Interference Mitigation for Synthetic Aperture Radar Based on Deep Residual Network

被引:59
作者
Fan, Weiwei [1 ]
Zhou, Feng [1 ]
Tao, Mingliang [2 ]
Bai, Xueru [3 ]
Rong, Pengshuai [1 ]
Yang, Shuang [1 ]
Tian, Tian [1 ]
机构
[1] Xidian Univ, Minist Educ, Key Lab Elect Informat Countermeasure & Simulat T, Xian 710071, Peoples R China
[2] Northwestern Polytech Univ, Sch Elect & Informat, Xian 710072, Peoples R China
[3] Xidian Univ, Natl Lab Radar Signal Proc, Xian 710071, Peoples R China
基金
中国国家自然科学基金; 中国博士后科学基金;
关键词
Radio Frequency Interference (RFI); interference mitigation; Synthetic Aperture Radar (SAR); deep residual network (ResNet); SUPPRESSION; FUSION; RFI;
D O I
10.3390/rs11141654
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Radio Frequency Interference (RFI) is a key issue for Synthetic Aperture Radar (SAR) because it can seriously degrade the imaging quality, leading to the misinterpretation of the target scattering characteristics and hindering the subsequent image analysis. To address this issue, we present a narrow-band interference (NBI) and wide-band interference (WBI) mitigation algorithm based on deep residual network (ResNet). First, the short-time Fourier transform (STFT) is used to characterize the interference-corrupted echo in the time-frequency domain. Then, the interference detection model is built by a classical deep convolutional neural network (DCNN) framework to identify whether there is an interference component in the echo. Furthermore, the time-frequency feature of the target signal is extracted and reconstructed by utilizing the ResNet. Finally, the inverse time-frequency Fourier transform (ISTFT) is utilized to transform the time-frequency spectrum of the recovered signal into the time domain. The effectiveness of the interference mitigation algorithm is verified on the simulated and measured SAR data with strip mode and terrain observation by progressive scans (TOPS) mode. Moreover, in comparison with the notch filtering and the eigensubspace filtering, the proposed interference mitigation algorithm can improve the interference mitigation performance, while reducing the computation complexity.
引用
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页数:26
相关论文
共 48 条
[1]  
Abadi M, 2016, PROCEEDINGS OF OSDI'16: 12TH USENIX SYMPOSIUM ON OPERATING SYSTEMS DESIGN AND IMPLEMENTATION, P265
[2]  
[Anonymous], 2013, Int. J. Remote Sens. Appl
[3]  
[Anonymous], P 2008 INT RAD S WRO
[4]  
[Anonymous], COMMUN ACM, DOI [DOI 10.1145/3065386, 10.1145/3065386]
[5]  
[Anonymous], 2017, PROC CVPR IEEE, DOI DOI 10.1109/CVPR.2017.632
[6]  
[Anonymous], IEEE T PATTERN ANAL
[7]  
[Anonymous], 2012, IEEE Trans. Geosci. Remote Sens
[8]  
[Anonymous], PROC CVPR IEEE
[9]  
[Anonymous], 2015, PROC CVPR IEEE
[10]  
[Anonymous], IEEE T PATTERN ANAL