Shape estimation and self-noise analysis for towed arrays

Towed line arrays of hydrophones are used in the underwater environment to detect weak signals, to resolve closely-spaced contacts and to estimate the bearing and other properties of acoustic sources. The detection performance of a towed array is limited by its self-noise. Towed array data are processed using an adaptive spatial filtering technique implemented in the frequency domain. The resulting frequency-wavenumber spectrum enables the self-noise to be readily identified, its temporal and spatial properties to be quantified and its propagation speed along the array to be estimated. The performance of a towed array sonar system is observed to degrade during a change of course by the tow vessel because the shape of the array becomes nonlinear. Adaptive beamforming of the towed array data leads to signal suppression due to phase errors resulting from imperfect knowledge of the hydrophone positions. This characteristic of the adaptive beamformer is exploited here to compare the performance of two array shape estimation techniques which use only data from the hydrophones themselves to estimate the shape of the array