TOWED ARRAY SHAPE ESTIMATION USING KALMAN FILTERS - EXPERIMENTAL INVESTIGATIONS

This is the second of two papers describing the use of Kalman filters to estimate the shape of a towed array of hydrophones. The first paper presented the problem of estimating the shape of a towed array instru mented with either depth sensors, compasses, or both in a discrete tim e state space formulation. This state space representation was derived from a dynamical model of the propagation of tow point induced motion down the array. A Kalman filter was derived to recursively estimate t he shape of this towed array. In addition, solutions to the Riccati eq uation were used to predict the mean square error of the Kalman filter array shape estimates. The present paper investigates the performance of this Kalman filter approach as an array shape estimator using both simulated examples and sea trial data. Fundamental to the Kalman filt er approach is the model that describes the dynamical behavior of the towed array. The results of an experimental program that was recently undertaken to validate this model are also presented.