Radar Localization Held 99.38% Recall in Falling Snow

ReRadar extracts rotation-equivariant features from scanning millimeter-wave radar, pools them into rotation-invariant place descriptors, then uses landmark matching to estimate a three-degree-of-freedom pose. With target-dataset adaptation, it reached 99.37% Recall@1 on OORD Bellmouth, 91.44% on Mulran DCC01 and 99.38% on a falling-snow Boreas sequence. A cross-dataset model without target data reached 98.07% on OORD. The tests suggest that preserving spatial structure before invariant pooling can improve global localization under difficult weather and viewpoint changes.