2026/07/15 by Cody A. Marquardt, HeonYong Kang · 1 voice
Computer Science · Engineering · #Indoor and Outdoor Localization Technologies #Target Tracking and Data Fusion in Sensor Networks #Underwater Vehicles and Communication Systems
paper · doi:10.1002/rob.70279
openalex publication_date 2026/07/15 · openalex created_date 2026/07/16 · openalex updated_date 2026/07/17
ABSTRACT Robust localization of autonomous underwater vehicles is conventionally performed using dead‐reckoning, but its accumulated error can be excessive for long‐term or pioneering exploration when the Doppler Velocity Log cannot maintain bottom‐lock and when positioning references such as Ultra‐Short‐Base‐Line systems are unavailable. In this letter, we present an online localization that identifies current disturbances and corrects underwater position in real time without global references. An online Pruned Exact Linear Time method for optimal detection of statistical anomalies, such as current disturbances, is further expanded for real‐time dataset update and integrated with Kalman filter state estimation via recursive iteration. We demonstrate high accuracy in random‐current simulation and validate localization performance through implementation using 3‐h field data at two offshore sites. Furthermore, the comparative analysis indicates that, unlike other methods, online localization can effectively estimate underwater position in the presence of varying or stronger currents without dynamic model constraints.