A Sparse Recovery Algorithm for Suppressing Multiple Linear Frequency Modulation Interference in the Synthetic Aperture Radar Image Domain

Guanqi Tong; Xingyu Lu; Jianchao Yang; Wenchao Yu; Hong Gu; Weimin Su

doi:10.3390/s24103095

Sensors (May 2024)

A Sparse Recovery Algorithm for Suppressing Multiple Linear Frequency Modulation Interference in the Synthetic Aperture Radar Image Domain

Guanqi Tong,
Xingyu Lu,
Jianchao Yang,
Wenchao Yu,
Hong Gu,
Weimin Su

Affiliations

Guanqi Tong: School of Electronic and Optical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China
Xingyu Lu: School of Electronic and Optical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China
Jianchao Yang: School of Electronic and Optical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China
Wenchao Yu: School of Electronic and Optical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China
Hong Gu: School of Electronic and Optical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China
Weimin Su: School of Electronic and Optical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China

DOI: https://doi.org/10.3390/s24103095
Journal volume & issue: Vol. 24, no. 10
p. 3095

Abstract

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In synthetic aperture radar (SAR) signal processing, compared with the raw data of level-0, level-1 SAR images are more readily accessible and available in larger quantities. However, an amount of level-1 images are affected by radio frequency interference (RFI), which typically originates from Linear Frequency Modulation (LFM) signals emitted by ground-based radars. Existing research on interference suppression in level-1 data has primarily focused on two methods: transforming SAR images into simulated echo data for interference suppression, or focusing interference in the frequency domain and applying notching filters to reduce interference energy. However, these methods overlook the effective utilization of the interference parameters or are confined to suppressing only one type of LFM interference at a time. In certain SAR images, multiple types of LFM interference manifest bright radiation artifacts that exhibit varying lengths along the range direction while remaining constant in the azimuth direction. It is necessary to suppress multiple LFM interference on SAR images when original echo data are unavailable. This article proposes a joint sparse recovery algorithm for interference suppression in the SAR image domain. In the SAR image domain, two-dimensional LFM interference typically exhibits differences in parameters such as frequency modulation rate and pulse width in the range direction, while maintaining consistency in the azimuth direction. Based on this observation, this article constructs a series of focusing operators for LFM interference in SAR images. These operators enable the sparse representation of dispersed LFM interference. Subsequently, an optimization model is developed that can effectively suppress multi-LFM interference and reduce image loss with the assistance of a regularization term in the image domain. Simulation experiments conducted in various scenarios validate the superior performance of the proposed method.

Published in Sensors

ISSN: 1424-8220 (Online)
Publisher: MDPI AG
Country of publisher: Switzerland
LCC subjects: Technology: Chemical technology
Website: http://www.mdpi.com/journal/sensors

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