With the application of modern communication technology in aerospace widely,how to avoid the hazard of the jamming signals to air traffic in the airport environment has become the focus issue which is concerned widely. In this paper,a novel method combining the spectral correlation features and support vector machine(SVM)based on the jamming signals detection model for avoiding the outside signals interference to aeronautical communications in the airport environment.We extract cyclostationary characteristic parameters as training samples and testing samples,then utilize a nonlinear SVM to detect the jamming signals.Test result shows that our algorithm achieves a good detection accuracy of classification and performance.%随着现代通信技术在航空领域的广泛应用，在机场环境下如何避免各干扰信号对航空通信的危害成为人们广泛关注的焦点问题。本文基于机场环境下的信号感知模型，提出一种基于支持向量机（SVM）和谱相关性的干扰信号感知算法，有效避免了外界信号对航空通信信号的干扰。该算法采用信号循环谱进行分析的方法提取特征向量，进而结合SVM分类器对航空干扰信号进行检测。仿真结果表明，本文算法对干扰信号具有较高的分类检测精度和良好的识别性能。
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