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Hybrid electromagnetic imaging algorithm based on Bayesian compressed sensing and Born iteration

A Bayesian compression, hybrid electromagnetic technology, applied in electromagnetic field characteristics, based on specific mathematical models, calculations, etc., can solve nonlinear and ill-conditioned problems, and achieve the effect of reducing computational complexity, improving computational efficiency and imaging accuracy

Pending Publication Date: 2022-03-04
NANJING UNIV OF POSTS & TELECOMM
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Problems solved by technology

[0004] The purpose of the present invention is to provide a hybrid electromagnetic imaging algorithm based on Bayesian compressed sensing and Born iteration, which solves the nonlinear and ill-conditioned problems that occur when the traditional imaging method deals with non-weak scatterers, and greatly reduces the computational complexity And does not require cumbersome full-wave simulation, which improves computing efficiency and imaging accuracy

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  • Hybrid electromagnetic imaging algorithm based on Bayesian compressed sensing and Born iteration
  • Hybrid electromagnetic imaging algorithm based on Bayesian compressed sensing and Born iteration
  • Hybrid electromagnetic imaging algorithm based on Bayesian compressed sensing and Born iteration

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Embodiment 1

[0045] An embodiment of the present invention provides a hybrid electromagnetic imaging algorithm based on Bayesian compressed sensing and Born iteration, including the following steps:

[0046] S1. Calculate the initial value of the total field by using the Born approximation and the incident field;

[0047] S2. Start iteration, calculate the hyperparameter vector, reconstruct the scattering data in Bayesian according to the hyperparameter vector, calculate and update the contrast;

[0048] S3. Calculate and update the total field according to the incident field and the forward observation matrix on the basis of the initial value of the total field;

[0049] S4. In response to detecting that the convergence condition is met, the iteration is stopped, and the contrast and the total field are output.

Embodiment 2

[0051] like figure 1 As shown, a hybrid electromagnetic imaging algorithm based on Bayesian compressed sensing and Born iteration provided by the embodiment of the present invention, the specific implementation steps are as follows:

[0052] Step 1: Algorithm initialization, the number of iterations is set to 1, the contrast is set to 0, the Bayesian prior parameters are adjusted, the incident field and scattered field data are collected and stored, and the initial value of the total field is calculated.

[0053] Step 2: Hyperparameter estimation, that is, calculating the hyperparameter vector.

[0054] Step 3: Update the contrast, and calculate the contrast under the Bayesian framework.

[0055] Step 4: Update the total field according to the incident field and the forward observation matrix;

[0056] Step 5: Judging whether to converge according to the convergence condition, the judgment of the convergence condition is as follows: when the number of iterations reaches the pr...

Embodiment 3

[0058] A hybrid electromagnetic imaging algorithm based on Bayesian compressed sensing and Born iteration provided by an embodiment of the present invention includes the following steps.

[0059] Step 1, assuming that the detection area Ξ is surrounded by an electromagnetic source I with a quantity V v (r) Detection, its data equation and state equation are respectively:

[0060]

[0061]

[0062] Among them, Ω is the measurement area, H(·) is the 0th-order form of the Hankel function of the second kind, k is the spatial wave number, is the target contrast, I v (r) is the electromagnetic source of the incident field.

[0063] Step 2, establishing a discretization model, the discretization model includes a limited number of scene networks, a limited number of transmitting and receiving antennas, a limited number of frequency points, and the like.

[0064] Assuming that the scene is discretized into N×L grids, a discretization model is established; the number of detect...

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Abstract

The invention discloses a hybrid electromagnetic imaging algorithm based on Bayesian compressed sensing and Born iteration, and belongs to the technical field of non-weak scatterer imaging. Comprising the following steps: calculating a total field initial value by utilizing Born approximation and an incident field; iteration is started, a hyper-parameter vector is calculated, scattering data is reconstructed in Bayesian according to the hyper-parameter vector, and the contrast is calculated and updated; calculating and updating the total field according to the incident field and the forward observation matrix on the basis of the initial value of the total field; in response to detecting that a convergence condition is met, stopping iteration, and outputting a contrast ratio and a total field; the non-linear and ill-conditioned problems occurring when a traditional imaging method is used for processing a non-weak scatterer are solved, the calculation complexity is greatly reduced, tedious full-wave simulation is not needed, and the calculation efficiency and the imaging precision are improved.

Description

technical field [0001] The invention relates to a hybrid electromagnetic imaging algorithm based on Bayesian compressed sensing and Born iteration, and belongs to the technical field of non-weak scatterer imaging. Background technique [0002] Electromagnetic inverse scattering refers to the study of the characteristics of the scattered field according to the given incident field and the measured scattered field, and electromagnetic imaging is an important aspect of the application of electromagnetic inverse scattering theory, which refers to the given incident electromagnetic wave and part obtained by measurement Under the conditions of scattered field data, the geometric shape or electromagnetic parameters of the scatterers are imaged and reconstructed; with the increasing application of electromagnetic imaging, especially the continuous breakthroughs in medical and non-destructive testing of targets, people have become more and more interested in electromagnetic imaging. ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01N23/00G01R29/08G06F30/20G06N7/00
CPCG01N23/00G01R29/0871G01R29/0892G06F30/20G06N7/01
Inventor 陆宇航王芳芳
Owner NANJING UNIV OF POSTS & TELECOMM
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