A multi-feature constraint-based fmcw millimeter wave overlapping echo thickness measurement method and device

Abstract

The application provides a kind of FMCW millimeter wave overlapping echo thickness measurement method and device based on multi-feature constraint.For the object whose thickness needs to be measured, first, a frequency-modulated continuous wave FMCW transceiver is used to send a frequency-modulated continuous wave signal whose frequency changes linearly with time to the object, and the two echo signals reflected by the front and back walls of the measured object are mixed to obtain an intermediate frequency beat signal containing the time delay difference information of the front and back walls, and then the center positions of the front and back walls after spectral refinement are determined;Then, the two echo signals are superimposed and envelope extracted, and the center position of the superimposed signal is determined by envelope spectrum;Finally, the positions of the front and back walls of the object and the thickness are determined by the two center positions.This application realizes the separation and thickness extraction of the frequency domain overlapping front and back wall echo without the need to improve the millimeter wave hardware bandwidth and change the existing system hardware structure, thereby improving the measurement accuracy in the case of thin measured object.

Description

Technical Field

[0001] This application relates to the field of millimeter-wave radar technology, and in particular to an FMCW millimeter-wave overlap echo thickness measurement method and apparatus based on multi-feature constraints. Background Technology

[0002] Thickness measurement is a crucial quality control indicator in industrial manufacturing and material processing, especially for non-metallic materials such as polyethylene (PE) sheets, plastic products, and non-metallic pipes, as it directly affects the product's structural strength, sealing performance, and safety. Existing thickness measurement technologies mainly include radiographic thickness measurement, terahertz thickness measurement, ultrasonic thickness measurement, mechanical contact thickness measurement, and microwave thickness measurement.

[0003] X-ray thickness measurement utilizes the relationship between the energy attenuation of X-rays after penetrating a material and the thickness to measure thickness. It offers advantages such as fast response and suitability for continuous inspection in industrial production lines. However, due to the ionizing radiation characteristics of X-rays, it requires high standards for the operating environment and personnel protection. Terahertz thickness measurement leverages the good penetrating power of terahertz waves into non-metallic materials, enabling high-precision thickness measurement. However, its systems are complex, equipment costs are extremely high, and engineering deployment is difficult. Ultrasonic thickness measurement uses ultrasonic waves to propagate within the material and generate reflected echoes at the interfaces, calculating thickness based on propagation time. It offers high measurement accuracy, but typically requires a coupling agent, and its applicability is limited by rapid energy attenuation in porous and sound-absorbing materials. Mechanical contact thickness measurement methods rely on direct contact measurement using calipers, micrometers, etc. While simple in structure and low in cost, they are prone to damaging soft materials or high-precision surfaces and are difficult to meet the demands of high-speed online inspection.

[0004] Microwave thickness measurement technology utilizes the propagation and interface reflection characteristics of electromagnetic waves within materials to achieve thickness measurement. It features non-contact operation, penetration of thick non-metallic structures, and the elimination of coupling agents, making it particularly suitable for inspecting thick-walled structures such as rubber products, thick plastic parts, and polyethylene pipes. Frequency-modulated continuous wave (FMCW) millimeter-wave radar thickness measurement technology is an important implementation of microwave thickness measurement. Its basic principle is as follows: The FMCW transceiver transmits a frequency-modulated continuous wave signal whose frequency varies linearly with time. After the signal is incident on the surface of the material being measured, partial reflection occurs at the front wall interface, forming a front wall echo. The remaining signal penetrates the material and is reflected again at the rear wall interface, forming a rear wall echo. Both echo signals are received synchronously by the transceiver. The received echo and the transmitted reference signal are mixed to generate an intermediate frequency (IF) signal containing echo time difference information. A Fast Fourier Transform (FFT) is performed on this IF signal to obtain the IF spectrum. Two independent peaks in the spectrum correspond to the front and rear wall echoes, respectively. Frequency values ​​are extracted by peak detection, and the thickness of the material is calculated by combining parameters such as sweep bandwidth, sweep period, and material refractive index.

