Radar-based method, apparatus, medium, and device for selecting a vibration measurement point

Abstract

This application discloses a method, apparatus, medium, and device for selecting vibration measurement points based on radar. The method includes: acquiring echo data of the object under test collected by a radar device; determining multiple candidate vibration points based on the echo data; estimating the stationary clutter component of each candidate vibration point to obtain the stationary clutter component; filtering out stationary measurement points from the candidate vibration points based on the stationary clutter component to obtain at least one vibration measurement point; and performing vibration measurement on the object under test based on each vibration measurement point. Using this application embodiment, stationary measurement points that do not vibrate can be filtered out from the candidate vibration points, thereby improving the accuracy of radar vibration measurement results.

Description

Technical Field

[0001] This application relates to the field of radar interferometry technology, specifically to a radar-based method, apparatus, medium, and equipment for selecting vibration measurement points. Background Technology

[0002] With the development of radar technology, radar, as a non-contact vibration measurement instrument, has many advantages that other vibration measurement instruments lack. Radar interferometric measurement technology is gradually being applied to the field of bridge vibration measurement. Currently, vibration measurement can be achieved using radar based on phase differential interferometry. By extracting the phase of pixels in the radar image and processing it through interferometric phase filtering, clutter suppression, phase unwrapping, time-series vibration extraction, and vibration parameter estimation, bridge vibration can be measured.

[0003] However, in actual measurement, radar is easily affected by factors such as thermal noise, external interference, and target scattering characteristics. A large number of pixels in the radar image have very low phase quality, making it impossible to achieve phase differential interferometry measurement. If a conventional high phase quality pixel selection scheme is used, a large number of stationary measurement points that have not vibrated will appear, resulting in low accuracy of radar vibration measurement results. Summary of the Invention

[0004] This application provides a radar-based method, apparatus, medium, and device for selecting vibration measurement points. It can filter out stationary measurement points that are not vibrating from the candidate vibration points, thereby improving the accuracy of radar vibration measurement results.

[0005] In a first aspect, this application provides a radar-based method for selecting vibration measurement points, characterized by comprising:

[0006] Acquire echo data of the object under test collected by radar equipment, and determine multiple vibration candidate points based on the echo data;

[0007] The stationary clutter component is estimated for each of the aforementioned vibration candidate points to obtain the stationary clutter component.

[0008] Based on the stationary clutter component, stationary measurement points are screened out from each of the vibration candidate points to obtain at least one vibration measurement point, and vibration measurement is performed on the object under test based on each of the vibration measurement points.

[0009] By adopting the above technical solution, the stationary clutter component of the vibration candidate point is calculated, and the vibration candidate point is divided into stationary measurement point and vibration measurement point according to the stationary clutter component. This allows the stationary measurement point to be screened out, and the vibration measurement of the radar is performed based on the vibration measurement point, thereby improving the accuracy of the radar vibration measurement results.

[0010] Optionally, determining multiple candidate vibration points based on the echo data includes:

[0011] An echo image is generated based on the echo data, and the echo image includes multiple pixels.

[0012] Pixels in the echo image whose amplitude is higher than the amplitude threshold are filtered out. The average amplitude of each pixel in the echo image after filtering out the pixels with amplitude values ​​higher than the amplitude threshold is calculated, and the average amplitude is determined as the noise amplitude.

[0013] Calculate the signal-to-noise ratio of each pixel based on the noise amplitude;

[0014] Pixels with a signal-to-noise ratio lower than the signal-to-noise ratio threshold are filtered out to obtain the vibration candidate points.

[0015] By adopting the above technical solution, pixels with high amplitude are screened out, and the average amplitude of pixels with low amplitude in the echo image is determined as the noise amplitude. The signal-to-noise ratio of the pixels is then calculated based on the noise amplitude, and pixels with low signal-to-noise ratio are screened out to complete the initial screening of pixels and obtain vibration candidate points.

