A Unified Method for Deinterleaving and PRI Modulation Recognition of Radar Pulses Based on Deep Neural Networks

In the modern electronic warfare signal environment, multiple radar signals of high density are mixed and received, separating them into for each emitter is an essential step identification. Each has its own pulse repetition interval (PRI), which a key parameter deinterleaving trains. The PRI modulated in various forms depending on purpose operation, analyzing mean modulation type core processing. Many existing papers have tried separate independent approaches recognition. However, many distortions unintentionally generated process extracting train using estimated through This degrades recognition performance. this paper, we propose unified method pulses deep learning-based multitasking learning. simulation results demonstrate good performance proposed recognition, compared to conventional method, prove that robust noisy environments.