Underwater Range-Only Particle Filter Localization of a Full Ocean Depth Autonomous Profiler

Autonomous marine vehicles of various types have become essential tools for oceanographic research, allowing in situ data collection in challenging marine environments. However, accurately determining the position of a vehicle during underwater missions remains a challenging problem that creates difficult operational scenarios and limits the effectiveness of data collection. This study utilizes a particle filter-based localization method for the hadal-rated Deep Autonomous Profiler (DAP). Our particle filter approach successfully estimates the DAP's position throughout its deployment using range-only acoustic measurements from a topside vessel. The computational efficiency allows real-time implementation, making it suitable for a range of operating scenarios and other vehicles. The particle filter-based localization can provide precise placement of in-situ measurements and data collection without the need for an ultra-short baseline (USBL), demonstrating the utility of probabilistic approaches in marine operations and exploration.