[0005] However, when the thickness of the object being measured is small, the beat frequency interval of the reflected signals from the front and rear walls in the frequency domain decreases in the existing FMCW millimeter-wave radar thickness measurement technology. Under the condition of limited system bandwidth, spectral overlap or aliasing is prone to occur. Traditional FFT thickness measurement methods are difficult to accurately separate the echoes from the front and rear walls, resulting in difficulties in interface location identification and a decrease in thickness measurement accuracy. Summary of the Invention

[0006] In view of this, this application provides a method and apparatus for FMCW millimeter-wave overlap echo thickness measurement based on multi-feature constraints, in order to solve the problem that the front and rear wall echoes cannot be accurately separated when the thickness of the object being measured is small, resulting in low measurement accuracy.

[0007] The first aspect of this application provides a method for FMCW millimeter-wave overlap echo thickness measurement based on multi-feature constraints, the method comprising: Two echo signals are obtained from the FMCW millimeter-wave radar transmitted signal and reflected by the front and rear walls of the object under test. The two echo signals are mixed to obtain an intermediate frequency beat frequency signal containing the propagation time delay difference information between the front and rear walls. The intermediate frequency beat frequency signal is subjected to spectral refinement processing to obtain a high-resolution spectrum. The high-resolution spectrum is then mapped to the distance domain to determine the high-resolution spectrum refinement curve. The center positions r0 of the front wall and the rear wall are determined based on the high-resolution spectrum refinement curve. The two echo signals reflected from the front and rear walls are superimposed, and then the envelope of the superimposed signal is extracted to obtain an envelope signal that reflects the superposition and modulation characteristics of the front and rear wall echoes. The envelope signal is subjected to spectral analysis. The center position r1 of the characteristic peak is determined based on the envelope spectrum. The positions of the front and rear walls are determined by the center positions r0 and r1. The thickness of the object under test is determined based on the positions of the front and rear walls.

[0008] Optionally, the spectral refinement processing of the intermediate frequency beat signal includes: The original discrete beat frequency signal is subjected to a complex frequency shift operation to obtain a baseband complex signal; The baseband complex signal is subjected to digital low-pass filtering, and the filtered baseband complex signal is downsampled according to a preset decimation factor. Then, a fast Fourier transform is performed on the downsampled signal to obtain the high-resolution spectrum with improved frequency resolution.

[0009] Optionally, the envelope extraction of the superimposed signal includes: The front wall echo signal and the rear wall echo signal are superimposed in the time domain to obtain the superimposed signal x(t); Performing a Hilbert transform on the superimposed signal x(t) yields the orthogonal components of the superimposed signal. (t); Based on the superimposed signal x(t) and the orthogonal components (t) Construct an analytic signal z(t) and calculate the magnitude of the analytic signal A(t) = |z(t)| as the envelope signal.

[0010] Optionally, before performing spectral refinement processing on the intermediate frequency beat frequency signal, the method further includes: The intermediate frequency beat frequency signal is subjected to a fast Fourier transform to obtain a low-resolution spectrum, and then the low-resolution spectrum is mapped to the distance domain to determine the low-resolution spectrum refinement curve. After determining the high-resolution spectrum refinement curve, anomaly detection is performed on the high-resolution spectrum refinement curve using the low-resolution spectrum refinement curve.

[0011] Optionally, the method is applied to the thickness measurement of non-metallic material sheets or pipes, wherein the object being measured is a PE sheet, plastic product, or polyethylene pipe.

[0012] A second aspect of this application provides an FMCW millimeter-wave overlap echo thickness measurement device based on multi-feature constraints, the device comprising: The beat frequency signal determination unit is used to acquire two echo signals formed by the reflection of the FMCW millimeter-wave radar transmitted signal through the front and rear walls of the object under test, and to perform frequency mixing processing on the two echo signals to obtain an intermediate frequency beat frequency signal containing information on the propagation time delay difference between the front and rear walls. The spectrum refinement unit is used to refine the spectrum of the intermediate frequency beat signal to obtain a high-resolution spectrum, then map the high-resolution spectrum to the distance domain to determine the high-resolution spectrum refinement curve, and determine the center position r0 of the front wall and the rear wall according to the high-resolution spectrum refinement curve. The envelope extraction unit is used to superimpose the two echo signals formed by the reflections from the front wall and the rear wall, and then extract the envelope of the superimposed signal to obtain an envelope signal that reflects the superposition modulation characteristics of the front and rear wall echoes. The thickness determination unit is used to perform spectral analysis on the envelope signal, determine the center position r1 of the characteristic peak based on the envelope spectrum, determine the positions of the front and rear walls through the center positions r0 and r1, and determine the thickness of the object under test based on the positions of the front and rear walls.

