Bayesian Inversion Techniques for Synthetic Aperture Radar Imaging

Abstract

The presence of congestion in the electromagnetic (EM) spectrum can have a detrimental effect on the usability of conventionally formed synthetic aperture radar (SAR) images. This is particularly an issue in scenarios involving interference; or where it is desirable to penetrate walls or foliage by transmitting in the low frequency range (which is a notoriously active part of the EM spectrum). To alleviate the effects of excess noise appearing in the recorded data, Bayesian inference techniques can be used during the image formation process, which incorporate prior knowledge about the scene. The techniques aim to obtain an image which is consistent with both prior knowledge and the recorded data, in addition to retaining information on the certainty of the solution.

Date of Award	27 Jul 2022
Original language	English
Awarding Institution	The University of Manchester
Supervisor	Kody Law (Main Supervisor) & William Lionheart (Co Supervisor)