SPRITE: 3-D SParse Radar Imaging TEchnique

Abstract

An original 3-D high resolution radar imaging approach, called SPRITE for “SParse Radar Imaging TEchnique,” is presented. It incorporates in an original way the available prior knowledge about the electromagnetic backscattering, extending the commonly used sparse point-wise scatterers to sparse facet-wise scatterers. It is based on a regularization scheme that accounts for information of sparsity and support. The radar map formation is performed efficiently based on a penalized and constrained criterion, and an Alternating Direction Method of Multipliers algorithm, largely used in image restoration and machine learning. It is customized in a such way that, at each iteration, the map update is fast in the frequency domain by 3-D FFT and IFFT while the updates of the auxiliary variables are direct and separable. SPRITE is both evaluated on synthetic and real measurement data from a spherical measurement setup. In comparison to the conventional method, called Polar Format Algorithm, the resolution is drastically enhanced. The main scatterers are recovered with increased accuracy, leading to a deeper understanding of the scattering behavior. Furthermore, compared to recent $\ell _1$ based methods that are limited to point-wise scatterers, SPRITE and its facet-wise scatterers provide an impressive and improved spatial backscattering representation.