Calibration method, system, electronic device and storage medium for bridge deflection monitoring

Abstract

The application discloses a bridge deflection monitoring calibration method, system, electronic device and storage medium, the method comprises the following steps: obtaining the total number of the to-be-monitored targets installed on the bridge, the calibration parameters of each target and the factory calibration coefficient, and obtaining the first new calibration coefficient generated after the millimeter wave radar and all target installation calibration; obtaining the radio frequency data of the millimeter wave radar, processing the radio frequency data to obtain 2D data; generating a point cloud target by using the 2D data and the factory calibration coefficient; matching the corresponding point cloud target to each target by using the calibration parameters of each target, wherein the calibration parameters comprise distance information and angle information; calculating the angle spectrum phase of each to-be-detected target matched to the point cloud target by using the 2D data, the calibration parameters and the first new calibration coefficient; and calculating the deflection value of each to-be-detected target by using the angle spectrum phase.

Description

Technical Field

[0001] This invention relates to the field of radar technology, and in particular to a calibration method, system, electronic device, and storage medium for bridge deflection monitoring. Background Technology

[0002] Bridge deflection monitoring is a key indicator for assessing bridge safety. Current methods for bridge deflection monitoring utilize millimeter-wave radar, but the accuracy of these monitoring methods needs improvement. Summary of the Invention

[0003] This invention provides a calibration method, system, electronic device, and storage medium for bridge deflection monitoring, aiming to effectively solve the technical problem that the accuracy of bridge deflection monitoring using millimeter-wave radar in the prior art needs to be improved.

[0004] According to a first aspect of the present invention, the present invention provides a calibration method for bridge deflection monitoring, comprising: acquiring the total number of targets to be monitored installed on the bridge, the calibration parameters and factory calibration coefficients of each target, and acquiring a first new calibration coefficient generated after the millimeter-wave radar and all targets are installed and calibrated; acquiring radio frequency data of the millimeter-wave radar and processing the radio frequency data to obtain 2D data; generating point cloud targets using the 2D data and the factory calibration coefficients; matching a corresponding point cloud target for each target using the calibration parameters of each target, wherein the calibration parameters include distance information and angle information; calculating the angular spectrum phase for each target matched with a point cloud target using the 2D data, the calibration parameters, and the first new calibration coefficients; and calculating the deflection value of each target using the angular spectrum phase.

[0005] Furthermore, the step of obtaining the first new calibration coefficient generated after the millimeter-wave radar and all targets are installed and calibrated includes: determining whether the first new calibration coefficient corresponding to the nth target to be detected exists; if it exists, the first new calibration coefficient is read into memory, and n=n+1 is set to obtain the first new calibration coefficient corresponding to the next monitoring target, until n is not less than the total number of targets to be detected.

[0006] Furthermore, the step of generating point cloud targets using 2D data and the factory calibration coefficients includes: performing constant false alarm rate (CFAR) processing on the 2D data to obtain first processed data; calibrating the antenna channel of the millimeter-wave radar based on the factory calibration coefficients; and performing angular dimension FFT using the first processed data and the calibrated antenna channel to obtain point cloud targets.

[0007] Furthermore, the step of matching each target with a corresponding point cloud target using the calibration parameters of each target includes: determining whether the target in the point cloud target has a matching target; if not, traversing a predetermined number of targets to obtain the point cloud target that matches the current target.

[0008] Further, the step of calculating the angular spectrum phase of each target to be detected that matches the point cloud target using 2D data and the first new calibration coefficient includes: determining whether a command to generate a new calibration table has been received; if received, generating a new calibration table based on the 2D data and saving it as a new calibration file; calibrating based on the new calibration table and performing an angle-dimensional FFT according to the calibration parameters to calculate the angular spectrum phase of the target; determining whether the step of traversing a predetermined number of targets has been completed; if completed, executing the step of calculating the deflection value of each target to be detected using the angular spectrum phase, until the step of traversing a predetermined number of targets has been completed.

