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Volume 42 Issue 2
Feb.  2016
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Journal of Beijing University of Aeronautics and Astronautics  > 2016  >  42(2): 375-382.
LI Jingqing, FENG Cunqian, ZHANG Dong, et al. Group-target signal separation based on time-frequency enhancement and total variation[J]. Journal of Beijing University of Aeronautics and Astronautics, 2016, 42(2): 375-382. doi: 10.13700/j.bh.1001-5965.2015.0110(in Chinese)
Citation: LI Jingqing, FENG Cunqian, ZHANG Dong, et al. Group-target signal separation based on time-frequency enhancement and total variation[J]. Journal of Beijing University of Aeronautics and Astronautics, 2016, 42(2): 375-382. doi: 10.13700/j.bh.1001-5965.2015.0110(in Chinese)
shu

Group-target signal separation based on time-frequency enhancement and total variation

doi: 10.13700/j.bh.1001-5965.2015.0110
  • 1.

    Air and Missile Defense College, Air Force Engineering University, Xi'an 710051, China

  • 2. Collaborative Innovation Center of Information Sensing and Understanding, Xi'an 710077, China

  • Received Date: 05 Mar 2015
  • Publish Date: 20 Feb 2016
    Abstract
  • To solve the problems of weak time-frequency orthogonality and the complexity of separation on group-target echo acquired by low-resolution radar, a group-target signal separation algorithm based on total variation (TV) is proposed as a precondition of time-frequency enhancement. The necessity of time-frequency enhancement is indicated by analyzing the sparsity of group-target signal on the basis of rotating model. According to the differences between the micro-motion periods of different sub-targets, the multi-view group-target echoes are respectively enhanced in time-frequency domain by two-way delay processing. Ultimately, on the basis of the distribution property of energy region for group-target echo, the group-target echo is separated with high fidelity via the regional TV fusion method in conjunction with principal component analysis. The simulation results validate that the algorithm can be used to separate and extract weak signals from some strong signals more easily when the sampling rate is lower. And the fusion resolution of the proposed algorithm is also superior to the fusion method based on TV norm.

     

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