Measuring the characteristics of backscattering of sound on a rough surface in the near-field zone of a phased array

Salin, M. B.; Potapov, O. A.; Salin, B. M.; Chashchin, A. S.

doi:10.1134/s106377101506010x

Cited by 6 publications

(1 citation statement)

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“…ADCP is equipped with 4 echo sounder beams that can be treated as 4 water height gauges than allows tracking elevation and skew of the surface, produced by long waves. Another design of upward-looking acoustic tools relies on sound scattering model to reconstruct surface spectrum moments basing on the Doppler spectrum of the reflected signal [12][13][14]. High frequency signals reverberation patterns may allow to track individual wave crests in vicinity of the transducer, as it has been reported by [15] and [16].…”

Section: Introductionmentioning

confidence: 99%

Surface waves prediction based on long-range acoustic backscattering in a mid-frequency range

Ermoshkin,

Kosteev,

Ponomarenko

et al. 2022

Preprint

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New data was obtained for a frequency band that had not been so well-studied for sea surface probing applications before. During the described 2-weeks sea experiment 1-3 kHz tonal pulses were emitted from a platform, located on the northern Black Sea shelf, and Doppler spectrum of reverberation was studied. We believe that this band is worth further studying due the sound propagation range is large enough to meet practical needs in coastal zone while the angle-distance resolution is quite moderate. However it is quite difficult to interpret the obtained data since backscattering spectrum shape is influenced by a series of effects and has a complicated link to wind waves and currents parameters. Backscattering of acoustical signals was received for distances around 2 nautical miles. Significant wave height, dominant wave frequency were estimated as the result of such signals processing with the use of machine learning tools. A decision-tree-based mathematical regression model was trained to solve the inverse problem. Wind waves prediction is in a good agreement with direct measurements, made on the platform, and machine learning results allow physical interpretation.

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