Waveform Optimization of CS-MIMO Radar Based on Gradient Descent Algorithm

In the past few years, the adaptive waveform design algorithm has emerged; it improves multiple input and multiple output (MIMO) radar performance by designing the transmitting radar waveforms to adapt to the changes of targets, noise, and clutter in the environment. A MIMO radar waveform design method based on compressed sensing is proposed by using the gradient descent method. Considering the prior information on noise and interference in the environment, the compressed sensing (CS) MIMO model is designed, and the objective function is to maximize the signal-to-interference-plus-noise-ratio (SINR) of the radar. Then the method of joint optimization of the transmit signal and filter is used to obtain the transmit waveform with better detection performance. Compared with the conventional MIMO radar, the optimized waveform of CS-MIMO can greatly reduce the amount of data. Computer simulation shows that the detection performance of the optimized waveform is better than that of the traditional linear frequency modulated (LFM) waveform.