Tomosar dual-frequency defuzzification method for sparse non-uniform baseline

Abstract

The invention discloses a tomographic SAR dual-frequency defuzzification method for sparse non-uniform baselines, relates to the technical field of radar signal processing, can suppress a large number of false targets in three-dimensional imaging caused by sparse non-uniform baselines, and improve image quality. Obtain the position distribution of the sparse non-uniform baseline; take the result image of the conjugate multiplication of the elevation backprojection BP image at two frequency points, take the peak side lobe ratio as the cost function for the result image, and use the SAR limit frequency as the constraint Conditionally build the optimization equation and solve it to get the optimal value f of the two frequency points 1 * ,f 2 * . get in f 1 * ,f 2 * TomoSAR data of each sparse non-uniform baseline under the frequency point. Group the TomoSAR data belonging to the same frequency point into one group, and perform chromatographic processing separately to obtain f 1 * ,f 2 * The estimated value of the backscatter coefficient of the grid whose elevation coordinate is z under the frequency point is conjugated and multiplied to obtain the 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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