[0009] Furthermore, the calibration method for bridge deflection monitoring further includes: after the step of determining whether a command to generate a new calibration table has been received, if no command has been received, determining whether a first new calibration coefficient exists; if a first new calibration coefficient exists, directly executing the step of calibrating based on the new calibration table and performing an angle-dimensional FFT according to the calibration parameters to calculate the angular spectrum phase of the target; if a first new calibration coefficient does not exist, executing the step of determining whether the traversal of the predetermined number of targets has been completed, until the traversal of the predetermined number of targets is completed.

[0010] Further, the step of generating a new calibration table based on the 2D data includes: obtaining the distance parameters and angle calibration parameters of the target in the 2D data; matching the point cloud target according to the distance parameters and the angle calibration parameters, and obtaining the distance value and Doppler index value between the matched point cloud targets; obtaining MIMO channel complex data according to the distance value and the Doppler index value; selecting one channel of the millimeter-wave radar as a reference channel, and obtaining the reference channel data as a reference value; obtaining all channel data of the millimeter-wave radar and calculating the absolute value; calculating the phase compensation coefficient using the absolute value, the reference value, and the channel data used; calculating the absolute value of the phase compensation coefficient and normalizing the amplitude to obtain a first new calibration coefficient.

[0011] According to a second aspect of the present invention, the present invention also provides a calibration system for bridge deflection monitoring, comprising: a parameter acquisition module, configured to acquire the total number of targets to be monitored installed on the bridge, the calibration parameters and factory calibration coefficients of each target, and acquire a first new calibration coefficient generated after the millimeter-wave radar and all targets are installed and calibrated; a 2D data generation module, configured to acquire radio frequency data of the millimeter-wave radar and process the radio frequency data to obtain 2D data; a point cloud target generation module, configured to generate point cloud targets using the 2D data and the factory calibration coefficients; a matching module, configured to match a corresponding point cloud target for each target using the calibration parameters of each target, wherein the calibration parameters include distance information and angle information; an angle spectrum phase calculation module, configured to calculate the angle spectrum phase for each target matched with a point cloud target using the 2D data, the calibration parameters, and the first new calibration coefficients; and a deflection value calculation module, configured to calculate the deflection value of each target using the angle spectrum phase.

[0012] According to a third aspect of the present invention, the present invention also provides an electronic device comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, it implements the calibration method for bridge deflection monitoring described in any one of the above embodiments.

[0013] According to another aspect of the present invention, the present invention also provides a computer-readable storage medium having a computer program stored thereon, characterized in that, when the computer program is executed by a processor, it implements the calibration method for bridge deflection monitoring described in any one of the above-described methods.

[0014] Through one or more embodiments of the above embodiments of the present invention, at least the following technical effects can be achieved:

[0015] In the technical solution disclosed in this invention, the deflection of the bridge is monitored by monitoring targets on the bridge, which helps to improve the accuracy of bridge deflection monitoring. Attached Figure Description

[0016] The technical solution and other beneficial effects of the present invention will become apparent from the following detailed description of specific embodiments of the invention, in conjunction with the accompanying drawings.

[0017] Figure 1 This is a schematic diagram of the antenna transmission and reception for a millimeter-wave radar.

[0018] Figure 2 A flowchart of a calibration method for bridge deflection monitoring provided in an embodiment of the present invention;

[0019] Figure 3Phase curve of the target in the old calibration scheme during the accuracy verification process of the calibration method for bridge deflection monitoring provided in the embodiments of the present invention;

[0020] Figure 4 The phase curve of the target of the calibration scheme in this embodiment of the invention is shown during the accuracy verification process of the calibration method for bridge deflection monitoring provided in this embodiment of the invention.

[0021] Figure 5 Phase curve of the target of the old calibration scheme during the noise verification process of the calibration method for bridge deflection monitoring provided in the embodiments of the present invention;

[0022] Figure 6 The phase curve of the target of the calibration scheme in this embodiment of the bridge deflection monitoring calibration method provided in the noise verification process of the calibration scheme of this invention;

[0023] Figure 7 Phase curve of the target of the old calibration scheme during the universality verification process of the calibration method for bridge deflection monitoring provided in the embodiments of the present invention;

[0024] Figure 8 The phase curve of the target of the calibration scheme in this invention is used to verify the universality of the calibration method for bridge deflection monitoring provided in the embodiments of the present invention.

