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SAR imaging method based on non-convex total variation regularization

An imaging method and a technology of total variation, which can be used in the reflection/re-radiation of radio waves, the use of re-radiation, measurement devices and other directions, which can solve the problems of underestimation of SAR reconstruction targets, influence of SAR calibration accuracy, and signal processing errors. Achieve the effect of suppressing speckle noise, suppressing additive noise and clutter, and maintaining continuity

Active Publication Date: 2021-04-30
AEROSPACE INFORMATION RES INST CAS
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Problems solved by technology

But L 1 The regularization method is a convex optimization method, which inevitably underestimates the magnitude of the SAR reconstruction target, resulting in errors at the signal processing end, which in turn affects the accuracy of SAR calibration

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  • SAR imaging method based on non-convex total variation regularization
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  • SAR imaging method based on non-convex total variation regularization

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[0053] Compared to L 1 The norm penalty term, the graphics and properties of the non-convex penalty term are closer to L 0 Norm penalty term, thus, non-convex regularization can both obtain sparse solutions and avoid underestimation of the magnitude of reconstructed sparse vectors. Commonly used non-convex penalties are: L qNorm penalty, log sum penalty (LSP), minimum maximum concave penalty (Minimax concave penalty, MCP), smooth clipping absolute deviation penalty (Smoothly clipped absolute deviation, SCAD). A simple linear combination of the non-convex penalty term and the TV regular term generates a composite penalty function, and a non-convex & total variation regularization model can be obtained. This imaging model has the following advantages: 1. Compared with L 1 &TV regularization, this method avoids underestimating the magnitude of the reconstructed sparse vector and improves the reconstruction accuracy; 2. Compared with the matched filter (Matched filter, MF) algo...

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Abstract

The invention relates to a SAR imaging method based on non-convex total variation regularization, and the method comprises the following steps: constructing an SAR observation model; constructing an SAR imaging model based on non-convex total variation regularization; using a variable separation and generalized threshold iterative shrinkage algorithm to solve the SAR imaging model based on non-convex total variation regularization, and completing SAR imaging. Compared with the L1&TV regularization method, the target scattering intensity amplitude information can be accurately reconstructed, and the underestimation of the target scattering intensity amplitude information is avoided; compared with a conventional matched filtering algorithm, the method provided by the invention not only can effectively suppress additive noise and clutter, but also can suppress speckle noise, keeps continuity and uniformity of a surface target backscattering coefficient, and can enhance characteristics of a point target and a surface target at the same time.

Description

technical field [0001] The invention relates to the technical field of radar imaging, in particular to a SAR imaging method based on nonconvex & total variation regularization (Nonconvex & total variation regularization). Background technique [0002] Synthetic aperture radar (SAR) is an active microwave imaging system with the characteristics of all-day, all-weather and high-resolution imaging, and is widely used in military reconnaissance, environmental monitoring and land resource management. With the development of SAR technology, the resolution and mapping bandwidth of the radar system are required to be continuously improved, and the bottleneck of large data volume is becoming more and more obvious. [0003] Based on L 1 The regularized SAR imaging method can effectively suppress noise and clutter and improve image quality under the condition of full sampling; under the condition of downsampling rate, it can effectively reconstruct the SAR image and maintain the targe...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01S13/90
CPCG01S13/90
Inventor 吴一戎徐仲秋张冰尘刘鸣谦
Owner AEROSPACE INFORMATION RES INST CAS
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