Analysis and suppression of bias effect in sparse SAR imaging

Zhongqiu Xu; Zhonghao Wei; Mingqian Liu; Bingchen Zhang; Yirong Wu

doi:10.1117/12.2532446

7 October 2019 Analysis and suppression of bias effect in sparse SAR imaging

Zhongqiu Xu, Zhonghao Wei, Mingqian Liu, Bingchen Zhang, Yirong Wu

Proceedings Volume 11155, Image and Signal Processing for Remote Sensing XXV; 111551E (2019) https://doi.org/10.1117/12.2532446
Event: SPIE Remote Sensing, 2019, Strasbourg, France

Abstract

The analytic solution of sparse signal reconstruction algorithm based on L₁ regularization is a biased estimation, which leads to the underestimation of target intensity when applied to sparse SAR imaging, resulting in the bias effect and affecting the reconstruction accuracy. In this paper, we quantitatively analyze the bias effect in SAR imaging applications, and analyse the influence of target intensity, signal-to-noise ratio, intensity ratio of adjacent targets in the observation scene on the reconstruction bias. In order to suppress the bias effect and improve the reconstruction accuracy, we adopt a class of algorithms based on nonconvex penalty, and verify the performance of these algorithms using simulations and real data.

Conference Presentation

Citation Download Citation

Zhongqiu Xu, Zhonghao Wei, Mingqian Liu, Bingchen Zhang, and Yirong Wu "Analysis and suppression of bias effect in sparse SAR imaging", Proc. SPIE 11155, Image and Signal Processing for Remote Sensing XXV, 111551E (7 October 2019); https://doi.org/10.1117/12.2532446

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available