Method for accurately detecting weak information change based on ultra-wideband microwave dual-band information fusion
By adopting a dual-band information fusion method in ultra-wideband microwave sensors, interfering signals are eliminated and intelligent algorithms are used to predict, the problem of miniaturized antennas being reduced to noise sensitivity and penetration depth in non-destructive detection is solved, and higher detection accuracy and system stability are achieved.
Patent Information
- Application Number
- CN202311747473.3
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2023-12-19
- Publication Date
- 2025-06-20
AI Technical Summary
Miniaturized antennas will lead to higher frequency bandwidths in non-destructive testing, making the sensor more sensitive to environmental noise and reduce the penetration depth, making it difficult to accurately detect weak information changes.
The method based on ultra-wideband microwave dual-band information fusion is adopted, and the interference signals of low-frequency reflection coefficient and high-frequency transmission coefficient are eliminated through dual-band microwave signal fusion, and the test samples are predicted using intelligent algorithms (such as convolutional neural networks).
It improves the non-destructive detection accuracy of ultra-wideband microwave sensors, enhances the prediction accuracy of detection signals and system stability, and can effectively detect weak information changes, such as the detection of blood sugar concentration.
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Abstract
Description
Technical Field
[0001] The present invention belongs to the fields of biomedical detection and ultra-wideband microwave non-destructive detection, and relates to a novel ultra-wideband microwave frequency band information fusion method. Background Art
[0002] Miniaturized devices are the research goal of future wearable devices and integrated devices. As a non-destructive detection device, the principle of an antenna is that changes in the dielectric properties of the object to be measured cause differences in the propagation of microwave signals, thereby characterizing the target object. However, reducing the size of the antenna also brings a series of problems. For example, a higher frequency bandwidth makes the sensor more sensitive to environmental noise, and the penetration depth also decreases. In order to reduce the interference of antenna miniaturization on the detection signal, a dual-band information fusion method based on ultra-wideband microwave signals is proposed. Summary of the Invention
[0003] The present invention provides a method for accurately detecting weak information changes based on ultra-wideband microwave dual-band information fusion to improve the accuracy of non-destructive detection of ultra-wideband microwave sensors. Taking the non-invasive detection of glucose concentration by microwave as an example, this method is simple and fast, and can judge the blood glucose concentration through the fusion of dual-band microwave signals, avoiding harmful methods to the human body such as puncture, and can obtain sufficient information to detect the test sample. The technical solution of the present invention is as follows: A method for accurately detecting weak information changes based on ultra-wideband microwave dual-band information fusion, comprising the following steps: (1) Build a microwave non-destructive detection system; (2) Configure different test samples; (3) Calibrate and set the vector network analyzer; (4) Read the ultra-wideband microwave signals of different test samples; (5) Define two working frequency bands, namely low frequency and high frequency; (6) Compare the microwave signals of the dual bands with the changes in the reference values of the test samples and plot them into a graph; (7) Perform information fusion on the dual-band microwave signals, filter out the low-frequency reflection coefficient and the high-frequency transmission coefficient, and use them as the input of the target object recognition algorithm; (8) Use an intelligent algorithm (taking the convolutional neural network as an example) to predict the test samples. Description of the Drawings
[0004] Figure 1 Measurement device diagram Figure 2 Dual-band spectrum diagram Figure 3 Relationship between microwave signals of different frequency bands and glucose concentration Figure 4 Glucose concentration prediction result Embodiment
[0005] The object of the present invention is to overcome the negative impact of antenna miniaturization on detection signals, and a high-low frequency information fusion method is proposed. Taking glucose concentration detection as an example, two miniaturized ultra-wideband antennas are placed on both sides of the detection model. The reflection coefficient and transmission coefficient are collected, and the interference information in the high frequency and low frequency is removed by the high-frequency and low-frequency information fusion method. Finally, an intelligent algorithm is used to accurately predict the test samples. At the same time, the ultra-wideband microwave signal has the advantages of low radiation power and large target information carrying capacity, and can be used as a conventional means for non-destructive detection of blood glucose concentration. Therefore, it is necessary to improve the prediction accuracy of detection signals and the system stability through high-frequency and low-frequency information fusion.
[0006] The present invention will be described below with reference to the accompanying drawings and examples.
[0007] (1) Since the dielectric constants of the samples to be measured are different. Therefore, microwave signals can be used to characterize the test samples. Two miniaturized ultra-wideband antennas are placed on both sides of the detection model, and the reflection coefficient and transmission coefficient are collected, so as to realize non-destructive detection of the test samples.
[0008] (2) Connect the antenna to the vector network analyzer, as Figure 1 shown, and then calibrate the vector network analyzer.
[0009] (3) Taking glucose concentration detection as an example, glucose solutions with different concentrations are prepared and injected into the detection model in equal amounts in turn, and the reflection coefficient and transmission coefficient are recorded by the vector network analyzer.
[0010] (4) Read the microwave signals measured by the vector network analyzer, and draw the frequency-domain waveform diagrams of different blood glucose concentrations, as Figure 2 shown. Divide the high-frequency and low-frequency two working frequency bands according to certain rules.
[0011] (5) Analyze the microwave signals in the two frequency bands, and adopt a dual-frequency information fusion strategy to remove interference signals such as the low-frequency reflection coefficient and the high-frequency transmission coefficient, as Figure 3 shown. The fused signal is input into an intelligent algorithm (taking a convolutional neural network as an example) to accurately predict the test samples, as Figure 4 shown.
[0012] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will be accorded the widest scope consistent with the principles and novel features disclosed herein.
[0013] The above are only embodiments of the present application and are not intended to limit the present application. For those skilled in the art, various changes and modifications can be made to the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included within the scope of the claims of the present application.
Claims
1. A method for accurately detecting weak information changes based on ultra-wideband microwave dual-band information fusion. This method is simple and fast, and can eliminate interference signals in high and low frequencies through the dual-band information fusion strategy, improving the stability and accuracy of the sensing system. Taking glucose concentration detection as an example, the technical solution of the present invention is as follows: A method for accurately detecting weak information changes based on ultra-wideband microwave dual-band information fusion includes the following steps: (1) Build a microwave non-destructive testing system; (2) Configure different test samples; (3) Calibrate and set the vector network analyzer; (4) Read the ultra-wideband microwave signals of different test samples; (5) Define two working frequency bands, namely low frequency and high frequency; (6) Compare the microwave signals of the dual-band with the change of the test sample reference value and draw a graph; (7) Perform information fusion on the dual-band microwave signals, filter out the low-frequency reflection coefficient and the high-frequency transmission coefficient, and use them as the input of the target object recognition algorithm; (8) Use an intelligent algorithm (taking the convolutional neural network as an example) to predict the test samples.