Practical radar compressive sampling system via slow-time dimensional processing

Compressive sampling provides an effective undersampling method for Radar signal processing. Conventional radar compressive sampling system uses waveform-matched sparse dictionary to process undersampling and pulse compressing simultaneously. Such system´s lowest sample number is nearly proportional to the sparsity of reconstructed signal, which is equal to the number of targets in echo signal. However, in practical applications, clutters in signal will increase the sparsity of reconstructed signal seriously. In this paper we proposes a practical radar signal compressive sampling method via slow-time dimensional MTI clutter pre-suppression and MTD coherent pre-accumulation. The performance degradation of conventional radar compressive sampling system caused by clutters has been analyzed. We prove that the reconstructed signal of compressive sampled signal after MTI&MTD processing is same as a Nyquist sampled signal after pulse compressing and MTI&MTD processing. Theoretical analyses and simulations verify that the proposed compressive sampling system via slow-time dimensional processing is a valid system to undersample the radar echo signals in clutter environment.