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Journal of Projectiles, Rockets, Missiles and Guidance >

2019 , Vol. 39 >Issue 5: 81 - 84

DOI: https://doi.org/10.15892/j.cnki.djzdxb.2019.05.019

Application of Bi-spectral Feature and Depth Learning in Signal Modulation Recognition

  • LI Nan
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  • School of Information Engineering, Xijing University, Xi’an 710123, China

Received date: 2018-08-20

  Online published: 2025-05-12

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Abstract

The diversity of modulation patterns of emitter signals makes it difficult to identify emitter accurately. The characteristics of bi-spectral diagonal slice can clearly reflect the characteristics of emitter signals, and the deep neural network learning can process the signal sample big data. Applying bi-spectral feature and depth neural network to signal modulation recognition can extract the essential feature of emitter signal and improve the correct recognition rate of emitter modulation signal. The simulation results show that the bi-spectral feature can better reflect the signal characteristics than other recognition algorithms, and the depth learning model has a higher recognition rate.

Key words： signal modulation recognition; bi-spectral feature; depth neural network; SNR

Cite this article

LI Nan . Application of Bi-spectral Feature and Depth Learning in Signal Modulation Recognition[J]. Journal of Projectiles, Rockets, Missiles and Guidance, 2019 , 39(5) : 81 -84 . DOI: 10.15892/j.cnki.djzdxb.2019.05.019

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