Signal Absorption-Based Range Estimator for Undersea Swarms

Submitted in partial fulfillment of the requirements for the degree of Master of Science in Mechanical Engineering at the Massachusetts Institute of Technology and the Woods Hole Oceanographic Institution September 2020.Robotic swarms are increasingly complex above the waterline due to reliable communication links. However, the limited propagation of similar signals in the ocean has impacted advances in undersea robotics. Underwater vehicles often rely on acoustics for navigation solutions; however, this presents challenges for robotic swarms. Many localization methods rely on precision time synchronization or two-way communication to estimate ranges. The cost of Chip-scale Atomic Clocks (CSACs) and acoustic modems is limiting for large-scale swarms due to the cost-per-vehicle and communications structure. We propose a single vehicle with reliable navigation as a "leader" for a scalable swarm of lower-cost vehicles that receive signals via a single hydrophone. This thesis outlines range estimation methods for sources with known signal content, including frequency and power at its origin. Transmission loss is calculated based on sound absorption in seawater and geometric spreading loss to estimate range through the Signal Absorption-Based Range Estimator (SABRE). SABRE's objective is to address techniques that support low-cost undersea swarming. This thesis's contributions include a novel method for range estimation onboard underwater vehicles that supports relative navigation through Doppler-shift methods for target bearing. This thesis develops the theory, algorithms, and analytical tools for real-world data range estimation