Autofocusing circular synthetic aperture sonar imagery using phase corrections modeled as generalized cones

Area of Science:

• Acoustic imaging
• Signal processing
• Synthetic aperture sonar

Background:

• Circular synthetic aperture sonar (CSAS) generates high-resolution imagery but faces challenges with phase errors due to long aperture lengths.
• Uncorrected phase errors lead to focus aberrations in CSAS images, degrading image quality.

Purpose of the Study:

• To develop a method for estimating and correcting phase errors in CSAS imagery.
• To improve the quality and reliability of CSAS-generated images.

Main Methods:

• Phase error in CSAS image patches is modeled as a generalized cone in wave-number space.
• A method is derived to reconstruct the error cone geometry using local curvature estimates.
• One-dimensional line searches are employed to maximize focus and estimate curvatures.

Main Results:

• The derived method successfully estimates the geometry of phase error cones.
• Aberrations are corrected by applying the estimated cone geometry as an inverse filter.
• The approach is validated on both simulated and real CSAS data with aperture distortions.

Conclusions:

• The proposed method effectively corrects focus aberrations in CSAS imagery.
• This technique enhances the fidelity of high-resolution sonar imaging.
• Accurate phase error correction is crucial for reliable CSAS applications.