Waveform Design for Compressive Sensing Radar Based on Minimizing the Statistical Coherence of the Sensing Matrix

To enhance the performance of Compressive Sensing Radar (CSR) target information extraction ability, a CSR optimal waveform design method based on minimizing the statistical coherence of the sensing matrix is proposed. First, a universal CSR model is established and waveform optimization object function minimizing the coherence of the sensing matrix is derived. Then, the Genetic Algorithm (GA) is employed to solve this problem with polyphase coded signal as an example code. The optimized waveform makes the sub-sensing matrix orthogonality degree approximately optimal. Comparing with traditional waveforms, this waveform reduces effectively the target information estimation error, increases the permissible upper bound of target detection number, and enhances the accuracy and robustness of CSR target information extraction. Computer simulation shows the effectiveness of the method.