The existing sparse imaging observation error estimation methods are to usually estimate the error of each observation position by\nsubstituting the error parameters into the iterative reconstruction process, which has a huge calculation cost. In this paper, by\nanalysing the relationship between imaging results of single-observation sampling data and error parameters, a SAR observation\nerror estimation method based on maximum relative projection matching is proposed. First, the method estimates the precise\nposition parameters of the reference position by the sparse reconstruction method of joint error parameters. Second, a relative\nerror estimation model is constructed based on the maximum correlation of base-space projection. Finally, the accurate error\nparameters are estimated by the Broyden-Fletcher-Goldfarb-Shanno method. Simulation and measured data of microwave\nanechoic chambers show that, compared to the existing methods, the proposed method has higher estimation accuracy, lower\nnoise sensitivity, and higher computational efficiency.
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