Radar angular superresolution algorithm based on Fourier-Wavelet regularized deconvolution

Angular resolution of real aperture radar is limited by the aperture size and wavelength. In this paper, a novel angular superresolution algorithm based on Fourier-Wavelet regularized deconvolution (ForWaRD) is proposed. Orthogonal expansion and scalar shrinkage in a tandem transform domain lie at the core of the ForWaRD. Duo to deconvolution is a noise sensitive process, the method is used to deconvolve and denoise the echo signal simultaneously. We also conclude that optimum performance of this algorithm is simultaneously determined by the Fourier structure of the antenna pattern and the wavelet structure of the surface scatterers. Simulation results show that the algorithm can efficiently enhance the resolution of scanning radar under a low SNR environment.