[0016] Optionally, the step of estimating the stationary clutter component for each of the vibration candidate points to obtain the stationary clutter component includes:

[0017] Construct a stationary clutter component function, substitute each of the vibration candidate points into the stationary clutter component function to obtain the fitting circle center; obtain the stationary clutter component based on the fitting circle center and the stationary clutter component formula.

[0018] By adopting the above technical solution, the sequence of each vibration candidate point is substituted into the stationary clutter component function to obtain the fitting circle center. Then, the stationary clutter component is calculated based on the fitting circle center and the stationary clutter component formula.

[0019] Optionally, substituting each of the vibration candidate points into the stationary clutter component function to obtain the fitting circle center includes: substituting each of the vibration candidate points into the stationary clutter component function, generating a fitting circle according to the least squares method, and determining the center of the fitting circle to obtain the fitting circle center.

[0020] By adopting the above technical solution and using the least squares method, the center of the fitted circle is estimated, thereby obtaining the center of the fitted circle.

[0021] Optionally, the step of filtering out stationary measurement points from each of the candidate vibration points based on the clutter component to obtain at least one vibration measurement point includes:

[0022] Substituting the stationary clutter component and each of the vibration candidate points into the vibration index formula, the vibration index of each of the vibration candidate points is obtained.

[0023] Determine whether the vibration index of each vibration candidate point is greater than the vibration index threshold.

[0024] If the vibration index of the candidate vibration point is greater than the vibration index threshold, then the candidate vibration point is determined as the stationary measurement point, and the stationary measurement points among the candidate vibration points are eliminated to obtain at least one vibration measurement point.

[0025] By adopting the above technical solution, the vibration index of each vibration candidate point is calculated based on the stationary clutter component. Then, based on the vibration index threshold, each vibration candidate point is divided into effective vibration measurement points and stationary measurement points that need to be screened out.

[0026] A second aspect of this application provides a radar-based vibration measurement point selection device, the device comprising: a vibration candidate point determination module, configured to acquire echo data of the object under test collected by radar equipment, and determine multiple vibration candidate points based on the echo data;

[0027] The clutter component calculation module is used to estimate the stationary clutter component of each of the vibration candidate points to obtain the stationary clutter component; the vibration measurement point determination module is used to screen out the stationary measurement points among the vibration candidate points according to the stationary clutter component to obtain at least one vibration measurement point, and to perform vibration measurement on the object under test according to each of the vibration measurement points.

[0028] A third aspect of this application provides an electronic device.

[0029] A fourth aspect of this application provides a computer-readable storage medium.

[0030] By employing the technical solution of this application, the static clutter component of the vibration candidate points is calculated, and the vibration candidate points are divided into static measurement points and vibration measurement points according to the static clutter component. This allows the static measurement points to be screened out, and the vibration measurement of the radar is performed based on the vibration measurement points, thereby improving the accuracy of the radar vibration measurement results. Attached Figure Description

[0031] Figure 1 This is a schematic flowchart of a radar-based vibration measurement point selection method provided in an embodiment of this application.

[0032] Figure 2 This is a simulation diagram of a fitting circle center estimation method provided in an embodiment of this application;

[0033] Figure 3This is a schematic diagram of the structure of a radar-based vibration measurement point selection device disclosed in an embodiment of this application.

[0034] Figure 4 This is a schematic diagram of the structure of an electronic device disclosed in an embodiment of this application.

[0035] Explanation of reference numerals in the attached figures: 301, Vibration candidate point determination module; 302, Clutter component calculation module; 303, Vibration measurement point determination module; 400, Electronic equipment; 401, Processor; 402, Memory; 403, User interface; 404, Network interface; 405, Communication bus. Detailed Implementation

[0036] To enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments.

[0037] In the description of the embodiments of this application, the words "for example" or "for instance" are used to indicate examples, illustrations, or explanations. Any embodiment or design that is described as "for example" or "for instance" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design options. Rather, the use of the words "for example" or "for instance" is intended to present the relevant concepts in a specific manner.

