BELOW-BAND SIGNAL PROCESSING FOR LOCALIZING DISTANTSOURCES IN A NOISY DEEP OCEAN
David J. Geroski, David R. Dowling
Abstract:
Frequency Difference Source Localization (FDSL) methods have proven successful
for localizing sources both in the deep ocean and in the shallow ocean using recordings from a vertical array of hydrophones. These source localization algorithms are based upon the phase coherence of a product of recorded complex field values, termed autoproducts, at frequencies below the recordings’ bandwidth. Similar to Matched Field Processing (MFP), the measured autoproduct is correlated to a replica that is calculated based on the user's knowledge of the acoustic environment. These below-band source localization methods are
nonlinear and sacrifice in-band spatial resolution for robustness to environmental mismatch.
Past frequency-difference localization efforts utilized high signal-to-noise ratio (SNR) data to demonstrate robustness to mismatch. This paper explores the performance of FDSL in the presence of noise. Specifically, simulated noise and noise measured during the PhilSea10 experiment are added to both simulated and measured pings to determine the SNR below which localization performance begins to degrade. For the scenario considered here, the source was located 210 km from a vertical receiving array in a deep ocean environment with an active internal wave field. The source broadcast was a linear frequency sweep from 200 to 300 Hz. At high SNR (>20 dB) using single-digit-Hertz below-band frequencies, the source is correctly localized in all simulations, and in 97 out of 100 trials using single-broadcast ocean recordings. For simulated and measured forward signals distorted by simulated noise, this
performance persists down to SNR's of –20 and –14 dB, respectively. For measured forward signals with elevated levels of measured noise, successful performance persists down to –8 dB SNR.
Keywords: Source Localization, Nonlinear Signal Processing, Matched Field Processing