L0 NORM OPTIMIZATION IN SAR IMAGE RECONSTRUCTION BASED ON SPARSE DECOMPOSITION
L0 NORM OPTIMIZATION IN SAR IMAGE RECONSTRUCTION BASED ON SPARSE DECOMPOSITION

Author(s): Andon Lazarov, Dimitar Minchev
Subject(s): Information Architecture, Electronic information storage and retrieval
Published by: Бургаски свободен университет
Keywords: SAR; Compressed Sensing; l0 norm optimization; Sparse Decomposition
Summary/Abstract: Synthetic Aperture Radar SAR) image reconstruction algorithms based sparse decomposition is considered. The linear frequency modulated (LFM) signal reflected from the scene, relief of the Earth surface is presented as matrix multiplication of three matrices: azimuth Inverse Discrete Fourier Transform (IDFT) matrix, image matrix and range IDFT matrix. L0 norm optimization image reconstruction procedure is applied over reduced number of measurements defined by randomly generated azimuth and range sensing matrix. The geometry of the scene is described by standard Matlab „peaks” function. Results of numerical experiments are provided

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