Fast-slow Time Domain Joint Processing Suppressing Smeared Spectrum Jamming

被引：0
|
作者：
Zhang L. [1 ,2 ]
Wang G. [1 ]
Zhang X. [1 ]
Li S. [1 ]
机构：
[1] Naval Aviation University, Yantai
[2] Unit 94326 of the PLA, Jinan
来源：
Dianzi Yu Xinxi Xuebao/Journal of Electronics and Information Technology | 2020年 / 42卷 / 10期
基金：
中国国家自然科学基金;
关键词：
Fast-slow time domain; Jamming cancellation; Joint processing; SMeared SPectrum (SMSP) jamming;
D O I：
10.11999/JEIT23_dzyxxxb-42-10-2508
中图分类号：
学科分类号：
摘要：
The existing SMeared SPectrum (SMSP) jamming suppression algorithms take a jammed echo whose length equal to radar transmitting signal as the processing object and do not involve the whole echo within the coherent processing interval. For this problem, a jamming suppression algorithm based on fast and slow time domain joint processing is proposed under the background of Linear Frequency Modulation (LFM) coherent radar countering SMSP jamming. The time and frequency domain characteristics of SMSP are studied and the effect on coherent radar is analyzed on the condition of self screening jamming. On this basis, four processing steps are designed to suppress the SMSP jamming. Firstly, the jamming fast time location is estimated by calculating the differential entropy of slow time signal. Secondly, the real jamming parameter is found based on the maximum correlation coefficient criterion. Then the jamming signals are reconstructed using Biorthogonal Fourier Transform. Finally, the SMSP jamming is suppressed by cancellation. The simulation results show that the proposed algorithm model is highly consistent with the actual radar processing flow, and the efficiency is further verified through algorithms comparison. © 2020, Science Press. All right reserved.
引用
收藏
页码：2508 / 2515
页数：7
相关论文
共 17 条
  • [1] SPARROW M J, CIKALO J., ECM techniques to counter pulse compression radar, (2006)
  • [2] ZHAO Yang, SHANG Chaoxuan, HAN Zhuangzhi, Et al., Fractional Fourier transform and compressed sensing adaptive countering smeared spectrum jamming, Journal of Electronics&Information Technology, 41, 5, pp. 1047-1054, (2019)
  • [3] LU Yunlong, LI Ming, CAO Runqing, Et al., Jointing time-frequency distribution and compressed sensing for countering smeared spectrum jamming, Journal of Electronics&Information Technology, 38, 12, pp. 3275-3281, (2016)
  • [4] LI Xin, WANG Chunyang, YUAN Hui, Et al., SMSP jamming suppression method based on jamming reconstruction and kurtosis maximum, Journal of Beijing University of Aeronautics and Astronautics, 44, 6, pp. 1176-1184, (2018)
  • [5] YIN Hongwei, LI Guolin, LU Cuihua, An algorithm of deception jamming suppression based on complex-value Blind Source Separation, Journal of Shanghai Jiaotong University, 49, 10, pp. 1564-1569, (2015)
  • [6] LI Fei, LI Guolin, NIAN Penglei, Radar signal deception jamming suppressing based on Blind Source Separation, Journal of Naval Aeronautical and Astronautical University, 30, 5, pp. 424-428, (2015)
  • [7] ADAMY D L., EW 104: EW Against A New Generation of Threats, pp. 60-64, (2015)
  • [8] HUO Weibo, HUANG Yulin, PEI Jifang, Et al., Ship detection from ocean SAR image based on local contrast variance weighted information entropy, Sensors, 18, 4, (2018)
  • [9] GOKSU H., Ground moving target recognition using log energy entropy of wavelet packets, Electronics Letters, 54, 4, pp. 233-235, (2018)
  • [10] ZHANG Shuanghui, LIU Yongxiang, LI Xiang, Autofocusing for sparse aperture ISAR imaging based on joint constraint of sparsity and minimum entropy, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 10, 3, pp. 998-1011, (2017)
12