Maritime radars are prevalently adopted to capture the vessel's omnidirectional data as imagery. Nevertheless, inherent 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 estimating 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.

翻译：海事雷达普遍用于以图像形式捕获船舶的全向数据。然而，海洋雷达仍存在固有挑战，包括频率受限、分辨率欠佳以及检测结果不确定。此外，广阔海域中可识别地标的稀缺性仍是一个难题，导致连续场景中常缺乏匹配的特征点。在此背景下，我们提出了一种稳健的海事雷达扫描表示方法LodeStar，以及一种针对海洋雷达应用定制的增强特征提取技术。进而，我们采用半直接方法估算海洋雷达里程计。基于LodeStar的方法显著降低了里程计估计的误差，这一结论通过细致的实验验证得到了证实。