Radar Signal Sorting Method Based on Online Kernel Clustering

This paper presents an Online Kernel Clustering with Parameters Adaptation(OKCPA),and applies it to the unknown radar emitter signal sorting.OKCPA algorithm which is based on Support Vector Machine(SVM),uses the kernel trick to map the dates into the high-dimensional linear space,and uses stochastic gradient descent to update the boundary function,the step size and penalization parameter is updated with the dates coming,which accelerates the speed of clustering sorting.Simulation results show that this method has higher clustering sorting speed and higher sorting accuracy.