Progress in Radar Emitter Signal Deinterleaving

Abstract

Radar emitter signal deinterleaving is a key technology for radar signal reconnaissance and an essential part of battlefield situational awareness. This paper systematically sorts out the mainstream technology of radar emitter signal deinterleaving. It summarizes the main research progress in radar emitter signal deinterleaving from three directions: interpulse modulation characteristics-based, intrapulse modulation characteristics-based, and machine learning-based research. Particularly, this paper focuses on explaining the principle and technical characteristics of the latest deinterleaving technology, such as neural network-based and data stream clustering-based techniques. Finally, the shortcomings of the current radar emitter deinterleaving technology are summarized, and the future trend is predicted.

Keywords

• radar emitter
• pulse deinterleaving
• pulse stream
• machine learning
• deep learning
• data stream clustering