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Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform

Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform

Published on: February 12, 2014

Fast nearfield to farfield conversion algorithm for circular synthetic aperture sonar.

Daniel S Plotnick¹, Philip L Marston¹, Timothy M Marston²

¹Department of Physics and Astronomy, Washington State University, Pullman, Washington 99164-2814 daniel.plotnick@wsu.edu, marston@wsu.edu.

The Journal of the Acoustical Society of America

|August 7, 2014

Summary

Circular synthetic aperture sonar (CSAS) imaging algorithms typically assume farfield data. This study presents a nearfield to farfield conversion algorithm to correct image distortions when farfield measurements are impractical.

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Area of Science:

Acoustics
Signal Processing
Sonar Imaging

Background:

Monostatic circular synthetic aperture sonar (CSAS) imaging relies on azimuthal angle-dependent backscattering.
Standard CSAS algorithms assume data acquisition in the farfield.
Nearfield measurements, often necessitated by experimental constraints, introduce image distortions and alter feature angular dependence.

Purpose of the Study:

To develop and present a method for correcting image distortions in CSAS when data is acquired in the nearfield.
To enable accurate target imaging even when farfield measurements are not feasible.

Main Methods:

A fast, approximate Hankel function-based algorithm is introduced.
This algorithm converts nearfield scattering data to the farfield equivalent.
The method is applied to an extended target for comparative analysis.

Main Results:

The developed algorithm effectively converts nearfield CSAS data to the farfield.
Comparison of images and spectrograms reveals significant reduction in distortions when using the nearfield-to-farfield correction.
Accurate angular dependence of target features is preserved.

Conclusions:

The presented Hankel function-based algorithm provides a viable solution for CSAS imaging in nearfield conditions.
This method overcomes limitations of traditional farfield assumptions, improving image fidelity.
Accurate sonar imaging is achievable even with experimental constraints preventing farfield data collection.