[0038] In the description of the embodiments of this application, the term "multiple" means two or more. For example, multiple systems means two or more systems, and multiple screen terminals means two or more screen terminals. Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the indicated technical features. Thus, a feature defined with "first" or "second" may explicitly or implicitly include one or more of that feature. The terms "comprising," "including," "having," and variations thereof all mean "including but not limited to," unless otherwise specifically emphasized.

[0039] In one embodiment, please refer to Figure 1 This paper proposes a radar-based method for selecting vibration measurement points. This method can be implemented using a computer program, a microcontroller, or a radar-based vibration measurement point selection device based on the von Neumann architecture. The computer program can be integrated into the application or run as a standalone utility application.

[0040] Step 101: Acquire echo data of the object under test collected by radar equipment, and determine multiple candidate vibration points based on the echo data.

[0041] In this embodiment, the radar equipment can be a ground-based multiple-input multiple-output (MIMO) interferometric radar. MIMO radar uses a special arrangement of multiple transmitting and receiving antennas to synthesize a large-aperture array, possessing two-dimensional high-resolution imaging capabilities. Furthermore, imaging does not require mechanical movement of the antennas, and the use of electrical scanning enables rapid transmission and reception of radar signals, with image acquisition frequencies reaching tens of hertz. In this embodiment, the object under test refers to the object whose weak vibrations need to be measured, which can be a large structure such as a bridge.

[0042] For example, weak vibrations cannot be measured using the results of range focusing, but can be measured using the phase portion, which is more sensitive to range information. Specifically, the echo data collected by the radar equipment can be analyzed. After range focusing, the phase sequence of the echo data contains all vibration information, thereby extracting all vibration parameters. In this embodiment, these vibration parameters are defined as vibration candidate points.

[0043] Based on the above embodiments, as an optional embodiment, the step of determining multiple candidate vibration points based on echo data may further include the following steps:

[0044] Step 201: Generate an echo image based on the echo data.

[0045] For example, in this embodiment of the application, the echo image can be understood as a two-dimensional array composed of multiple pixels. Each pixel includes data in two dimensions: azimuth and range. Specifically, high-resolution imaging can be performed based on the echo data to generate the echo image.

[0046] Step 202: Filter out pixels in the echo image whose amplitude is higher than the amplitude threshold, calculate the average amplitude of each pixel in the echo image after filtering out pixels whose amplitude is higher than the amplitude threshold, and determine the average amplitude as the noise amplitude.

[0047] Specifically, when the signal-to-noise ratio is high, the performance of vibration measurement using complex information is better. In order to improve the accuracy of vibration measurement, it is necessary to filter out pixels in the echo image whose noise amplitude is higher than the amplitude threshold. By calculating the average amplitude of each pixel after filtering out pixels whose amplitude is higher than the amplitude threshold as the noise amplitude, the influence of pixels with large noise amplitude on the calculation results can be avoided.

[0048] Step 203: Calculate the signal-to-noise ratio of each pixel based on the noise amplitude, and remove pixels with a signal-to-noise ratio lower than the signal-to-noise ratio threshold to obtain vibration candidate points.

[0049] Specifically, the signal-to-noise ratio (SNR) threshold can be understood as an SNR threshold. In this embodiment, the SNR threshold ranges from 10 to 20 dB. In this embodiment, the SNR of each pixel can be calculated based on the noise amplitude, and the SNR of each pixel can be compared with the SNR threshold. Pixels with an SNR lower than the SNR threshold are filtered out, and the filtered pixels are defined as vibration candidate points.

[0050] Step 102: Estimate the stationary clutter component for each vibration candidate point to obtain the stationary clutter component.

[0051] Specifically, stationary clutter refers to the echo reflected by stationary objects. The complex information of vibration candidate points is mainly divided into stationary clutter components, vibration components, and noise components. If the stationary clutter component is strong, the amplitude and phase changes of the vibration candidate point caused by vibration will be relatively weak. Therefore, the stationary clutter component should be estimated before estimating the vibration index of the vibration candidate point.

[0052] For example, after analyzing the echo data to obtain candidate vibration points, it is necessary to screen out stationary measurement points that have not vibrated or candidate vibration points with small vibration amplitudes. Therefore, it is necessary to estimate the stationary clutter component of each vibration candidate point to obtain the clutter component of each candidate vibration point, and then screen out the candidate vibration points based on the clutter component of each candidate point.