[0013] Optionally, the spectrum refinement unit performs spectrum refinement processing on the intermediate frequency beat signal, including: The original discrete beat frequency signal is subjected to a complex frequency shift operation to obtain a baseband complex signal; The baseband complex signal is subjected to digital low-pass filtering, and the filtered baseband complex signal is downsampled according to a preset decimation factor. Then, a fast Fourier transform is performed on the downsampled signal to obtain the high-resolution spectrum with improved frequency resolution.

[0014] Optionally, the envelope extraction unit performs envelope extraction on the superimposed signals, including: The front wall echo signal and the rear wall echo signal are superimposed in the time domain to obtain the superimposed signal x(t); Performing a Hilbert transform on the superimposed signal x(t) yields the orthogonal components of the superimposed signal. (t); Based on the superimposed signal x(t) and the orthogonal components (t) Construct an analytic signal z(t) and calculate the magnitude of the analytic signal A(t) = |z(t)| as the envelope signal.

[0015] Optionally, before performing spectral refinement processing on the intermediate frequency beat frequency signal, the device further includes: The refinement detection unit is used to perform a fast Fourier transform on the intermediate frequency beat frequency signal to obtain a low-resolution spectrum, and then map the low-resolution spectrum to the distance domain to determine the low-resolution spectrum refinement curve. After determining the high-resolution spectrum refinement curve, anomaly detection is performed on the high-resolution spectrum refinement curve using the low-resolution spectrum refinement curve.

[0016] In the embodiments provided in this application, for an object whose thickness needs to be measured, an FM continuous wave signal with a frequency that varies linearly with time is first sent to it via an FM continuous wave transceiver. Two echo signals formed by reflections from the front and rear walls of the object are acquired, and then mixed to obtain an intermediate frequency beat signal containing information on the propagation delay difference between the front and rear walls. The intermediate frequency beat signal is then spectrum-refined to determine a high-resolution spectrum refinement curve, and the refined center position r0 is determined using this curve. The two echo signals are then superimposed and their envelopes extracted, and the center position r1 is determined using the envelope spectrum. Finally, the positions and thicknesses of the front and rear walls of the object are determined using these two center positions. This application, by optimizing the echo signal processing and spectrum separation algorithm, achieves effective separation and thickness extraction of overlapping front and rear wall echoes in the frequency domain without increasing millimeter-wave hardware bandwidth or changing the existing system hardware structure. This improves the thickness resolution and measurement accuracy for thinner items, such as extremely thin PE boards. Attached Figure Description

[0017] Figure 1 A flowchart illustrating the method provided in this application embodiment; Figure 2This is an echo signal overlay diagram provided in an embodiment of this application; Figure 3 This is an example of envelope extraction effect provided in an embodiment of this application; Figure 4 This is a structural diagram of the device provided in the embodiments of this application; Figure 5 This is a schematic diagram of the internal structure of a computer device provided in an embodiment of this application. Detailed Implementation

[0018] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0019] The terminology used in this application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. The singular forms “a,” “the,” and “the” used in this application and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used herein refers to and includes any or all possible combinations of one or more of the associated listed items.

[0020] It should be understood that although the terms first, second, third, etc., may be used in this application to describe various information, such information should not be limited to these terms. These terms are only used to distinguish information of the same type from one another. For example, without departing from the scope of this application, first information may also be referred to as second information, and similarly, second information may also be referred to as first information. Depending on the context, the word "if" as used herein may be interpreted as "when," "when," or "in response to determination."

[0021] This application provides a method and apparatus for FMCW millimeter-wave overlap echo thickness measurement based on multiple feature constraints, so as to improve the thickness measurement accuracy of extremely thin objects.

[0022] The technical solutions of this application will be described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments.

[0023] like Figure 1 The diagram shown is a flowchart of a multi-feature constraint-based FMCW millimeter-wave overlap echo thickness measurement method provided in this application. The process may include the following steps: Step S101: Acquire two echo signals formed by the reflection of the FMCW millimeter-wave radar transmitted signal through the front and rear walls of the object under test, and perform frequency mixing processing on the two echo signals to obtain an intermediate frequency beat signal containing the propagation time delay difference information between the front and rear walls.

