Key Radar Signal Sorting and Recognition Method Based on Clustering Combined with PRI Transform Algorithm

Abstract

In this paper, we investigate the problem of key radar signal sorting and recognition in electronic intelligence (ELINT). Our major contribution is the development of a combined approach based on clustering and pulse repetition interval (PRI) transform algorithm, to solve the problem that the traditional methods based on pulse description word (PDW) were not exclusively targeted at tiny particular signals and were less time-efficient. We achieve this in three steps: firstly, PDW presorting is carried out by the DBSCAN (Density-Based Spatial Clustering of Applications with Noise) clustering algorithm, and then PRI estimates of each cluster are obtained by the PRI transform algorithm. Finally, by judging the matching between various PRI estimates and key targets, it is determined whether the current signal contains key target signals or not. Simulation results show that the proposed method should improve the time efficiency of key signal recognition and deal with the complex signal environment with noise interference and overlapping signals.