcoming
harsh weather conditions such as fog and heavy snow. In this paper, we present
a novel radar-only place recognition that measures the similarity score by
utilizing Radon-transformed sinogram images and cross-correlation in frequency
domain. Doing so achieves rigid transform invariance during place recognition,
while ignoring the effects of radar multipath and ring noises. In addition, we
compute the radar similarity distance using mutable threshold to mitigate
variability of the similarity score, and reduce the time complexity of
processing a copious radar data with hierarchical retrieval. We demonstrate the
matching performance for both intra-session loop-closure detection and global
place recognition using a publicly available imaging radar datasets. We verify
reliable performance compared to existing stable radar place recognition
method. Furthermore, codes for the proposed imaging radar place recognition is
released for community.