[0024] In this embodiment, a linear frequency modulated signal is first transmitted via an FMCW transceiver radar. This signal is reflected back from the front and rear walls of the object being measured, forming two echoes: In the formula A1 and A2 represent the delays corresponding to the front and rear walls, respectively, and are the amplitudes of the echoes from the front and rear walls. These two echoes are then mixed using a mixer to obtain the mixed output. , i=(1,2). In this formula, The starting frequency, For frequency modulation slope, , =The distance from the front and rear walls of the object under test to the FMCW transceiver radar. This mixer output This refers to the intermediate frequency beat frequency signal that contains information about the propagation time delay difference between the front and rear walls.

[0025] Step S102: Perform spectrum refinement processing on the intermediate frequency beat signal to obtain a high-resolution spectrum, then map the high-resolution spectrum to the distance domain to determine the high-resolution spectrum refinement curve, and determine the center position r0 of the front wall and the rear wall according to the high-resolution spectrum refinement curve.

[0026] In this embodiment, the following can be used: A spectral refinement algorithm is used. The process is as follows: First, a complex frequency shift operation is performed on the aforementioned intermediate frequency beat signal. Let the intermediate frequency beat signal be x(n), the initial sampling rate be fs, and the target center frequency be selected as f0. A complex exponential sequence is constructed to perform the frequency shift operation on the signal, shifting the center frequency of the target analysis band to zero, thus obtaining the baseband complex signal. .

[0027] Subsequently, the unit impulse response was used as Digital low-pass filter Smoothing is performed to obtain a signal with limited effective bandwidth. = To eliminate out-of-band interference and suppress aliasing; based on this, according to the extraction factor The signal is downsampled to obtain a sequence. Reduce the equivalent sampling rate to Next, execute the sequence. Point Fast Fourier Transform yields the refined spectrum. At this point, the frequency resolution is reduced from the original... Optimized to Finally, combining the theory of frequency-modulated continuous wave ranging, the frequency modulation slope is utilized. with the speed of light Through formula This maps frequency information to the distance domain, thereby generating a high-resolution spectral refinement curve.

[0028] Due to the limitations of radar bandwidth, the peak values ​​of the front wall echo and the rear wall echo in the high-resolution spectrum refinement curve may still overlap and cannot be directly distinguished. Therefore, this step finally determines the peak value on the curve as the center position r0 of the refined front and rear walls.

[0029] Step S103: The two echo signals formed by the reflections from the front wall and the rear wall are superimposed, and then the envelope of the superimposed signal is extracted to obtain an envelope signal that reflects the superposition modulation characteristics of the front and rear wall echoes.

[0030] In this embodiment, the front wall echo signal and the rear wall echo signal obtained in step S101 are first superimposed in the time domain, such as... Figure 2 As shown, the superimposed signal x(t) = x1(t) + x2(t) is obtained. Then, the envelope of this superimposed signal x(t) is extracted, as follows: 1) Perform a Hilbert transform on the superimposed signal x(t) to obtain its orthogonal components. (t).

[0031] 2) Based on the superimposed signal x(t) and the orthogonal components Construct the analytic signal z(t). .

[0032] 3) Calculate the magnitude of the analytic signal z(t). The modulus That is, the envelope signal of the superimposed signal x(t) mentioned above, such as Figure 3 As shown.

[0033] Step S104: Perform spectrum analysis on the envelope signal, determine the center position r1 of the characteristic peak based on the envelope spectrum, determine the positions of the front and rear walls based on the center positions r0 and r1, and determine the thickness of the object under test based on the positions of the front and rear walls.

[0034] In this embodiment, the envelope signal obtained in step S103 is processed by Fast Fourier Transform to convert the envelope information from the time domain to the frequency domain, thus obtaining the envelope spectrum. Since there is a fixed propagation delay difference between the front and rear wall echoes, corresponding low-frequency modulation characteristics will be formed in the envelope spectrum. The center position r1 of the characteristic peak is then determined based on the envelope spectrum.

[0035] After determining the refined center position r0 and the envelope-extracted center position r1, the simultaneous formulas r0=(y1+y2) / 2 and r1=(y2-y1) / 2 are constructed. In these formulas, y1 is the front wall echo position parameter and y2 is the rear wall echo position parameter. Using the front and rear wall position parameters obtained from these formulas, the propagation distance difference between the two interfaces is calculated, ultimately yielding the thickness value of the measured PE board. .

