长江信息通信2024,Vol.37Issue(8) :48-51.DOI:10.20153/j.issn.2096-9759.2024.08.015

基于随机森林的无人机信号自动化识别算法

Automatic Recognition Algorithm of UAV Signal Based on Random Forest

李浩坤 蒋浩晨 周良臣
长江信息通信2024,Vol.37Issue(8) :48-51.DOI:10.20153/j.issn.2096-9759.2024.08.015

基于随机森林的无人机信号自动化识别算法

Automatic Recognition Algorithm of UAV Signal Based on Random Forest

李浩坤 1蒋浩晨 1周良臣1
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作者信息

  • 1. 成都信息工程大学,四川成都 610225
  • 折叠

摘要

针对无人机在低信噪比条件下的应用,提出了一种基于随机森林的无人机信号自动识别算法.首先,分析了无人机信号的时域和频域特性;然后,提出了针对无人机信号4种的特征参量构成的特征向量作为数据集,并优化了特征参量的计算方法;最后,设计了随机森林分类识别模型.仿真结果表明,该算法针对实采的无人机信号在信噪比为6 dB时可达到90%的识别率,具备较强的鲁棒性和低信噪比环境适应性,同时算法复杂度低,模型参数少,为后续的硬件实现提供了现实依据.

Abstract

An Automatic recognition algorithm of UAV signal based on Random Forest(RF)is proposed for theap plication under low signal-to-noise ratio(SNR).Firstly,the time domain and frequency domain characteristics of UAV signal are analyzed.Then,the feature vector composed of 4 kinds of characteristic parameters of UAV signal is presented as the data set,and the calcula-tion method of the characteristic parameters is optimized.Finally,a RF classification recognition model is designed.The simulation results show that the algorithm can achieve 90%recognition rate when the SNR is 6 dB,which has strong robustness and low SNR environment adaptabili-ty.Meanwhile,the algorithm complexity is low and the model parameters are few,which pro-vides a realistic basis for the subsequent hardware implementation.

关键词

无人机/信号识别/特征参量/随机森林

Key words

UAV/Signal recognition/Characteristic parameter/Random forest

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出版年

2024
长江信息通信
湖北通信服务公司

长江信息通信

影响因子:0.338
ISSN:2096-9759
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