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Method for adaptive sparse type subspace tracking tomography reconstruction

A technology of subspace tracking and tomography, applied in the direction of material analysis, analysis of materials, image enhancement using wave/particle radiation, which can solve problems such as influence

Active Publication Date: 2018-03-23
LIAONING TECHNICAL UNIVERSITY
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Seriously affect the realization of the scheme to identify the real target in the intricate false target

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  • Method for adaptive sparse type subspace tracking tomography reconstruction
  • Method for adaptive sparse type subspace tracking tomography reconstruction
  • Method for adaptive sparse type subspace tracking tomography reconstruction

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[0037] The present invention will be further described below in conjunction with the accompanying drawings. The following is used to illustrate the present invention, but not to limit the scope of the present invention.

[0038] A method for adaptive sparse subspace tracking tomography reconstruction, such as figure 1 As shown, the specific method is as follows.

[0039] Step 1: Obtain the total number of radio frequency sensors at the transmitting end and radio frequency sensors at the receiving end in the radio frequency tomography system, and the pixels received by each radio frequency sensor at the receiving end;

[0040] As a transceiver device, a wireless radio frequency sensor can be non-uniform or non-uniform, assuming that the emitted reflection type is isotropic signal propagating in free space.

[0041] Step 2: Divide the coverage area of ​​the wireless radio frequency sensor network into a square grid, and establish a multi-scattering and multi-path system model ...

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Abstract

The invention discloses a method for adaptive sparse type subspace tracking tomography reconstruction. The method comprises the steps of acquiring the total number of wireless RF sensors at the transmitting end and the receiving end in an RF tomography system and pixels which are received by each wireless RF sensor at the receiving end; performing square grid dividing on an area which is covered by a wireless RF sensor network, establishing a multi-scattering multipath system model for aiming at the pixels which are received by the wireless RF sensors at the receiving end; performing discretization processing on the multi-scattering multipath sytem model and obtaining a multi-scattering multipath linear model; estimating target sparsity by means of a compression sensing sparsity adaptive reconstruction algorithm, and reconstructing the target image of the tomography system by means of a subspace tracking algorithm. The method according to the invention has advantages of improving reconstruction precision, saving operation time and improving image sharpness. The method can be widely applied in the field of tomography image reconstruction technology.

Description

technical field [0001] The invention belongs to the technical field of radio frequency tomographic image reconstruction, in particular to an adaptive sparse subspace tracking tomographic imaging reconstruction method. Background technique [0002] Radio frequency tomography images are widely used in important fields such as intelligent environmental monitoring, industrial non-destructive testing, medical diagnosis, and tunnel exploration. It uses medical CT technology for reference, irradiates the imaging area with precisely collimated radio frequency waves, and then infers the dielectric properties of the imaging area according to the scattered signal, so as to obtain the target image. When the radio frequency signal propagates from the sending end to the receiving end, it will experience multiple scattering and arrive at the receiving end from different paths. This is the multi-scattering multi-propagation path tomography system. However, due to the formation of many "fal...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/00H04B17/391H04B17/382H04W84/18G01N23/00
CPCG01N23/00G06T5/00H04W84/18H04B17/382H04B17/391
Inventor 高明明吴月南敬昌
Owner LIAONING TECHNICAL UNIVERSITY
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