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Volume 42 Issue 3
Mar.  2020
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Xiangdong HUANG, Yuxuan SHAN, Jian WANG. High-performance Co-prime Spectral Analysis Method Based on Parallelled All-phase Point-pass Filtering[J]. Journal of Electronics & Information Technology, 2020, 42(3): 613-620. doi: 10.11999/JEIT190317
Citation: Xiangdong HUANG, Yuxuan SHAN, Jian WANG. High-performance Co-prime Spectral Analysis Method Based on Parallelled All-phase Point-pass Filtering[J]. Journal of Electronics & Information Technology, 2020, 42(3): 613-620. doi: 10.11999/JEIT190317

High-performance Co-prime Spectral Analysis Method Based on Parallelled All-phase Point-pass Filtering

doi: 10.11999/JEIT190317
Funds:  Qingdao National Laboratory for Marine Science and Technology 2016 Open Fund (QNLM2016OPR0411), The National Natural Science Foundation of China (61671012), 973 Program (6133190102)
  • Received Date: 2019-05-05
  • Rev Recd Date: 2019-10-31
  • Available Online: 2019-11-11
  • Publish Date: 2020-03-19
  • In order to completely remove the spurious-peak side effect in the undersampling based wide-band spectral analysis, this paper proposes a high-performance co-prime spectral analysis method based on paralleled all-phase point-pass filtering. On basis of a deep analysis on the mechanism of the classical co-prime spectral analysis, it is discovered that this spurious-peak side effect arises from those redudant overlapping boundary-bands related to distinct polyphase filtering branches between the up data path and the down data path. Therefore, through replacing the prototype filters in the classical co-prime spectral analysis by the all-phase point-pass filtering banks, a novel co-prime analysis dataflow is derived based on paralleled all-phase point-pass filtering. Both theoretic analysis and numerical simulation show that the proposed spectral analysis method achieves remarkable performance improvement: it can not only completely remove the spurious-peak side effect, but also obtain a much higher spectral resolution than the classical co-prime analysis, thereby possessing another merit of distinguishing dense spectral components. The proposed spectral analysis method possesses vast potentials in the software-defined radio, radar detection, passive positioning and marine wireless communication etc.

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