Coherent radar imaging based on compressed sensing

摘要: High-resolution radar images in the horizontal spatial domain generally require a large number of different baselines that usually come with considerable cost. In this paper, aspects compressed sensing (CS) are introduced to coherent imaging. We propose single CS-based formalism enables full three dimensional (3D)—range, Doppler frequency and (represented by direction cosines) domain—imaging. This new method can not only reduce system costs decrease needed enabling sparse sampling, but also achieves high-resolution range, frequency, space dimensions. Using an assumption point targets, 3D signal model for imaging has been derived. By comparing numerical simulations fast Fourier transform (FFT) maximum entropy (ME) methods at signal-to-noise ratios (SNRs), we demonstrate CS provide better performance resolution detectability given comparatively few available measurements relative required Nyquist-Shannon sampling criterion. These techniques being applied meteor observations.