Tomography SAR double-frequency ambiguity resolution method for sparse non-uniform baseline

Abstract

The invention discloses a tomography SAR double-frequency ambiguity resolution method for sparse non-uniform baselines, relates to the technical field of radar signal processing, and aims to suppressa large number of false targets appearing in three-dimensional imaging caused by the sparse non-uniform baseline and improve the image quality. The tomography SAR double-frequency ambiguity resolutionmethod comprises the steps of: acquiring position distribution of the sparse non-uniform baselines; taking a result image obtained by conjugate multiplication of elevation backward projection BP images at two frequency points, taking a peak sidelobe ratio of the result image as a cost function, taking a limiting frequency of SAR as a constraint condition to construct an optimization equation, andsolving the optimization equation to obtain optimal values f1* and f2* of the two frequency points; acquiring TomoSAR data of each sparse non-uniform baseline under the frequency points f1* and f2*;and classifying the TomoSAR data belonging to the same frequency point into a group, respectively carrying out chromatography processing to obtain backscattering coefficient estimated values of gridswith elevation coordinates z under f1* and f2* frequency points, and carrying out conjugate multiplication to obtain a deblurred image.

Description

technical field [0001] The invention relates to the technical field of radar signal processing, in particular to a tomographic SAR dual-frequency defuzzification method for sparse and non-uniform baselines. Background technique [0002] Tomosynthetic aperture radar (TomoSAR) is an extension of the traditional two-dimensional synthetic aperture radar (SAR) in the third dimension. The tomography technology uses the two-dimensional SAR data obtained by a certain number of radar motion trajectories satisfying a certain distribution, and performs aperture synthesis again in the height direction to realize three-dimensional imaging. However, in some scenarios, the position distribution and number of baselines are limited, and there is a contradiction between the amount of data collected and the resolution. Insufficient number of baselines will lead to blurring, and the non-uniform distribution of baselines will make the blur position distribution irregular, which improves the unde...

AI Technical Summary

Problems solved by technology

For many cases, the elevation baseline position distribution is non-uniform and not easy to change, the fuzzy position distribution lacks regularity, and the corresponding mathematical modeling is complicated, which increases the difficulty of understanding fuzzy

[0004] In summary, there is currently a lack of effective means to solve the elevation-oriented ambiguity problem of sparse non-uniform baselines

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