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Volume 43 Issue 11
Nov.  2021
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Xuejie BI, Juan HUI, Anbang ZHAO, Biao WANG, Lin MA, Xiaoman LI. Underwater Target Depth Classification Method Based on Vertical Acoustic Intensity Flux[J]. Journal of Electronics & Information Technology, 2021, 43(11): 3237-3246. doi: 10.11999/JEIT201045
Citation: Xuejie BI, Juan HUI, Anbang ZHAO, Biao WANG, Lin MA, Xiaoman LI. Underwater Target Depth Classification Method Based on Vertical Acoustic Intensity Flux[J]. Journal of Electronics & Information Technology, 2021, 43(11): 3237-3246. doi: 10.11999/JEIT201045

Underwater Target Depth Classification Method Based on Vertical Acoustic Intensity Flux

doi: 10.11999/JEIT201045
Funds:  The Scientific Research Staring Foundation of Jiangsu University of Science and Technology (1032932003, 1032931907), The National Natural Science Foundation of China (11574120, 12004143), The Science and Technology Foundation of State Key Laboratory (6142108190907), The Open Foundation of Key Laboratory of Marine Intelligent Equipment and System, Ministry of Education (MIES-2020-09)
  • Received Date: 2020-12-14
  • Rev Recd Date: 2021-06-04
  • Available Online: 2021-08-18
  • Publish Date: 2021-11-23
  • The existing target depth classification methods based on acoustic interference structure characteristics have a limited frequency range, and are only suitable for the case where target frequency can excite first two modes. Aiming to this problem, a novel target depth classification algorithm based on matching field processing is proposed in this paper. The proposed algorithm uses the reactive component of vertical complex acoustic intensity as matching variable to estimate target depth. The rough estimation results of target depth can be used to assist the binary classification of target depth. This method is suitable for the case where target frequency can excite first three modes, so as to expand the frequency range of the algorithm. The feasibility and robustness of the algorithm are verified by simulation results. The influence of mismatched sea environmental parameters on algorithm performance are also analyzed. The proposed algorithm has high accuracy and robustness.
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