Automatic RFI Identification for Sentinel-1 Based on Siamese-Type Deep CNN Using Repeat-Pass Images-Reference-Cited by-同舟云学术

Automatic RFI Identification for Sentinel-1 Based on Siamese-Type Deep CNN Using Repeat-Pass Images

Author:

Lu Xingyu¹^ORCID,Wang Chenchen¹^ORCID,Xu Xiaofeng²^ORCID,Yang Huizhang³^ORCID,Zhang Shiyuan¹,Tan Ke¹,Bao Xianglin²^ORCID,Su Weimin¹^ORCID,Gu Hong¹

Affiliation:

1. Department of Electronic and Optical Engineering, Nanjing University of Science and Technology, Nanjing, China

2. School of Computer and Information, Anhui Polytechnic University, Wuhu, Anhui, China

3. Department of Electronic Engineering, Tsinghua University, Beijing, China

Funder

National Natural Science Foundation of China

China Postdoctoral Science Foundation

National Natural Science Foundation of Jiangsu Province

Jiangsu Province Postdoctoral Science Foundation

Provincial Natural Science Foundation of Anhui

Advanced Research Project of Anhui Polytechnic University

Research Start-up Fund for Talent Introduction of Anhui Polytechnic University

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Earth and Planetary Sciences,Electrical and Electronic Engineering

Link

Reference52 articles.

4. A dictionary-based SAR RFI suppression method via robust PCA and chirp scaling algorithm;yang;IEEE Geosci Remote Sens Lett,2020

5. Accurate SAR image recovery from RFI contaminated raw data by using image domain mixed regularizations;lu;IEEE Trans Geosci Remote Sens,2021

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