Synthetic aperture radar autofocus based on phaseless measurements

DOI number:10.1117/1.JRS.14.014515

Journal:Journal of Applied Remote Sensing

Key Words:synthetic aperture radar; model error; compressed sensing; phaseless measurements.

Abstract:We introduce a new framework for compressed sensing (CS) in synthetic aperture radar (SAR) imaging in the case of model error. Conventional CS-based autofocus methods solve a joint optimization problem to achieve both model error parameter estimation and SAR image formation simultaneously. Owing to the possibly nonconvex feature of the joint optimization problem, however, these algorithms may get stuck in local optima having large phase errors and thus fail to reconstruct the image. In contrast, we use phaseless measurements and pose imaging as a convex optimization problem. To solve the convex problem, we use the alternating direction method of multipliers-based approach, which is computationally efficient and easy to implement. The results from simulations with both point targets and extended targets validate the effectiveness of the proposed method.

First Author:Yanwei Yin (尹艳伟)

Co-author:Zhang Wang,Hao Han,Yuanhang Jia

Indexed by:Journal paper

Correspondence Author:Falin Liu

Document Code:014515

Discipline:Engineering

Document Type:J

Volume:14

Issue:1

Translation or Not:no

Date of Publication:2020-02-01

Included Journals:SCI、EI