[0036] This concludes the process. Figure 1 The process is shown below.

[0037] This application can achieve the following technical effects: 1. Thickness measurement resolution can be improved without increasing hardware bandwidth. This solution optimizes echo signal processing and spectrum separation algorithms to achieve effective separation of echoes from the front and back walls of ultra-thin PE boards without increasing the bandwidth of the millimeter-wave radar system, thus reducing the dependence on ultra-high bandwidth hardware equipment.

[0038] 2. Improve the thickness measurement accuracy of ultra-thin PE sheets. In view of the problem that traditional FFT methods have difficulty in accurately identifying peaks when the front and rear wall spectra overlap, this solution can effectively extract interface information from the overlapping echoes, thereby improving the thickness measurement accuracy of thin-walled PE sheets.

[0039] 3. Enhance echo identification capability under complex conditions: This scheme can reduce the impact of multipath reflection, weak echo and spectral coupling on the measurement results to a certain extent by further processing the echo envelope and spectral characteristics, thereby improving the stability of interface identification.

[0040] In another embodiment, before performing spectral refinement on the intermediate frequency beat signal, the method further includes: The intermediate frequency beat frequency signal is subjected to a fast Fourier transform to obtain a low-resolution spectrum, and then the low-resolution spectrum is mapped to the distance domain to determine the low-resolution spectrum refinement curve. After determining the high-resolution spectrum refinement curve, anomaly detection is performed on the high-resolution spectrum refinement curve using the low-resolution spectrum refinement curve.

[0041] This embodiment adds an anomaly detection step to the above method. Specifically, it uses the low-resolution spectrum refinement curve generated from the signal before refinement to perform anomaly detection on the high-resolution spectrum refinement curve generated after refinement.

[0042] In practice, the high-resolution spectrum refinement curve is compared with the low-resolution spectrum refinement curve. If there is a significant deviation between the two in the estimation of the positions of the front and rear walls (the deviation exceeds the preset threshold), the current measurement result is determined to be abnormal, and a re-measurement or an alarm message can be triggered. If the deviation is within an acceptable range, the result of the high-resolution spectrum refinement curve is accepted and the subsequent steps are continued.

[0043] This embodiment introduces a low-resolution spectral refinement curve as a reference, which can effectively identify measurement anomalies caused by abnormal factors such as multipath interference, surface contamination, or incident angle deviation, thereby improving the robustness of the thickness measurement method and the reliability of the measurement results.

[0044] In another embodiment, the specific parameters involved in the above embodiments can also be illustrated by example.

[0045] In this embodiment, the FMCW millimeter-wave radar operates at a frequency of 77 GHz, with a sweep bandwidth of 4 GHz and a sweep period of 1 ms. The object under test is a PE sheet with a thickness of approximately 2 mm, and the refractive index of PE material in the millimeter-wave band is approximately 1.5.

[0046] In the spectrum refinement process, the original sampling rate fs was set to 10MHz, the decimation factor D was set to 8, and the number of FFT points N was set to 1024. After Zoom-FFT refinement, the frequency resolution was optimized from approximately 9.77kHz to approximately 1.22kHz, and the corresponding distance resolution was significantly improved.

[0047] During envelope extraction, a 64th-order FIR filter is used for Hilbert transform, and a 256-point FFT is used for envelope spectrum analysis. The above parameters are for illustrative purposes only; in practical applications, they can be adaptively adjusted according to the material properties, thickness range, and radar system performance of the object being measured.

[0048] This application also provides an FMCW millimeter-wave overlap echo thickness measurement device based on multi-feature constraints, such as... Figure 4 As shown, the device includes: The beat frequency signal determination unit 401 is used to acquire two echo signals formed by the reflection of the FMCW millimeter-wave radar transmitted signal through the front wall and the rear wall of the object under test, and to perform frequency mixing processing on the two echo signals to obtain an intermediate frequency beat frequency signal containing the propagation time delay difference information between the front wall and the rear wall. The spectrum refinement unit 402 is used to refine the spectrum of the intermediate frequency beat signal to obtain a high-resolution spectrum, then map the high-resolution spectrum to the distance domain to determine the high-resolution spectrum refinement curve, and determine the center position r0 of the front wall and the rear wall according to the high-resolution spectrum refinement curve. Envelope extraction unit 403 is used to superimpose the two echo signals formed by the reflection of the front wall and the rear wall, and then extract the envelope of the superimposed signal to obtain an envelope signal that reflects the superposition modulation characteristics of the front and rear wall echoes. The thickness determination unit 404 is used to perform spectral analysis on the envelope signal, determine the center position r1 of the characteristic peak according to the envelope spectrum, determine the position of the front and rear walls through the center position r0 and r1, and determine the thickness of the object under test according to the position of the front and rear walls.

