Compressed Sensing with Interleaving Slow-Time Pulses and Hybrid Sparse Image Reconstruction

This paper explores a type of hybrid sparse reconstruction technique for modern multifunction task scheduling radars and on following range-Doppler plots. A compressed sensing (CS) framework is devised to emit and then receive interleaved radar pulses in a scarce manner within a coherent processing interval. Sparse reconstruction methods are subsequently employed to regenerate full resolution range-Doppler images. Hybrid reconstructed solutions are finally formed by merging acquired data with sparsely recovered solutions. We show that this is essential for obtaining robust results in the presence of noisy environments and to measure outcomes on equal terms. Real data obtained from an experimental radar observing a Boeing 737 aircraft is employed to demonstrate the practical effectiveness of CS and hybrid sparse reconstruction.