关键词: 雷达信号识别, 半监督支持向量机, 分类决策面, 模糊函数, 奇异值分解

Abstract: To improve the accuracy rate of radar signal recognition in increasingly sophisticated electronic countermeasure environment, an improved S3VM algorithm based on HSS（Heuristic Sampling Search） is put forward. According to theory of ambiguity function, through SVD of radar signal recognition’ ambiguity function, it extracts its singular value as characteristic parameters; aiming at disadvantages of traditional semi-supervised support vector machines, the classifier constructed by improved S3VM is used for classifying the radar signal, then the recognition of tested samples is finished. Improved S3VM try to exploit multiple representative large-margin low-density separators by using HSS. It works out the shortcomings on S3VM efficiently, such as low classification accuracy and unstable classification performance. The experimental results show that accuracy rate is improved obviously by the algorithm in radar signal recognition.

Key words: radar signal recognition, semi-supervised Support Vector Machine（SVM）, separators, ambiguity function, Singular Value Decomposition（SVD）