Innovative Regression Model for Frequency-Dependent Acoustic Source Strength in the Aquatic Environment: Bridging Scientific Insight and Practical Applications

Moshe Greenberg, Uri Kushnir, Vladimir Frid

Research output: Contribution to journalArticlepeer-review

Abstract

This study addresses the challenge of predicting acoustic source strength in freshwater environments, focusing on frequencies between 100–400 kHz. Acoustic signal attenuation is inherently frequency-dependent and influenced by water properties as well as the total propagation path of the acoustic wave, complicating the accurate determination of source strength. To address this challenge, we developed a non-linear regression model for solving the inverse problem of attenuation correction in reflected signals from typical aquatic reflectors, addressing the current absence of robust correction tools in this frequency range. The novelty of our approach lies in designing a non-linear regression framework that incorporates key physical parameters—signal energy, propagation distance, and frequency—enabling accurate source strength prediction. Using an experimental setup comprising ultrasonic transducers and a signal generator under controlled conditions, we collected a comprehensive dataset of 366 samples. The results demonstrate that our proposed model achieves reliable source strength prediction by simplifying Thorpe’s equation for freshwater environments. This research represents a significant advancement in underwater acoustics, providing a practical and reliable tool for source strength estimation in freshwater systems. The developed methodology may have broad applications across sonar technology, environmental monitoring, and aquatic research domains.

Original languageEnglish
Article number1560
JournalSensors
Volume25
Issue number5
DOIs
StatePublished - 1 Mar 2025
Externally publishedYes

Keywords

  • acoustic source strength
  • marine environment
  • nonlinear regression
  • sound attenuation

ASJC Scopus subject areas

  • Analytical Chemistry
  • Information Systems
  • Atomic and Molecular Physics, and Optics
  • Biochemistry
  • Instrumentation
  • Electrical and Electronic Engineering

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