Radar Signals Intrapulse Modulation Recognition Using Phase-Based STFT and BiLSTM

The goal of Radar Emitter Recognition (RER) is to extract the features a received emitter signal. It has become critical issue as new radar types are emerging and electromagnetic environment becoming more dense complex. Deep Neural Networks (DNNs) have recently proven effective for identification, however, recognition phase-coded waveforms at low Signal Noise Ratio (SNR) remains challenge. In this paper, novel phase-based RER approach using Short Time Fourier Transform (STFT) Bidirectional Long Term Memory (BiLSTM) proposed while enhancing ability learning from noisy signals. phase spectrum signals analyzed in contrast amplitude used state-of-the-art approaches literature. derived directly provided an input BiLSTM architecture. A fully connected layer follows layer. Finally, softmax classifier employed accomplish task. Six distinct degraded by Additive White Gaussian (AWGN) with SNRs ranging -8dB 8dB simulated. suggested method research involves simple pre-processing exhibits overall accuracy than 90% SNR -2dB.