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Predicting hydrophone phase and evaluating its uncertainty using magnitude data and minimum phase approach.

Hasan Koruk¹, Srinath Rajagopal¹, William Vale²

¹Ultrasound and Underwater Acoustics, Department of Medical, Marine and Nuclear, National Physical Laboratory, Teddington TW11 0LW, United Kingdom.

|November 11, 2025

Summary

This study presents a new method to predict hydrophone phase response and its uncertainty using magnitude data. This simplifies calibration for ultrasound device acoustic measurements.

Keywords:

Calibration Hydrophone Machine learning Minimum phase approach Phase Phase uncertainty Ultrasound

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Area of Science:

Acoustics
Metrology
Signal Processing

Background:

Hydrophones are crucial for measuring ultrasound transducer acoustic output.
Direct phase response calibration is complex and sensitive to experimental conditions.
Magnitude response is typically quantified, while phase is often neglected.

Purpose of the Study:

To establish a procedure for estimating hydrophone phase response.
To evaluate the uncertainty associated with the predicted phase response.
To simplify hydrophone calibration by leveraging magnitude data.

Main Methods:

Utilized the minimum phase approach to calculate phase from a preconditioned magnitude spectrum.
Applied propagation of uncertainty to determine phase uncertainty from magnitude uncertainty.
Employed a machine learning model to assess phase uncertainty from band-limited magnitude spectra.

Main Results:

The developed procedure accurately predicted phase responses and evaluated uncertainties for hydrophone models.
Results showed good agreement with reference values for tested hydrophones.
The method demonstrated practical applicability for various hydrophones.

Conclusions:

The proposed procedure offers a practical solution for predicting hydrophone phase response.
It provides a reliable method for evaluating phase uncertainty, simplifying calibration.
This technique enhances the characterization of hydrophones in acoustic measurements.