[0053] Based on the above embodiments, as an optional embodiment, this application provides a fitted circle estimation method to calculate the stationary clutter component of each vibration candidate point. This process may further include the following steps:

[0054] Step 301: Construct the stationary clutter component function, substitute each of the vibration candidate points into the stationary clutter component function, and obtain the fitted circle center.

[0055] The stationary clutter component function is:

[0056]

[0057] In the formula, f represents the stationary clutter component function; x n y represents the real part of the candidate vibration point; n The imaginary part of the vibration candidate point; x c y represents the real part of the fitted circle; c R represents the imaginary part of the fitted circle; c The radius of the fitted circle is represented by ; N represents the number of candidate vibration points.

[0058] For example, please refer to Figure 2It shows a simulation diagram of a fitting circle center estimation method, constructing a stationary clutter component function, where the time series sequence of each vibration candidate point can be expressed as a complex sequence S. n For a complex sequence n = 1, 2, ..., N, the real and imaginary parts can be represented as {x} n y n According to the equation of a circle (xx) c ) 2 +(yy c ) 2 =R c 2 , where (x c y c ) represents the center of the circle, R c The radius is represented by . Substituting each candidate vibration point into the stationary clutter component function, without considering noise effects, and assuming the amplitude of each candidate vibration point remains constant while the phase changes, the point trajectories of the real and imaginary parts of its complex sequence are roughly distributed in a segment such as . Figure 2 On the arc shown, but in reality, each vibration candidate point will be affected by noise, and the point trajectory of its complex sequence will deviate from the arc. The degree of deviation depends on the noise level.

[0059] Furthermore, in a feasible implementation, the minimum problem of the stationary clutter component function can be solved using the least squares method, that is, the minimum problem of the point set {x} can be achieved. n y n Fitting the circular trajectory of} to achieve the center of the circle (x) c y c ), circle radius R c The estimate. For example... Figure 2 As shown, Figure 2 The center C of the arc is marked. Due to the influence of stationary clutter, the center C will deviate from the origin of the coordinate system. Therefore, if the stationary clutter component is not directly estimated and filtered out, it is difficult to distinguish between stationary measurement points and vibration measurement points based solely on the amplitude fluctuations.

[0060] Step 302: Obtain the stationary clutter component based on the fitted circle center and the formula for the stationary clutter component.

[0061] The formula for the stationary clutter component is:

[0062] S Clu =x c +j·y c ;

[0063] In the formula, S Clu It is represented as a stationary clutter component.

[0064] For example, by substituting the real and imaginary values ​​of the fitted circle center obtained above into the formula for the stationary clutter component, the stationary clutter component can be calculated.

[0065] Step 103: Based on the stationary clutter component, screen out the stationary measurement points among the candidate vibration points to obtain at least one vibration measurement point, and perform vibration measurement on the object under test based on each vibration measurement point.

[0066] Specifically, after calculating the stationary clutter component, the vibration index of each vibration point can be calculated based on the stationary clutter component. The vibration index can then be used to distinguish between vibration measurement points and stationary measurement points, thereby eliminating stationary measurement points and performing vibration measurements on the object under test based on the vibration measurement points.

[0067] Based on the above embodiments, as an optional embodiment, the process of distinguishing between vibration measurement points and stationary measurement points may further include the following steps:

[0068] Step 401: Substitute the stationary clutter component and each vibration candidate point into the vibration index formula to obtain the vibration index of each vibration candidate point.

[0069] The vibration index formula is as follows:

[0070]

[0071] Among them, I Vibr Indicates the vibration index; S n S represents a complex sequence of candidate vibration points. Clu represents the stationary clutter component; Std[] represents the standard deviation; Mean[] represents the mean.

[0072] For example, by substituting the stationary clutter component and each vibration candidate point into the vibration index formula, the absolute value of the difference between the complex sequence of the vibration candidate point and the stationary clutter component is calculated. Then, the vibration index is obtained by calculating the ratio of the standard deviation and the mean of this absolute value.

