GISAR image reconstruction based 2-D smoothed l0 norm minimization in sparse decomposition

General Inverse Synthetic Aperture Radar (GISAR) imaging algorithm based on two-dimensional (2-D) l0 norm minimization in signal sparse decomposition is discussed. GISAR geometry and kinematics are analytically described. GISAR signal model based on Linear Frequency Modulated (LFM) waveform is derived. The GISAR signal formation process is presented as a sparse decomposition in redundant Fourier basis. Image reconstruction procedure is presented as minimization of smooth norm of the image matrix. The algorithm of minimization of the number of non-zero point scatterers is thoroughly described. The results are illustrated by a numerical experiment.