Robust and efficient synthetic aperture radar multi-feature enhanced imaging method

The invention discloses a robust and efficient synthetic aperture radar multi-feature enhanced imaging method. The method comprises the following steps of: establishing an echo signal and a target multivariate feature enhancement framework; establishing a target multivariate feature enhancement solution equation, and solving target image data; applying entropy norm modeling synthetic aperture radar image focusing feature regularization prior, establishing a cost function, and solving an adjacent operator of the cost function to obtain a phase error and a focusing feature solution; applying l1norm modeling synthetic aperture radar image sparse feature regularization prior, and solving a sparse feature solution by using a soft threshold function and the phase error obtained in the step 3);and performing iteration on the target image data by using a Gaussian-Seidel method to obtain a synthetic aperture radar image with joint sparsity and focusing feature enhancement, and the like. According to the method, the sparse and focusing effects of the synthetic aperture radar image are recovered obviously in an experiment, and the focusing characteristics and sparse characteristics of the image can be enhanced quickly and effectively.