Distributed Feature Reduction Signal Sorting Algorithm

Abstract

With the development of science and technology, modern war has changed from traditional mechanized war to electronic war. Electronic warfare has become the mainstream combat mode in modern war. At present, the electromagnetic environment is very chaotic and complex, the pulse density increases rapidly, and the pulse modulation mode is complex and changeable. In order to deal with the low efficiency of traditional methods in complex electromagnetic environment, a distributed feature reduction signal sorting method is proposed. Firstly, attribute entropy regularization is added to the objective function, and different weights are given to different features. Secondly, the feature reduction process is added to select which dimension of features to be discarded by setting the threshold. Each iteration of the algorithm will update the membership matrix, cluster center and feature weight matrix until the termination conditions is satisfied. Simulation results show that the algorithm can reduce the number of iterations and time, and improve the accuracy of radar signal sorting results by reducing the number of features.