[0073] Step 402: Determine whether the vibration index of each vibration candidate point is greater than the vibration index threshold.

[0074] Step 403: If the vibration index of a candidate vibration point is greater than the vibration index threshold, then the candidate vibration point is determined as a stationary measurement point, and the stationary measurement points among the candidate vibration points are screened out to obtain at least one vibration measurement point.

[0075] In this embodiment of the application, the vibration index threshold can be understood as the vibration index limit, which is usually between 0.1 and 0.3.

[0076] For example, after calculating the vibration index of each vibration candidate point, the vibration index of each vibration point is compared with the vibration index threshold. Vibration candidate points with vibration indices less than the vibration index threshold are determined as vibration measurement points, and vibration candidate points with vibration indices greater than the vibration index threshold are determined as stationary measurement points.

[0077] The following are system embodiments of this application, which can be used to execute the method embodiments of this application. For details not disclosed in the system embodiments of this application, please refer to the method embodiments of this application.

[0078] Please refer to Figure 3 This application provides a radar-based vibration measurement point selection device, which may include: a vibration candidate point determination module 301, a clutter component calculation module 302, and a vibration measurement point determination module 303, wherein:

[0079] The vibration candidate point determination module 301 is used to acquire echo data of the object under test collected by the radar equipment, and determine multiple vibration candidate points based on the echo data.

[0080] The clutter component calculation module 302 is used to estimate the static clutter component of each of the vibration candidate points to obtain the static clutter component.

[0081] The vibration measurement point determination module 303 is used to filter out stationary measurement points from each of the vibration candidate points according to the stationary clutter component, obtain at least one vibration measurement point, and perform vibration measurement on the object under test according to each of the vibration measurement points.

[0082] Based on the above embodiments, as an optional embodiment, the vibration candidate point determination module 301 may further include: an echo image generation unit, a noise amplitude calculation unit, a signal-to-noise ratio calculation unit, and a vibration candidate point determination unit, wherein:

[0083] An echo image generation unit is used to generate an echo image based on the echo data, wherein the echo image includes multiple pixels.

[0084] The noise amplitude calculation unit is used to filter out pixels in the echo image whose amplitude is higher than the amplitude threshold, calculate the average amplitude of each pixel in the echo image after filtering out pixels whose amplitude is higher than the amplitude threshold, and determine the average amplitude as the noise amplitude.

[0085] The signal-to-noise ratio calculation unit is used to calculate the signal-to-noise ratio of each pixel based on the noise amplitude.

[0086] The vibration candidate point determination unit is used to filter out pixels with a signal-to-noise ratio lower than the signal-to-noise ratio threshold among the pixels to obtain the vibration candidate points.

[0087] Based on the above embodiments, as an optional embodiment, the clutter component calculation module 302 further includes: a fitting circle center determination unit and a clutter component calculation unit, wherein:

[0088] The fitting circle center determination unit is used to construct the stationary clutter component function. The vibration candidate points are substituted into the stationary clutter component function to obtain the fitting circle center.

[0089] The clutter component calculation unit is used to obtain the stationary clutter component based on the fitted circle center and the stationary clutter component formula.

[0090] Based on the above embodiments, as an optional embodiment, the fitting circle center determination unit further includes: a fitting circle center determination subunit, wherein:

[0091] The fitting circle center determination sub-unit is used to substitute each of the vibration candidate points into the stationary clutter component function, generate a fitting circle according to the least squares method, and determine the center of the fitting circle to obtain the fitting circle center.

[0092] Based on the above embodiments, as an optional embodiment, the vibration measurement point determination module may further include: a vibration index calculation unit, used to substitute the stationary clutter component and each of the vibration candidate points into the vibration index formula to obtain the vibration index of each of the vibration candidate points;

[0093] The vibration index determination unit is used to determine whether the vibration index of each vibration candidate point is greater than the vibration index threshold.

