Super-resolution Doppler Beam Sharpening based on Sparse Covariance Fitting

Conventional Doppler beam sharpening (DBS) technique forms the narrow-band Doppler filter groups by fast Fourier transform (FFT), resulting in poor cross-range resolution and high sidelobe level. Various super-resolution DBS methods are developed to enhance the cross-range resolution, but suffer from limited resolution improvement. In this paper, we exploit the inherent sparseness of the target distributions to formulate a super-resolution DBS methodology based on covariance fitting criterion. The method is global convergent, user-parameter free, and can yield an improved sparseness and higher cross-range resolution. Simulation results are presented to demonstrate the superior performance of the resulting super-resolution DBS method.