A Kernel Density Window Clustering Algorithm for Radar Pulses

As radar signal environments become denser and more complex, the capability of high-speed and accurate signal analysis is required for ES (electronic warfare support) system to identify individual radar signals at real-time. In this paper, we propose the novel clustering algorithm of radar pulses to alleviate the load of signal analysis process and support reliable analysis. The proposed algorithm uses KDE (kernel density estimator) and its CDF (cumulative distribution function) to compose clusters considering the distribution characteristics of pulses. Simulation results show the good performance of the proposed clustering algorithm in clustering and classifying the emitters.