This study provides an argument cautioning against the use of adaptive-beamforming (ABF) techniques in conjunction with a known method for estimating the bottom reflection loss from natural marine ambient noise. This application of ABF has been investigated in the past with rather inconsistent results. Furthermore, no formal proof that ABF algorithms do indeed provide an estimate of the bottom reflection loss is available. This study moves from a recent derivation of the relationship between the bottom reflection coefficient and the Fourier transform of the marine-noise spatial coherence function. The circumstances under which the beamforming operation approximates a discrete Fourier transform (DFT) of the spatial coherence function estimated from array data are analyzed. It is shown that, under certain conditions, conventional beamforming is equivalent to directly computing the DFT of the coherence function, as long as some subtle details are properly taken into account. Furthermore, it is shown that ABF cannot be guaranteed, in general, to perform this operation, and therefore provide an estimate of the bottom reflection coefficient. The conclusions are demonstrated on simulated and measured data.
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November 2018
November 30 2018
An analysis of beamforming algorithms for passive bottom reflection-loss estimation
Lanfranco Muzi;
Lanfranco Muzi
a)
Department of Electrical and Computer Engineering, Portland State University
, 1900 Southwest 4th Avenue, Portland, Oregon 97201, USA
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Martin Siderius;
Martin Siderius
Department of Electrical and Computer Engineering, Portland State University
, 1900 Southwest 4th Avenue, Portland, Oregon 97201, USA
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John Gebbie
John Gebbie
Metron Incorporated
, 2020 Southwest 4th Avenue, Suite 170, Portland, Oregon 97201, USA
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a)
Electronic mail: muzi@pdx.edu
J. Acoust. Soc. Am. 144, 3046–3054 (2018)
Article history
Received:
April 26 2018
Accepted:
November 03 2018
Citation
Lanfranco Muzi, Martin Siderius, John Gebbie; An analysis of beamforming algorithms for passive bottom reflection-loss estimation. J. Acoust. Soc. Am. 1 November 2018; 144 (5): 3046–3054. https://doi.org/10.1121/1.5080258
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