[0025] Figure 9 A framework diagram of a calibration system for bridge deflection monitoring provided in an embodiment of the present invention;

[0026] Figure 10 This is a schematic block diagram of the electronic device according to an embodiment of the present invention. Detailed Implementation

[0027] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0028] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the term "and / or" in this document is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Furthermore, the character " / " in this document, unless otherwise specified, generally indicates that the preceding and following related objects have an "or" relationship.

[0029] Millimeter-wave radar antenna calibration can generally be divided into two methods: point calibration and linear calibration. Both methods are typically performed under anechoic conditions.

[0030] Point calibration involves placing the inverted radar at a predetermined distance (meeting far-field conditions), with its angle relative to the radar fixed at 0°. Since this is in the far-field condition and the angle is 0°, theoretically, the phase and amplitude of the data from each channel should be consistent. Data from the channel corresponding to the inverted radar is acquired, and a set of calibration coefficients is calculated to ensure that the phase and amplitude of all channels remain consistent after multiplying by these coefficients.

[0031] Linear calibration also involves placing the angular inverter at a set distance (meeting far-field conditions), acquiring channel data of the angular response at different angles by rotating the radar, and performing linear fitting (least squares method) to ultimately obtain a set of calibration coefficients. The specific principle is as follows:

[0032] (1)

[0033] like Figure 1 As shown, This refers to the antenna spacing between adjacent channels. The angle is relative to the radar. In formula (1) This represents the phase difference between adjacent channels. The wavelength of electromagnetic waves, The inherent spacing difference is due to factors such as manufacturing process. This is the inherent phase difference value. It can be seen that... and To satisfy a linear relationship, the slope and intercept of the line can be determined by measuring data from multiple angles. The slope can then be used to calculate... Intercept corresponding The antenna is compensated for when calculating the steering vector, thereby achieving the antenna calibration function.

[0034] The far-field condition refers to the condition that: D > 2 * L 2 / λ, where D is the distance from the target to the radar, L is the maximum size of the antenna, and λ is the wavelength.

[0035] However, existing point calibration schemes only consider the 0° case and are not fully adaptable to other angles (for example, when there are manufacturing errors in the antenna spacing, this calibration scheme cannot accurately compensate for non-zero angles). Linear calibration schemes, in order to ensure accuracy across the entire angle measurement range (globally optimal), result in non-optimal accuracy of the angle measurement phase at different angles. Especially at certain large angles, the angle measurement (angle spectrum) phase accuracy may be poor. In bridge deflection monitoring scenarios, phase accuracy is critical; even small phase deviations can lead to errors during phase unwinding, significantly impacting the deflection results.

[0036] Furthermore, radars installed in the field, exposed to wind and sun for extended periods, will experience hardware and structural aging, and may also develop issues such as impurities covering the radome. These problems can cause a mismatch between the factory calibration coefficients and the actual situation. Usually, this mismatch error is very small and will not affect the radar's normal angle measurement function. However, even a slight change can lead to a significant alteration in the target phase accuracy, severely impacting the monitoring of bridge deflection. Removing the radar and recalibrating it in an anechoic chamber would incur high economic costs and render the equipment inoperable during the process.

[0037] To address the aforementioned issues, embodiments of this application provide a calibration method, system, electronic device, and storage medium for bridge deflection monitoring.

[0038] Figure 2 The figure shows a calibration method for bridge deflection monitoring provided by an embodiment of the present invention, including:

[0039] S101. Obtain the total number of targets to be monitored installed on the bridge, the calibration parameters and factory calibration coefficients of each target, and obtain the first new calibration coefficients generated after the millimeter-wave radar and all targets are installed and calibrated.

