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Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform

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High-resolution sonar imaging based on wideband fast iterative shrinkage thresholding deconvolution beamforming.

Deyue Hong¹, Zhiwen Qian¹, Xiaomei Fu¹

¹School of Marine Science and Technology, Tianjin University, Tianjin 300072, China.

The Journal of the Acoustical Society of America

|November 11, 2025

Summary

This study introduces a new deconvolution beamforming method using matrix transformation and a monotone fast iterative shrinkage thresholding algorithm (MFISTA) for high-resolution underwater acoustic imaging. The MFISTA method significantly improves resolution and reduces sidelobe levels for wideband coherent signals.

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Three-dimensional Optical-resolution Photoacoustic Microscopy

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Published on: May 3, 2011

Area of Science:

Underwater Acoustic Imaging
Signal Processing
Array Signal Processing

Background:

Conventional beamforming (CBF) is robust and simple for underwater acoustic imaging but limited by the Rayleigh resolution threshold.
Existing deconvolution beamforming methods improve resolution but struggle with incoherent targets and narrowband signals, not matching practical sonar models.
Intensity-based methods fail with coherent targets due to cross-term interference and are unsuitable for wideband signals.

Purpose of the Study:

To develop a high-resolution imaging method for wideband coherent signals in underwater acoustics.
To extend deconvolution beamforming capabilities beyond the limitations of intensity-based methods.
To address the mismatch between current deconvolution techniques and practical sonar imaging models.

Main Methods:

Introduced a matrix transformation technique to focus wideband signals to a reference frequency, approximating them as narrowband.
Developed a complex-domain deconvolution beamforming algorithm (MFISTA) to mitigate cross-term interference from coherent targets.
Utilized simulations with uniform linear arrays and lake-based experiments for validation.

Main Results:

The proposed MFISTA method achieved a main lobewidth less than 1/4 of CBF and 1/3 of other deconvolution methods.
Sidelobe levels were reduced by over 5 dB compared to other methods.
Lake-based experiments confirmed superior resolution, main lobewidth, sidelobe level, and noise immunity over intensity-based methods.

Conclusions:

The matrix transformation and MFISTA approach effectively extends deconvolution beamforming to wideband coherent signals for high-resolution underwater acoustic imaging.
This method overcomes limitations of intensity-based techniques, offering significant improvements in resolution and performance.
The validated performance demonstrates its potential for practical sonar imaging applications.