Through the study of ground-to-air communication interference signals which are collected by different monitoring equipments of different terrain and find that its audio signals can be regarded as the recognized object of ground-to-air communication interference signals.Since the feature of audio signals is based on short time domain so that it is not used directly in recognition.Therefore,we propose that K-means clustering algorithm is used to structure the feature extraction of ground-to-air communication interference audio signals,and the SVM algorithm of traversal selected parameters are regarded as a classifier to recognize the interference of ground-to-air communications audio signals.Experimental results prove that this method can well show the statistical characteristics of audio signals and has a high recognition rate for different ground-to-air communication audio interference signals in a shot time.%通过对设置在不同地形的监测设备所采集的地空通信信号研究发现,其音频信号可作为识别地空通信干扰信号的研究对象,但音频信号特征通常是基于短时间域上的,无法直接应用在识别过程中.故提出利用K-均值聚类算法构建地空通信干扰音频信号的特征集合,并将通过遍历选择参数的支持向量机作为分类器用于地空通信干扰音频信号识别.实验表明,该方法可以很好地表现出音频信号的统计特性,快速、高效地识别出不同的地空通信干扰信号.
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