Recognition Method of Radar Emitter Based on High Dimensional Repetition Frequency Feature
In this paper,a radar emitter recognition method based on decision tree is proposed by extracting and utilizing the high-dimensional features of radar pulse interval.The vector formed by adjacent pulse interval is taken as the high-dimensional feature of the pulse to enhance the separability between different radar signals.Such feature is extracted from the pulse column by clustering method,and then the feature is formed into a feature vector to show the integrity of the feature.Then,a decision tree classification model is constructed based on the feature vector.Finally,the model is used to identify the unknown radar pulse train.Simulation results show that the new method has significant advantages over the traditional method in different data volume and data noise sce-narios.
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