LodeStar: Maritime Radar Descriptor for Semi-Direct Radar Odometry

Maritime radars are prevalently adopted to capture the vessel’s omnidirectional data as imagery. Nevertheless, in- herent challenges persist with marine radars, including limited frequency, suboptimal resolution, and indeterminate detections. Additionally, the scarcity of discernible landmarks in the vast marine expanses remains a challenge, resulting in consecutive scenes that often lack matching feature points. In this context, we introduce a resilient maritime radar scan representation LodeStar, and an enhanced feature extraction technique tailored for marine radar applications. Moreover, we embark on esti- mating marine radar odometry utilizing a semi-direct approach. LodeStar-based approach markedly attenuates the errors in odometry estimation, and our assertion is corroborated through meticulous experimental validation. The code will be available from https://github.com/hyesu-jang/LodeStar.