Adaptive underwater target tracking using passive multipath time-delay measurements

TLDR

Underwater targets can undergo large, unpredictable changes in velocity and depth, making tracking challenging. The study aims to adaptively track an underwater maneuvering target’s range and velocity using passive time‑delay measurements. The tracking system uses a linearized polar motion model and incorporates a nonlinear block to enhance performance. The approach removes the need for extended Kalman filters, improving robustness, and partially decouples depth estimation from range estimation, reducing computational complexity.

Abstract

This paper examines the problem of adaptively tracking in range and velocity an underwater maneuvering target using passive time delay measurements. The target can make large scale random velocity and depth changes at times which are unknown to the observer. Tracking is accomplished by making use of the basic linearized polar model of target and observer motion previously developed [1]. Now, however, a nonlinear system block has been added to the tracking system [2], [3], which leads to two major benefits. First, the need for extended Kalman filters is eliminated making the passive tracking system more robust than it was previously [3]. The second benefit is a partial decoupling of depth estimation from the polar range estimator, which considerably reduces the computational level of the adaptive tracking system.