Quantifying Digitizer Design Requirements for a Sediment-Generated Noise Instrument

Coarse sediment that rivers move along their bed, or bedload, generates noise by interparticle collisions, otherwise known as sediment-generated noise (SGN). Development of a purpose-built low-power acoustic detector of underwater bedload transport would benefit water managers, hydrologists, and conservation efforts targeted at fluvial environments. Such a detector needs to have a long battery life in order to run autonomously over long periods; therefore, the sampling frequency and bit depth should be minimized in order to save power. This letter provides an estimate of how bit depth and sample rate affect SGN detection by using algorithms analogous to a variety of published SGN detection methods. We find that 12 bits and 11 kHz are sufficient to meet a median of 5% difference for all features chosen.

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Publication Details

Journal
IEEE Sensors Letters
Published
2025-09-09
DOI
https://doi.org/10.1109/lsens.2025.3607899
Primary Topic
Underwater Acoustics Research
Type
article
Field-Weighted Citation Impact
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article

Quantifying Digitizer Design Requirements for a Sediment-Generated Noise Instrument

David C. Burnett, James S. White, Quinn Morgan, Nate Sjullie
IEEE Sensors Letters
Underwater Acoustics Research
article

Quantifying Digitizer Design Requirements for a Sediment-Generated Noise Instrument

David C. Burnett, James S. White, Quinn Morgan, Nate Sjullie
article en

Abstract

Coarse sediment that rivers move along their bed, or bedload, generates noise by interparticle collisions, otherwise known as sediment-generated noise (SGN). Development of a purpose-built low-power acoustic detector of underwater bedload transport would benefit water managers, hydrologists, and conservation efforts targeted at fluvial environments. Such a detector needs to have a long battery life in order to run autonomously over long periods; therefore, the sampling frequency and bit depth should be minimized in order to save power. This letter provides an estimate of how bit depth and sample rate affect SGN detection by using algorithms analogous to a variety of published SGN detection methods. We find that 12 bits and 11 kHz are sufficient to meet a median of 5% difference for all features chosen.

IEEE Sensors LettersVol. 9(10)
Portland State University (US), United States Geological Survey (US)
Openalex Percentile: Top 75%
Underwater Acoustics Research
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