RECONSTRUCTION OF PERIODIC SONAR SIGNALS HIDDEN IN WIDEBAND NOISE USING ENSEMBLE AVERAGING AND MULTI-RATE DSP

Abstract: The reconstruction of periodic acoustical signals with time domain periodic averaging requires a reliable estimate of the fundamental frequency (fl) of the signal. The reconstruction task is particularly difficult when the signal is “hidden ” in additive noise and the signal-to-noise ratio is poor. This is usually the case in most passive SONAR problems when early detection and characterization of targets is required. Statistically reliable estimates of the fundamental frequency of a noisy periodic signal can be computed in the frequency domain using Bartlett’s smoothing procedure. In this procedure, a long, noisy signal is segmented into M mutually exclusive time segments and a power spectral estimate for each segment is computed. Spectral estimates are ensemble-averaged to enhance the signal power and reduce the residual spectral variance of the additive noise. In Bartlett’s smoothing procedure the spectral line detection efficiency improves with M when M> 50. The Bartlett’s smoothing procedure merely provides a range of values for the fundamental frequency within a range of four times the standard deviation of the embedded periodic signal. In the reconstruction phase, the recorded noisy signal i