[0049] In another embodiment, the spectrum refinement unit performs spectrum refinement processing on the intermediate frequency beat signal, including: The original discrete beat frequency signal is subjected to a complex frequency shift operation to obtain a baseband complex signal; The baseband complex signal is subjected to digital low-pass filtering, and the filtered baseband complex signal is downsampled according to a preset decimation factor. Then, a fast Fourier transform is performed on the downsampled signal to obtain the high-resolution spectrum with improved frequency resolution.

[0050] In another embodiment, the envelope extraction unit performs envelope extraction on the superimposed signals, including: The front wall echo signal and the rear wall echo signal are superimposed in the time domain to obtain the superimposed signal x(t); Performing a Hilbert transform on the superimposed signal x(t) yields the orthogonal components of the superimposed signal. (t); Based on the superimposed signal x(t) and the orthogonal components (t) Construct an analytic signal z(t) and calculate the magnitude of the analytic signal A(t) = |z(t)| as the envelope signal.

[0051] In another embodiment, before performing spectral refinement processing on the intermediate frequency beat frequency signal, the apparatus further includes: The refinement detection unit 405 is used to perform a fast Fourier transform on the intermediate frequency beat frequency signal to obtain a low-resolution spectrum, and then map the low-resolution spectrum to the distance domain to determine the low-resolution spectrum refinement curve. After determining the high-resolution spectrum refinement curve, anomaly detection is performed on the high-resolution spectrum refinement curve using the low-resolution spectrum refinement curve.

[0052] The above embodiments of the present invention provide a method for FMCW millimeter-wave overlap echo thickness measurement based on multiple feature constraints, and based on this method, a device for FMCW millimeter-wave overlap echo thickness measurement based on multiple feature constraints is provided. The above method and device can solve the problem that the front and rear wall echoes cannot be accurately separated when the thickness of the object being measured is small, resulting in low measurement accuracy.

[0053] This embodiment also discloses a computer device, such as... Figure 5 As shown, the computer device includes a processor and a memory, the memory storing at least one instruction, which is loaded and executed by the processor to implement any of the above-described FMCW millimeter-wave overlap echo thickness measurement methods based on multi-feature constraints.

[0054] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A method for thickness measurement using FMCW millimeter-wave overlap echo based on multi-feature constraints, characterized in that, The method includes: Two echo signals are obtained from the FMCW millimeter-wave radar transmitted signal and reflected by the front and rear walls of the object under test. The two echo signals are mixed to obtain an intermediate frequency beat frequency signal containing the propagation time delay difference information between the front and rear walls. The intermediate frequency beat frequency signal is subjected to spectral refinement processing to obtain a high-resolution spectrum. The high-resolution spectrum is then mapped to the distance domain to determine the high-resolution spectrum refinement curve. The center positions r0 of the front wall and the rear wall are determined based on the high-resolution spectrum refinement curve. The two echo signals reflected from the front and rear walls are superimposed, and then the envelope of the superimposed signal is extracted to obtain an envelope signal that reflects the superposition and modulation characteristics of the front and rear wall echoes. Spectral analysis is performed on the envelope signal. The center position r1 of the characteristic peak is determined based on the envelope spectrum. The simultaneous formulas r0=(y1+y2) / 2 and r1=(y2-y1) / 2 are constructed using the center positions r0 and r1 to determine the front wall echo position parameter y1 and the rear wall echo position parameter y2. Then, the thickness value d of the measured object is determined by d=y2-y1.

2. The method according to claim 1, characterized in that, The spectral refinement process for the intermediate frequency beat signal includes: The original discrete beat frequency signal is subjected to a complex frequency shift operation to obtain a baseband complex signal; The baseband complex signal is subjected to digital low-pass filtering, and the filtered baseband complex signal is downsampled according to a preset decimation factor. Then, a fast Fourier transform is performed on the downsampled signal to obtain the high-resolution spectrum with improved frequency resolution.

