The accuracy and reliability of hydrophone measurements are critical for various underwater applications. In this study, we present an automated method for acoustic data processing aimed at facilitating hydrophone intercomparison. The method employs robust tone detection to identify and segment acoustic files, enabling precise analysis of the received signals. This approach was applied to the comparison of four hydrophones, with the measurements following ISO/IEC 17043:2010 and ISO 13528:2022 standards for proficiency testing and statistical evaluation. The results demonstrate that the automated segmentation process not only improves the efficiency of data analysis but also ensures consistency across different hydrophones. The method offers significant potential for standardizing acoustic data evaluation in hydrophone calibration and intercomparison studies, contributing to more reliable performance assessments in hydrophone-based measurement system.
Benadí et al. (Wed,) studied this question.