Radar signal recognition based on modified semi-supervised SVM algorithm
Ying Fu, Wang Xing · 2017
To improve the accuracy rate of radar signal recognition in increasingly sophisticated electronic countermeasure environment, a modified Semi-supervised SVM (S3VM) algorithm based on HSS (Heuristic Sampling Search) is put forward. Aiming at disadvantages of traditional semi-supervised support vector machines, the classifier constructed by modified S3VM is used for classifying the radar signal, then the recognition of tested samples are finished. Modified S3VM try to exploit multiple representative large-margin low-density separators by using HSS, it works out the shortcomings of S3VM efficiently, such as low classification accuracy rate and unstable classification performance. The experiment results show the accuracy rate is improved obviously by using the algorithm in radar signal recognition.