DOI码：10.1117/1.JRS.14.014515

发表刊物：Journal of Applied Remote Sensing

关键字：synthetic aperture radar; model error; compressed sensing; phaseless measurements.

摘要：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.

合写作者：Zhang Wang,Hao Han,Yuanhang Jia

第一作者：Yanwei Yin (尹艳伟)

论文类型：期刊论文

通讯作者：Falin Liu

论文编号：014515

学科门类：工学

文献类型：J

卷号：14

期号：1

是否译文：否

发表时间：2020-02-01

收录刊物：SCI、EI