[0094] The vibration measurement point determination unit is used to determine the vibration candidate point as the stationary measurement point if the vibration index of the vibration candidate point is greater than the vibration index threshold, and to filter out the stationary measurement points among the vibration candidate points to obtain at least one vibration measurement point.

[0095] It should be noted that the above embodiments of the apparatus are only illustrated by the division of the above functional modules. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. In addition, the apparatus and method embodiments provided in the above embodiments belong to the same concept, and the specific implementation process can be found in the method embodiments, which will not be repeated here.

[0096] This application also discloses an electronic device. (See reference...) Figure 4 , Figure 4This is a schematic diagram of the structure of an electronic device disclosed in an embodiment of this application. The electronic device 400 may include: at least one processor 401, at least one network interface 404, a user interface 403, a memory 402, and at least one communication bus 405.

[0097] The communication bus 405 is used to enable communication between these components.

[0098] The user interface 403 may include a display screen and a camera. Optionally, the user interface 403 may also include a standard wired interface and a wireless interface.

[0099] The network interface 404 may optionally include a standard wired interface or a wireless interface (such as a Wi-Fi interface).

[0100] The processor 401 may include one or more processing cores. The processor 401 connects to various parts of the server using various interfaces and lines, and performs various server functions and processes data by running or executing instructions, programs, code sets, or instruction sets stored in memory 402, and by calling data stored in memory 402. Optionally, the processor 401 may be implemented using at least one hardware form of Digital Signal Processing (DSP), Field-Programmable Gate Array (FPGA), or Programmable Logic Array (PLA). The processor 401 may integrate one or a combination of several of the following: Central Processing Unit (CPU), Graphics Processing Unit (GPU), and modem. The CPU primarily handles the operating system, user interface graphics, and applications; the GPU is responsible for rendering and drawing the content required for display; and the modem handles wireless communication. It is understood that the modem may also not be integrated into the processor 401 and may be implemented as a separate chip.

[0101] The memory 402 may include random access memory (RAM) or read-only memory. Optionally, the memory 402 may include a non-transitory computer-readable storage medium. The memory 402 can be used to store instructions, programs, code, code sets, or instruction sets. The memory 402 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as touch function, sound playback function, image playback function, etc.), instructions for implementing the above-described method embodiments, etc.; the data storage area may store data involved in the above-described method embodiments, etc. Optionally, the memory 402 may also be at least one storage device located remotely from the aforementioned processor 401. (Refer to...) Figure 4 The memory 402, which serves as a computer storage medium, may include an operating system, a network communication module, a user interface module, and an application program for a radar-based method of selecting vibration measurement points.

[0102] exist Figure 4 In the illustrated electronic device 400, the user interface 403 is mainly used to provide an input interface for the user and acquire user input data; while the processor 401 can be used to call an application program stored in the memory 402 for a radar-based vibration measurement point selection method. When executed by one or more processors 401, the electronic device 400 performs one or more of the methods described in the above embodiments. It should be noted that, for the foregoing method embodiments, for the sake of simplicity, they are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, because according to this application, some steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also understand that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0103] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0104] In the various embodiments provided in this application, it should be understood that the disclosed apparatus can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some service interface; the indirect coupling or communication connection between apparatuses or units may be electrical or other forms.

[0105] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0106] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0107] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage device (CMD). Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned memory includes various media capable of storing program code, such as USB flash drives, portable hard drives, magnetic disks, or optical disks.

[0108] The above description is merely an exemplary embodiment of this disclosure and should not be construed as limiting the scope of this disclosure. Any equivalent changes and modifications made in accordance with the teachings of this disclosure shall still fall within the scope of this disclosure. Other embodiments of this disclosure will be readily apparent to those skilled in the art upon consideration of the specification and the disclosure of practical truths.

[0109] This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not described in this disclosure. The specification and embodiments are to be considered exemplary only, and the scope and spirit of this disclosure are defined by the claims.

