Feature-Aided Tracking Techniques for Active Sonar Applications
Jordan LeNoach, Michael Lexa, Stefano P. Coraluppi · 2021 IEEE 24th International Conference on Information Fusion (FUSION) · 2021
Feature-aided tracking techniques seek to improve tracking performance by utilizing additional feature information from detections in combination with the typical kinematic measurements such as bearing, range, and Doppler. In this paper, we explore three techniques primarily based around measured signal-to-noise ratio and target strength: single-ping scoring, state augmentation, and composite confirmation logic. Through simulated active sonar scenarios, we demonstrate tracking performance improvements through these techniques which include both improvement in both target and track completeness.