Work

Graph Signal Processing-Based Imaging for Synthetic Aperture Radar

Year: 2019

Type: article

Abstract: In this letter, we propose graph signal processing-based imaging for synthetic aperture radar (SAR). Our method provides improved denoising and resolution enhancing capabilities, along with a reduction in computational complexity, by exploiting the concept of extended neighborhood in SAR images. We present a modified version of a fused least absolute shrinkage and selection operator (LASSO) to cater for graph structure of the SAR image. It can also accommodate the compressed sensing framework. We solve the optimization problem via the alternating direction method of multipliers. Experimental results on a backhoe target corroborate the validity of our proposed method.

Source: IEEE Geoscience and Remote Sensing Letters

DOI: 10.1109/lgrs.2019.2919147

Authors: Shahzad Gishkori, Bernard Mulgrew

Institution: University of Edinburgh

Language: English

Topic: Advanced SAR Imaging Techniques

Subfield: Aerospace Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: green

Funders: Jaguar Land Rover, Engineering and Physical Sciences Research Council

Awards: TASCC: Pervasive low-TeraHz and Video Sensing for Car Autonomy and Driver Assistance (PATH CAD), G5702459141