Study on radar emitter recognition signal based on rough sets and RBF neural network

With the development of new type and use of radar emitter, it is more difficult to recognize radar emitter signal. The radar emitter signal information is converted into discrete value in this paper. The attribute of radar emitter signal is reduced and the decision rules are extracted based on rough sets. Then the cluster center of radial basis function (RBF) neural network is gain by rough K-means cluster method. The RBF neural network is constructed with the help of decision rules extracted from information table. The simulation result shows this radar emitter recognition model base on rough sets and RBF neural network can cut down the redundant attribute, lessen the neural network structure and recognize radar emitter signal effectively.