Comprehensive aperture radiometer inversion processing method based on multi-parameter regularization

Abstract

The invention discloses a comprehensive aperture radiometer inversion processing method based on multi-parameter regularization. The method comprises the following steps: 1) collecting visibility function data of an observation scene by using a synthetic aperture radiometer, and processing the visibility function data to obtain a visibility function V; calculating according to the system characteristic parameters of the synthetic aperture radiometer to obtain a system modulation matrix G of the synthetic aperture radiometer; 2) according to the visibility function V and the system modulation matrix G, utilizing a multi-parameter regularization method to obtain a feature regularization parameter vector; and 3) according to the feature regularization parameter vector, performing inversion to obtain brightness temperature distribution data of an observation scene, and finally obtaining a brightness temperature image of the observation scene. A multi-parameter regularization item is constructed, and a plurality of feature regularization parameters are selected by using a generalized cross validation criterion; and the image reconstruction error can be effectively reduced, and the brightness temperature precision of inversion imaging is improved.

Description

technical field [0001] The invention relates to a synthetic aperture radiometer inversion processing method in the technical field of microwave remote sensing, in particular to a synthetic aperture radiometer inversion processing method based on multi-parameter regularization. Background technique [0002] A synthetic aperture imaging radiometer (SAIR) is a passive microwave sensor for high-resolution imaging. Different from traditional real aperture radiometers, SAIRs improve the spatial resolution by using synthetic aperture technology, thereby avoiding various difficulties, such as bulky and weight problems brought by real aperture antennas, and enabling synthetic aperture radiometers without Mechanical scanning. [0003] The measurement output of SAIR is the visibility function sample in the frequency domain, and the brightness temperature distribution data in the spatial domain needs to be obtained through the brightness temperature reconstruction method. The reconstr...

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Problems solved by technology

In order to overcome the influence of the ill-conditioned inverse problem on the inversion accuracy, the typical brightness temperature reconstruction method is to obtain a stable and unique solution by adding new restrictions or penalties to the inverse problem, such as Tikhonov regularization and other methods (Picard B, Anterrieu E.Comparison of regularized inversion methods in synthetic aperture imagingradiometry[J].IEEE Transactions on Geoscience and Remote Sensing,2005,43(2):218-224.), and by considering the physical characteristics of band-limited imaging instruments to obtain suitable solutions The proposed band-limited regularization (Anterrieu E.A resolving matrix approach for synthetic aperture imaging radiometers[J].IEEE Transactions on Geoscience and Remote Sensing,2004,42(8):1649-1656.), but these regularization inversion methods often rely on Due to the selection of feature regularization parameters, and due to the ill-posed problem and the physical characteristics of limited frequency bands, there is still a large reconstruction error

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