Enhanced processing for a towed array using an optimal noise canceling approach

Noise self-generated by a surface ship towing an array in search of a weak target presents a major problem for the signal processing especially if broadband techniques are being employed. In this paper we discuss the development and application of an adaptive noise cancelling processor capable of extracting the weak far-field acoustic target in a noisy ocean acoustic environment. The fundamental idea for this processor is to use a model-based approach incorporating both target and ship noise. Here we briefly describe the underlying theory and then demonstrate through simulation how effective the canceller and target enhancer perform. The adaptivity of the processor not only enables the "tracking" of the canceller coefficients, but also the estimation of target parameters for localization. This approach which is termed "joint" cancellation and enhancement produces the optimal estimate of both in a minimum (error) variance sense