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Volume 41 Issue 7
Jul.  2019
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Yilin WANG, Shilong MA, Nan ZOU, Guolong LIANG. Detection of Unknown Line-spectrum Underwater Target Using Space-time Processing[J]. Journal of Electronics & Information Technology, 2019, 41(7): 1682-1689. doi: 10.11999/JEIT180796
Citation: Yilin WANG, Shilong MA, Nan ZOU, Guolong LIANG. Detection of Unknown Line-spectrum Underwater Target Using Space-time Processing[J]. Journal of Electronics & Information Technology, 2019, 41(7): 1682-1689. doi: 10.11999/JEIT180796

Detection of Unknown Line-spectrum Underwater Target Using Space-time Processing

doi: 10.11999/JEIT180796
Funds:  The National Key R&D Plan(2016YFC1400101), The National Natural Science Foundation of China (11504064), Heilongjiang Provience Scientific Research Foundation for Returned Scholars (JJ2016LX0051)
  • Received Date: 2018-08-16
  • Rev Recd Date: 2019-02-26
  • Available Online: 2019-03-23
  • Publish Date: 2019-07-01
  • For the passive detection of underwater line-spectrum target, the information such as the azimuth, frequency and the number of the line-spectrum signals is usually unknown, and the line-spectrum detection performance is affected by broadband interferences and noise. For this issue, a Space-Time Joint Detecion (STJD) method of detecting the unknown line-spectrum target by space-time domain processing is proposed. Firstly, a space-time filter that autonomously matches the unknown line-spectrum signals is constructed to filter out the broadband interferences and noise. Secondly, the conventional frequency domain beamforming is performed on the filtered signals, and then a space-time two-dimensional beam output with relatively pure line-spectrum spectral peaks is obtained. The line-spectrum signals are extracted from the space-time two-dimensional beam output, and the spatial spectrum is calculated using the extracted line-spectrum information. Then, the detection of the line-spectrum target is realized. Theoretical derivation and simulation results verify that the proposed method performs the spatiotemporal filtering on the unknown line-spectrum signals in the minimum mean square error sense, and fully utilizes the line-spectrum information for the passive detection of underwater line-spectrum target. Compared with the existing line-spectrum target detection methods utilizing the line-spectrum features, the proposed method requires lower Signal to Noise Ratio (SNR), and has better detection performance under the complex multi-target multi-spectrum-line conditions.
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