Optimal spatial filtering of real data from submarine sonar arrays

Abstract

Submarine hydrophone arrays sample the underwater acoustic pressure field in space and time to sense the presence of sources of radiated sound and to extract tactical information from the received sounds. The outputs of the hydrophones are combined by a spatial filter (or beamformer) so that signals from a chosen direction are coherently added while the effects of noise and interference from other directions are reduced by destructive interference. The spatial filter appropriately weights the hydrophone outputs prior to summation so as to enhance the output signal-to-noise ratio, thereby improving the detection, classification, localization and tracking performance of the passive sonar system onboard the submarine. By processing real acoustic data from a submarine hull-mounted array, it is shown that an optimal (adaptive) frequency-domain spatial filter (based on inversion of the observed cross spectral matrix for each frequency bin) enhances the detection of underwater acoustic signals, when compared with conventional spatial filtering (or delay-and-sum beamforming). The degree of improvement, however, depends on the method used to normalize the cross spectral matrix. Superior detection performance for a submarine hull-mounted array occurs when the observed cross spectral matrix for each frequency of interest is normalized using the average of all the single hydrophone output powers at each frequency. It is also shown that the self-noise analysis of a submarine towed array is facilitated by processing the element-level data in the frequency-wave number domain with a constrained optimal spatial filter, which is also referred to as a Minimum Variance Distortionless Response (MVDR) beamformer. This spatiotemporal filtering method is employed to separate signals (surface ship contacts) and tow vessel noise components (direct path and multipath arrivals) according to their directions of propagation. This method is also found to separate spatially-correlated self-noise components that propagate within the towed array structure at a speed that is slower than the speed of sound travel in water. A comparison of the frequency-wave number power spectra estimated using conventional and optimal spatial filtering methods shows that the MVDR spatial filter enables the various sources of acoustic energy that are sensed by the array to be more clearly delineated in frequency-wave number space. The MVDR spatial filter is a data-adaptive spatial filter that is observed to suppress spatial leakage, to enhance the spatial resolution of a towed array through narrower beamwidths, and to provide superdirective array gain at frequencies well below the design frequency of the towed array. Frequency-wave number analysis with optimal spatial filtering is a powerful diagnostic tool for studying the self-noise characteristics of a towed linear array of hydrophones.