Multi-look processing of high-resolution SAS data for improved target detection performance

Abstract

The rich content of synthetic aperture sonar (SAS) data is typically used to generate imagery with resolution as high as theoretically possible. But when the ultimate purpose of the imagery is for detecting objects with sizes large compared to the resolution cell, exploiting the raw data in alternative ways can be more useful. We first show how multiple lower-resolution SAS images (i.e., “looks”) can be obtained in an efficient, principled manner by band-limiting the image wavenumber spectrum of a full-resolution SAS image. By combining these multiple looks (from different aspect and frequency bands), a despeckled image that enjoys greater (target) signal to (seabed) reverberation ratio can be produced. On a large set of real SAS data collected at sea, it is demonstrated how better target detection performance of underwater mines can be achieved by using the lower-resolution despeckled imagery rather than single-look, maximum-resolution imagery.