3. The method according to claim 1, characterized in that, The envelope extraction of the superimposed signal includes: The front wall echo signal and the rear wall echo signal are superimposed in the time domain to obtain the superimposed signal x(t); Performing a Hilbert transform on the superimposed signal x(t) yields the orthogonal components of the superimposed signal. (t); Based on the superimposed signal x(t) and the orthogonal components (t) Construct an analytic signal z(t) and calculate the magnitude of the analytic signal A(t) = |z(t)| as the envelope signal.

4. The method according to claim 1, characterized in that, Before performing spectral refinement processing on the intermediate frequency beat frequency signal, the method further includes: The intermediate frequency beat frequency signal is subjected to a fast Fourier transform to obtain a low-resolution spectrum, and then the low-resolution spectrum is mapped to the distance domain to determine the low-resolution spectrum refinement curve. After determining the high-resolution spectrum refinement curve, anomaly detection is performed on the high-resolution spectrum refinement curve using the low-resolution spectrum refinement curve.

5. The method according to claim 1, characterized in that, The method is applied to the thickness measurement of non-metallic material sheets or pipes, wherein the object being measured is a PE sheet, plastic product, or polyethylene pipe.

6. A multi-feature constraint-based FMCW millimeter-wave overlap echo thickness measurement device, characterized in that, The device includes: The beat frequency signal determination unit is used to acquire two echo signals formed by the reflection of the FMCW millimeter-wave radar transmitted signal through the front and rear walls of the object under test, and to perform frequency mixing processing on the two echo signals to obtain an intermediate frequency beat frequency signal containing information on the propagation time delay difference between the front and rear walls. The spectrum refinement unit is used to refine the spectrum of the intermediate frequency beat signal to obtain a high-resolution spectrum, then map the high-resolution spectrum to the distance domain to determine the high-resolution spectrum refinement curve, and determine the center position r0 of the front wall and the rear wall according to the high-resolution spectrum refinement curve. The envelope extraction unit is used to superimpose the two echo signals formed by the reflections from the front wall and the rear wall, and then extract the envelope of the superimposed signal to obtain an envelope signal that reflects the superposition modulation characteristics of the front and rear wall echoes. The thickness determination unit is used to perform spectral analysis on the envelope signal, determine the center position r1 of the characteristic peak based on the envelope spectrum, construct the simultaneous formulas r0=(y1+y2) / 2 and r1=(y2-y1) / 2 using the center positions r0 and r1, determine the front wall echo position parameter y1 and the rear wall echo position parameter y2, and then determine the thickness value d of the measured object using d=y2-y1.

7. The apparatus according to claim 6, characterized in that, The spectrum refinement unit performs spectrum refinement processing on the intermediate frequency beat signal, including: The original discrete beat frequency signal is subjected to a complex frequency shift operation to obtain a baseband complex signal; The baseband complex signal is subjected to digital low-pass filtering, and the filtered baseband complex signal is downsampled according to a preset decimation factor. Then, a fast Fourier transform is performed on the downsampled signal to obtain the high-resolution spectrum with improved frequency resolution.

8. The apparatus according to claim 6, characterized in that, The envelope extraction unit performs envelope extraction on the superimposed signal, including: The front wall echo signal and the rear wall echo signal are superimposed in the time domain to obtain the superimposed signal x(t); Performing a Hilbert transform on the superimposed signal x(t) yields the orthogonal components of the superimposed signal. (t); Based on the superimposed signal x(t) and the orthogonal components (t) Construct an analytic signal z(t) and calculate the magnitude of the analytic signal A(t) = |z(t)| as the envelope signal.

9. The apparatus according to claim 6, characterized in that, Before performing spectral refinement processing on the intermediate frequency beat frequency signal, the device further includes: The refinement detection unit is used to perform a fast Fourier transform on the intermediate frequency beat frequency signal to obtain a low-resolution spectrum, and then map the low-resolution spectrum to the distance domain to determine the low-resolution spectrum refinement curve; and after determining the high-resolution spectrum refinement curve, to perform anomaly detection on the high-resolution spectrum refinement curve through the low-resolution spectrum refinement curve.

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