Joint waveform design of cognitive radar based on LSTM network in the presence of signal-dependent interference

Abstract

Waveform design is a key component of cognitive radar. However, waveforms designed using a single criterion have difficulty meeting the multi-working mode of radar. We present a joint waveform design method in the presence of signal-dependent interference based on a long short term memory network. The proposed method combines characteristics of mutual information (MI) and signal to interference-plus-noise-ratio (SINR) criteria and achieves a smooth trade-off between them. The minimum mean square error (MMSE) method is set as a comparison to prove the enhanced capabilities in detection and recognition. Here, we initiate a final recognition rate indicator of radar to measure the radar’s comprehensive performance. As a result, compared with the MI criterion, SINR criterion, and MMSE method, to use as a transmission signal, the proposed paradigm increased the final recognition rate by 4.08%, 6.89%, and 5.25%, respectively, verifying the effectiveness of the proposed method.