Waveform design and high-resolution imaging of cognitive radar based on compressive sensing

We introduce the compressive sensing (CS) theory for waveform design of cognitive radar, and then propose an algorithm for the high-resolution radar signal waveform and its corresponding imaging method based on the sparse orthogonal frequency division multiplexing-linear frequency modulation (OFDM-LFM) signal. We first present the principle of spectrum synthesis and high-resolution imaging based on OFDM-LFM signals. Then, we propose the spectrum-sparse waveform design criterion and the reconstruction algorithm for a high-resolution range profile (HRRP) based on CS. Based on this, we analyze in detail the relationship between the scattering characteristics of the target and the parameters of the designed signal, and we construct the feedback of the target characteristics on the waveforms. Therefore, the "cognitive" function of radar can be achieved by adaptively adjusting the waveform with the target characteristics. Simulations are given to validate the effectiveness of the proposed algorithm.