Bearing-Only Tracking Considering Dynamics of a Towed Sensor-Array

Abstract

Passive target motion analysis (TMA) of an underwater or surface object relies on bearing only measurements captured by hydrophone sensor-array, which is being towed by an own-ship. These measurements are processed by an onboard state estimation algorithm to derive target kinematics, a process known as bearing-only tracking (BOT). It is well known that the own-ship must perform a maneuvre to make the tracking system observable, due to which the towed sensor-array destabilizes, leading to uncertain positions and unreliable estimations. Calculating an accurate sensor-array positioning is crucial for reliable target state estimation. To address this, we model the dynamics of the towed cable sensor-array using a lumped mass approach, enabling precise determination of the array's position during maneuvres. This derived position is then used in state estimation algorithms for reliable tracking. We compare the performance of various estimators that consider towed sensor-array dynamics against existing methods in terms of evaluating metrics, such as root mean square error (RMSE), percentage track loss, average RMSE, and relative execution time. Our findings demonstrate that incorporating dynamic modeling significantly enhances the accuracy and reliability of BOT.