Computer Science ›› 2021, Vol. 48 ›› Issue (7): 225-232.doi: 10.11896/jsjkx.200500091

• Computer Graphics & Multimedia • Previous Articles     Next Articles

UAV Sound Recognition Algorithm Based on Deep Learning

XU Hao, LIU Yue-lei   

  1. School of Electronics and Control Engineering,Chang’ an University,Xi’ an 710016,China
  • Received:2020-05-20 Revised:2020-08-23 Online:2021-07-15 Published:2021-07-02
  • About author:XU Hao,born in 1998,undergraduate.His main research interests include deep learning and industrial automation.(2017900299@chd.edu.cn)
    LIU Yue-lei,born in 1986,Ph.D,lectu-rer.His main research interests include intelligent optimization algorithm and deep learning.

Abstract: Deep learning has demonstrated its superior performance and broad development prospect in image recognition and sound processing.It is of certain significance for the UAV detection system established in no-fly zone to use deep learning method to judge the sound signal of UAV.In order to obtain better detection effect,the representative feature extraction and classification methods are listed at first,and their advantages and disadvantages are analyzed.Then,a method of data processing is proposed to expand the number of available samples.At the same time,different combinations of deep learning network training samples are used in the experiment.Finally,the confounding matrix method is used to evaluate the experimental results of different SNR models,filtering limits,fitting degrees,neural network combinations and cross-model recognition.The results show that reducing the sound intensity of the UAV can improve the recognition distance of the system.By using MFCC to extract the sound features,the samples classified by the fully connected neural network have a longer identification radius and a lower misjudgment rate.

Key words: Deep learning, Obfuscation matrix, Sound detection, Unmanned aerial vehicle

CLC Number: 

  • TP391
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