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Volume 42 Issue 10
Oct.  2020
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Liang ZHANG, Guohong WANG, Xiangyu ZHANG, Siwen LI. Fast-slow Time Domain Joint Processing Suppressing Smeared Spectrum Jamming[J]. Journal of Electronics & Information Technology, 2020, 42(10): 2508-2515. doi: 10.11999/JEIT190734
Citation: Liang ZHANG, Guohong WANG, Xiangyu ZHANG, Siwen LI. Fast-slow Time Domain Joint Processing Suppressing Smeared Spectrum Jamming[J]. Journal of Electronics & Information Technology, 2020, 42(10): 2508-2515. doi: 10.11999/JEIT190734

Fast-slow Time Domain Joint Processing Suppressing Smeared Spectrum Jamming

doi: 10.11999/JEIT190734
Funds:  The National Natural Science Foundation of China (61731023, 61701519, 61671462), Taishan Scholar Climbing Plan
  • Received Date: 2019-09-24
  • Rev Recd Date: 2020-02-12
  • Available Online: 2020-03-03
  • Publish Date: 2020-10-13
  • 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.
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