Journal of Systems Engineering and Electronics ›› 2022, Vol. 33 ›› Issue (6): 1151-1158.doi: 10.23919/JSEE.2022.000129


Mainlobe jamming suppression via improved BSS method for rotated array radar

Hailong ZHANG1,2(), Gong ZHANG1,*(), Biao XUE1(), Jiawen YUAN1()   

  1. 1 Key Laboratory of Radar Imaging and Microwave Photonics, Ministry of Education, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
    2 Nanjing Marine Radar Institute, Nanjing 211153, China
  • Received:2021-07-13 Accepted:2022-06-28 Online:2022-12-18 Published:2022-12-24
  • Contact: Gong ZHANG;;;
  • About author:
    ZHANG Hailong was born in 1989. He received his M.S. degree in information and communication engineering from the School of Electronic and Optical Engineering, Nanjing University of Science and Technology, Nanjing, China, in 2015. He is currently a doctoral student in the College of Electronics and Information Engineering, Nanjing University of Aeronautics and Astronautics. His main research interests are mainlobe jamming suppression, inverse aperture radar, and time-frequency analysis. E-mail:

    ZHANG Gong was born in 1964. He received his Ph.D. degree in electronic engineering from Nanjing University of Aeronatics and Astronautics (NUAA), Nanjing, China, in 2002. From 1990 to 1998, he was a member of the Technical Staff at No.724 Institute, China Shipbuilding Industry Corporation, Nanjing. Since 1998, he has been with the College of Electronic and Information Engineering, NUAA, where he is currently a professor. He is a member of the Committee of Electromagnetic Information, Chinese Society of Astronautics and a senior member of the Chinese Insitute of Electronics. His research interests include radar signal processing and classification recognition. E-mail:

    XUE Biao was born in 1995. He received his B.S. degree in electronic and information engineering from Nanjing University of Aeronautics and Astronautics, Nanjing, China, in 2019. He is currently pursuing his Ph.D. degree in communication and information system from Nanjing University of Aeronautics and Astronautics, Nanjing, China. His research interest include multiple input multiple output synthetic aperture radar and near-field millimeter wave synthetic aperture radar. E-mail:

    YUAN Jiawen was born in 1994. She received her M.S. degree in instrumentation engineering from Nanjing University of Aeronautics and Astronautics, Nanjing, China, in 2018. She is currently a Ph.D. candidate at Nanjing University of Aeronautics and Astronautics. Her research interests include array signal processing and direction-of-arrival. E-mail:
  • Supported by:
    This work was supported by the National Natural Science Foundation of China (62271255;61871218;61801211), the Fundamental Research Funds for the Central Universities (3082019NC2019002;NG2020001;NP2014504), the Open Research Fund of State Key Laboratory of Space-Ground Integrated Information Technology (2018_SGIIT_KFJJ_AI_03), the Funding of Postgraduate Research Practice & Innovation Program of Jiangsu Province (KYCX200201), and the Open Research Fund of the Key Laboratory of Radar Imaging and Microwave Photonics (Nanjing University of Aeronautics and Astronautics), Ministry of Education (NJ20210001).


This study deals with the problem of mainlobe jamming suppression for rotated array radar. The interference becomes spatially nonstationary while the radar array rotates, which causes the mismatch between the weight and the snapshots and thus the loss of target signal to noise ratio (SNR) of pulse compression. In this paper, we explore the spatial divergence of interference sources and consider the rotated array radar anti-mainlobe jamming problem as a generalized rotated array mixed signal (RAMS) model firstly. Then the corresponding algorithm improved blind source separation (BSS) using the frequency domain of robust principal component analysis (FD-RPCA-BSS) is proposed based on the established rotating model. It can eliminate the influence of the rotating parts and address the problem of loss of SNR . Finally, the measured peak-to-average power ratio (PAPR) of each separated channel is performed to identify the target echo channel among the separated channels. Simulation results show that the proposed method is practically feasible and can suppress the mainlobe jamming with lower loss of SNR.

Key words: mainlobe jamming, blind signal separation (BSS), robust principal component analysis (RPCA), peak to average power ratio (PAPR)