A new method for SAR radio frequency interference mitigation based on maximum a posterior estimation

Yong Qiang Guo, Feng Zhou, Mingliang Tao, Ming Sheng

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

8 Scopus citations

Abstract

Hazardous to synthetic aperture radar (SAR), the radio frequency interference (RFI) significantly degrades the SAR imaging quality and prevents accurate image interpretation. In recent years, RFI mitigation has received intensive attention in the active microwave remote sensing community. Making use of the statistical distribution of RFI and SAR echoes, this paper proposes a new method for RFI suppression based on the maximum a posterior (MAP) estimation. After careful modeling of sparse prior and data likelihood, the method performs Bayesian inference of the posterior and estimates the model parameters by MAP. Then, it reconstructs RFI and subtracts it from the raw data. Finally, it obtains well-focused SAR image using the state-of-the-art imaging techniques. The effectiveness of the method has been validated using measured SAR data.

Original languageEnglish
Title of host publication2017 32nd General Assembly and Scientific Symposium of the International Union of Radio Science, URSI GASS 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-4
Number of pages4
ISBN (Electronic)9789082598704
DOIs
StatePublished - 10 Nov 2017
Event32nd General Assembly and Scientific Symposium of the International Union of Radio Science, URSI GASS 2017 - Montreal, Canada
Duration: 19 Aug 201726 Aug 2017

Publication series

Name2017 32nd General Assembly and Scientific Symposium of the International Union of Radio Science, URSI GASS 2017
Volume2017-January

Conference

Conference32nd General Assembly and Scientific Symposium of the International Union of Radio Science, URSI GASS 2017
Country/TerritoryCanada
CityMontreal
Period19/08/1726/08/17

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