Volume 48 Issue 10
Oct.  2022
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LI Liyuan, LI Ping, LI Guolin, et al. Classification of plateau shrub echo signal based on bispectrum analysis[J]. Journal of Beijing University of Aeronautics and Astronautics, 2022, 48(10): 2070-2078. doi: 10.13700/j.bh.1001-5965.2021.0075(in Chinese)
Citation: LI Liyuan, LI Ping, LI Guolin, et al. Classification of plateau shrub echo signal based on bispectrum analysis[J]. Journal of Beijing University of Aeronautics and Astronautics, 2022, 48(10): 2070-2078. doi: 10.13700/j.bh.1001-5965.2021.0075(in Chinese)

Classification of plateau shrub echo signal based on bispectrum analysis

doi: 10.13700/j.bh.1001-5965.2021.0075
Funds:

National Natural Science Foundation of China 61871414

Foundation Strengthening Project 2019-JCJQ-ZD-324

More Information
  • Corresponding author: LI Ping, E-mail: liping85@bit.edu.cn
  • Received Date: 08 Feb 2021
  • Accepted Date: 23 Mar 2021
  • Publish Date: 30 Mar 2021
  • The echo signal of the target is the most important way for radio fuze to obtain target information. This research employs bispectral analysis to examine the echo properties of terahertz wave at different heights of plateau in shrub terrain in order that the front-end of terahertz band fuze can be implemented into the plateau battle field in the future and adapt to the different landform environments of the plateau. In order to reduce the classification time, the bispectral data is integrated to obtain the bispectral slice features of the actual signal, and then the k-nearest neighbor algorithm is used for classification. Empirical mode decomposition (EMD) is used to extract the intrinsic mode function features of the original data, and the classification results are compared with the previous group. Through a series of data classification, the results show that using one-dimensional integrated bispectral information can effectively extract the features of 2 m, 3 m, 4 m, 5 m from the ground and classify them, empirical mode decomposition can also effectively improve the success rate of classification, the success rate can reach more than 90%.

     

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