Using Shadows in Circular Synthetic Aperture Sonar Imaging for Target Analysis

TL;DR

This paper demonstrates how shadow information in Circular Synthetic Aperture Sonar (CSAS) can be retrieved and used to enhance target recognition and 3D shape reconstruction, providing valuable insights for mine warfare applications.

Contribution

It introduces a method to extract and utilize shadows from CSAS data, combining sub-aperture filtering, fixed focus shadow enhancement, and space-carving for 3D reconstruction.

Findings

Shadows can be effectively retrieved from CSAS data.

Enhanced shadow information improves target shape analysis.

3D reconstruction from shadows is feasible and beneficial.

Abstract

Circular Synthetic Aperture Sonar (CSAS) provides a 360{\deg} azimuth view of the seabed, surpassing the limited aperture and mono-view image of conventional side-scan SAS. This makes CSAS a valuable tool for target recognition in mine warfare where the diversity of point of view is essential for reducing false alarms. CSAS processing typically produces a very high-resolution two-dimensional image. However, the parallax introduced by the circular displacement of the illuminator fill-in the shadow regions, and the shadow cast by an object on the seafloor is lost in favor of azimuth coverage and resolution. Yet the shadows provide complementary information on target shape useful for target recognition. In this paper, we explore a way to retrieve shadow information from CSAS data to improve target analysis and carry 3D reconstruction. Sub-aperture filtering is used to get a collection of images at various points of view along the circular trajectory and fixed focus shadow enhancement (FFSE) is applied to obtain sharp shadows. An interactive interface is also proposed to allow human operators to visualize these shadows along the circular trajectory. A space-carving reconstruction method is applied to infer the 3D shape of the object from the segmented shadows. The results demonstrate the potential of shadows in circular SAS for improving target analysis and 3D reconstruction.