Claims

1. A method for selecting a radar-based vibration measurement point, characterized in that include: Acquire echo data of the object under test collected by radar equipment, and determine multiple vibration candidate points based on the echo data; Based on the echo data, multiple candidate vibration points are determined, including: High-resolution imaging is performed based on the echo data to generate an echo image. The echo image is a two-dimensional array consisting of multiple pixels, and each pixel includes data in two dimensions: azimuth and range. Pixels in the echo image whose amplitude is higher than the amplitude threshold are filtered out. The average amplitude of each pixel in the echo image after filtering out the pixels with amplitude values ​​higher than the amplitude threshold is calculated, and the average amplitude is determined as the noise amplitude. Calculate the signal-to-noise ratio of each pixel based on the noise amplitude; Pixels with a signal-to-noise ratio lower than the signal-to-noise ratio threshold are filtered out to obtain the vibration candidate points; The stationary clutter component is estimated for each of the aforementioned vibration candidate points to obtain the stationary clutter component. Based on the stationary clutter component, stationary measurement points are screened out from each of the vibration candidate points to obtain at least one vibration measurement point, and vibration measurement is performed on the object under test based on each of the vibration measurement points. Based on the stationary clutter component, stationary measurement points are screened out from each of the candidate vibration points, resulting in at least one vibration measurement point, including: Substituting the stationary clutter component and each of the vibration candidate points into the vibration index formula, the vibration index of each of the vibration candidate points is obtained. Determine whether the vibration index of each vibration candidate point is greater than the vibration index threshold. If the vibration index of the candidate vibration point is greater than the vibration index threshold, then the candidate vibration point is determined as the stationary measurement point, and the stationary measurement points among the candidate vibration points are eliminated to obtain at least one vibration measurement point. The vibration index formula is: ； wherein, represents the vibration index; represents the complex sequence of the vibration candidate point, represents the stationary clutter component; Std[] represents the computation of the standard deviation; represents the computation of the mean.

2. The radar-based vibration measurement point selection method according to claim 1, characterized in that, The step of estimating the stationary clutter component for each of the aforementioned vibration candidate points to obtain the stationary clutter component includes: Construct a stationary clutter component function, and substitute each of the vibration candidate points into the stationary clutter component function to obtain the fitted circle center; The stationary clutter component is obtained based on the fitted circle center and the formula for the stationary clutter component.

3. The radar-based vibration measurement point selection method according to claim 2, characterized in that, The step of substituting each of the vibration candidate points into the stationary clutter component function to obtain the fitting circle center includes: Substitute each of the vibration candidate points into the stationary clutter component function, generate a fitting circle according to the least squares method, and determine the center of the fitting circle to obtain the fitting circle center.

4. The radar-based vibration measurement point selection method according to claim 2, characterized in that, The stationary clutter component function is: ； where f represents a stationary clutter component function; represents a real part value of the vibration candidate point; represents an imaginary part value of the vibration candidate point; represents a real part value of the fitted circle; represents an imaginary part value of the fitted circle; represents a radius of the fitted circle; and N represents the number of vibration candidate points. The formula for the stationary clutter component is: ； In the formula, is expressed as a stationary spurs component.

5. A radar-based selection device of a vibration measuring point, characterized in that The apparatus for performing the radar-based vibration measurement point selection method as described in claim 1, the apparatus comprising: The vibration candidate point determination module (301) is used to acquire echo data of the object under test collected by the radar equipment, and determine multiple vibration candidate points based on the echo data; The clutter component calculation module (302) is used to estimate the static clutter component of each of the vibration candidate points to obtain the static clutter component. The vibration measurement point determination module (303) is used to screen out stationary measurement points from each of the vibration candidate points according to the stationary clutter component, obtain at least one vibration measurement point, and perform vibration measurement on the object under test according to each of the vibration measurement points.

6. An electronic device, comprising: The device includes a processor (401), a memory (402), a user interface (403), and a network interface (404). The memory (402) is used to store instructions. The user interface (403) and the network interface (404) are used to communicate with other devices. The processor (401) is used to execute the instructions stored in the memory (402) to cause the electronic device (400) to perform the method as described in any one of claims 1-4.

7. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores instructions that, when executed, perform the steps of the method as described in any one of claims 1-4.

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