Leveraging Machine Learning for Advanced Passive Sonar Tracking

Passive sonar systems employ a standardized signal processing pipeline to track, classify, and localize underwater contacts. This automated process, often referred to as "automation," begins after front-end processing generates visual displays for sonar operator analysis and automated processing. Existing algorithms that track energy signatures on these displays typically include Kalman filters, probabilistic multi-hypothesis trackers, and particle filters. However, these traditional tracking me...