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Sparsity estimation compressed sensing reconstruction method

A compressive sensing reconstruction and sparsity technology, which can be used in instruments, measurement devices, and re-radiation to solve problems such as reduced reconstruction accuracy and unknown sparsity.

Pending Publication Date: 2022-06-17
NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
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Problems solved by technology

[0003] The purpose of the present invention is to propose a sparsity estimation compressive sensing reconstruction method combining least squares and local search, to solve the problem of low reconstruction accuracy caused by unknown sparsity in compressive sensing reconstruction, and to provide the final high-quality signal reconstruction provide assurance

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  • Sparsity estimation compressed sensing reconstruction method
  • Sparsity estimation compressed sensing reconstruction method
  • Sparsity estimation compressed sensing reconstruction method

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[0021] The invention is explained in more detail below by means of examples.

[0022] The algorithm flow is as figure 1 As shown, using the relationship between the sum of column pixel values ​​and the true sparsity, the optimal sparsity estimate is determined based on least squares and local search, and the signal is reconstructed with a regularized orthogonal matching pursuit algorithm. The specific method is as follows:

[0023] The method of this embodiment is used in the inverse synthetic aperture radar imaging of space-based high-speed moving targets. The Yake-42 scene image is restored, and the linear relationship between the sum of the pixel values ​​of each column of the image and the true sparsity is found through statistical analysis. The sparsity estimation function is squarely fitted to obtain the initial sparsity estimation value; then the local search method is used to obtain the sparsity estimation value that meets the set requirements, and finally the origina...

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Abstract

The invention discloses a sparseness estimation compressed sensing reconstruction method, which comprises the following steps of: finding a linear relation between the sum of pixel values of each column of an image and real sparseness through statistical analysis, and fitting a sparseness estimation function through least square to obtain an initial sparseness estimation value; and further obtaining an optimal sparseness estimation value by using a local search method. The method can complete the operation of quickly estimating the sparseness of the signal, solves the problem that the unknown sparseness seriously affects the precision of a greedy reconstruction algorithm, provides guarantee for the precise reconstruction of the compressed sensing signal, and has the advantages of low calculation complexity, good robustness and strong generalization ability.

Description

technical field [0001] The invention relates to a compressive sensing reconstruction method for sparsity estimation combined with least squares and local search, and belongs to the technical field of sub-sampling signal recovery. Background technique [0002] Inverse synthetic aperture radar is widely used in the research of air moving target imaging, but the bandwidth of the radar system cannot be increased infinitely, which limits the imaging resolution. Compressed sensing technology has the advantages of reducing bandwidth and data storage space, and is the key to solving the problem of high sampling rate. The theory of compressed sensing mainly includes: the sparse representation of the signal, the construction of the measurement matrix and the design of the reconstruction algorithm. Among them, the reconstruction algorithm design is the focus and difficulty of compressed sensing theory. In the actual reconstruction process, the unknown image sparsity leads to oversamp...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01S13/90H03M7/30
CPCG01S13/90H03M7/3062
Inventor 朱德燕付晓萱唐骏伟赵寰宇胡子佳
Owner NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
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