Operation Mode Recognition of Airborne Radar Based on Multi-Feature Fusion RS-ConvNet

Abstract

Modern warfare has entered the era of information and networking, where electronic warfare (EW) is of vital importance. Operation mode recognition occupies an important po-sition in EW, while the overlapping waveform parameters of airborne radar operation modes make it difficult to accom-plish the recognition task in complex electromagnetic environments' especially under low signal-to-noise ratio (SNR) regions. Analyzing the time-sequential regularity of radar pulse parameters and intermediate frequency (IF) sampling signals, this paper designs a novel representation of operation modes, and proposes a multi-feature residual-and-shrinkage ConvNet (RS-ConvNet) with an attention mechanism to iden-tify multiple air-to-air modes. Simulation results show the proposed method has superior performance under low SNRs.