Heading and hydrophone data fusion for towed array shape estimation

Abstract

This paper addresses the problem of towed array shape estimation for passive, horizontal sonar arrays. Beamforming and localization techniques significantly degrade when an assumed linear array bends due to tow platform maneuvers or ocean currents. In this paper, heading sensors along the array and acoustic hydrophone data are jointly used to estimate the shape of the array. Previously, heading data have been filtered using a dynamical motion model to reduce noise during turns. In recent work, a time-varying noise field directionality estimate that incorporates a dynamical model for the acoustic field provides a second, albeit biased, estimate of the array shape. In this paper, these two estimates are combined via adaptive weights to obtain improved shape estimates during maneuvers. A multi-source simulation is used to demonstrate the robustness of the combined array shape estimate when compared to the separate heading or acoustic sensor based techniques.

All-fiber acoustic-posture integrated towed linear array based on fiber laser hydrophone

“…At present, for the ultra-fine towed linear array without attitude sensor, only the shape of the tow cable is estimated [7] . Odom J L [8] et al propose to combine the two estimations using adaptive weights to obtain improved shape estimation during maneuvering; Yue-Hui T [9] et al proposed a method to a shape deformation estimation method for towed array sonar has been proposed based on parabolic model and exponential model; Maofa W [10] et al pointed out that a motion model of the towed linear array under an ISW according to the Korteweg-De Vries (KdV) equation and solve the model by finite method combined with the Newton iteration method. There is currently no all fiber towed linear array that can integrate distributed attitude measurement and point type sound measurement.…”