title: High-resolution bottom-loss estimation using the ambient-noise vertical coherence function.
abstract: The seabed reflection loss (shortly "bottom loss") is an important quantity for predicting transmission loss in the ocean. A recent passive technique for estimating the bottom loss as a function of frequency and grazing angle exploits marine ambient noise (originating at the surface from breaking waves, wind, and rain) as an acoustic source. Conventional beamforming of the noise field at a vertical line array of hydrophones is a fundamental step in this technique, and the beamformer resolution in grazing angle affects the quality of the estimated bottom loss. Implementation of this technique with short arrays can be hindered by their inherently poor angular resolution. This paper presents a derivation of the bottom reflection coefficient from the ambient-noise spatial coherence function, and a technique based on this derivation for obtaining higher angular resolution bottom-loss estimates. The technique, which exploits the (approximate) spatial stationarity of the ambient-noise spatial coherence function, is demonstrated on both simulated and experimental data.
authors.affiliation: Department of Electrical and Computer Engineering, Portland State University, 1900 Southwest 4th Avenue, Portland, Oregon 97201.
authors.forename: Lanfranco
authors.initials: L
authors.lastname: Muzi
authors.affiliation: Department of Electrical and Computer Engineering, Portland State University, 1900 Southwest 4th Avenue, Portland, Oregon 97201.
authors.forename: Martin
authors.initials: M
authors.lastname: Siderius
authors.affiliation: School of Earth and Ocean Sciences, University of Victoria, 3800 Finnerty Road, Victoria, British Columbia V8P 5C2, Canada.
authors.forename: Jorge E
authors.initials: JE
authors.lastname: Quijano
authors.affiliation: School of Earth and Ocean Sciences, University of Victoria, 3800 Finnerty Road, Victoria, British Columbia V8P 5C2, Canada.
authors.forename: Stan E
authors.initials: SE
authors.lastname: Dosso