[0040] S102. Acquire radio frequency data from the millimeter-wave radar and process the radio frequency data to obtain 2D data;

[0041] S103. Generate point cloud targets using 2D data and factory calibration coefficients;

[0042] S104. Match the corresponding point cloud target for each target using the calibration parameters of each target;

[0043] S105. Calculate the angular spectrum phase for each target to be detected that matches the point cloud target using 2D data, calibration parameters, and the first new calibration coefficient.

[0044] S106. Calculate the deflection value of each target to be tested using the angular spectrum phase.

[0045] In step S101, the target to be tested is the angular reflector. When monitoring the bridge deflection, the angular reflector changes very little with the bridge vibration displacement and can be approximated as stationary. The total number of targets to be tested is N, where N is an integer greater than 1. The calibration parameters include the angle parameters of the target after the millimeter-wave radar and the target are installed and calibrated, the distance between the target and the radar, and other parameters. The factory calibration coefficient is the calibration coefficient of the radar when it leaves the factory.

[0046] In step S102, the radio frequency data is ADC data, and the radio frequency data is processed by 2D FFT processing, that is, FFT operation is performed along the distance dimension and the Doppler dimension respectively.

[0047] In step S104, the calibration parameters include distance information, angle information, etc. If the point cloud target satisfies the distance information, angle information, etc. represented by the calibration parameters, the point cloud target is considered as a target target.

[0048] In some embodiments, the step of obtaining the first new calibration coefficient generated after the millimeter-wave radar and all targets are installed and calibrated includes: determining whether the first new calibration coefficient corresponding to the nth target to be detected exists; if it exists, the first new calibration coefficient is read into memory, and n=n+1 is set to obtain the first new calibration coefficient corresponding to the next monitoring target, until n is not less than the total number of targets to be detected.

[0049] In this embodiment, the first calibration coefficient is automatically generated after the radar and target have been installed and calibrated, upon receiving a trigger command from the host computer. That is, each target to be detected should have a first new calibration coefficient. Each target and its corresponding first new calibration coefficient form a new calibration table, which is then saved as a file to generate a new calibration coefficient file. By obtaining the new calibration coefficient for each target, the channel data of each target can be calibrated during subsequent calibration processes, thus ensuring optimal angle measurement and phase accuracy for each target.

[0050] In some embodiments, the step of generating a point cloud target using the 2D data and the factory calibration coefficients includes:

[0051] The 2D data is subjected to constant false alarm rate (CFAR) processing to obtain the first processed data;

[0052] The antenna channel of the millimeter-wave radar is calibrated based on the factory calibration coefficients.

[0053] Using the first processed data and the calibrated antenna channel, perform an angular dimension FFT to obtain the point cloud target.

[0054] In this embodiment, the 2D data is generated from the data of all targets. Therefore, in the point cloud targets obtained by processing the 2D data, each point cloud target should have a corresponding target.

[0055] In some embodiments, the step of matching each target with a corresponding point cloud target using the calibration parameters of each target includes:

[0056] Determine whether the target in the point cloud has a matching target. If not, iterate through a predetermined number of targets to obtain the point cloud target that matches the current target.

[0057] In this embodiment, by matching point cloud targets with targets, the calibration coefficient of each target can be calibrated in subsequent calculations, and no target will be missed.

[0058] In some embodiments, the step of calculating the angular spectrum phase of each target to be detected that matches the point cloud target using the 2D data, the calibration parameters, and the first new calibration coefficient includes:

[0059] Determine if a command to generate a new calibration table has been received;

[0060] If received, a new calibration table is generated based on the 2D data and saved as a new calibration file;

[0061] Calibration is performed based on the new calibration table, and angular-dimensional FFT is performed according to the calibration parameters to calculate the angular spectrum phase of the target.

[0062] Determine whether the step of traversing the predetermined number of targets has been completed. If completed, execute the step of calculating the deflection value of each target to be detected using the angular spectrum phase, until the step of traversing the predetermined number of targets is completed.

[0063] In this embodiment, the command to generate a new calibration table, that is, the command to calibrate the first new calibration coefficient, can calibrate the first calibration coefficient of each target by traversing through the table.

[0064] In some embodiments, the calibration method for bridge deflection monitoring further includes:

[0065] After determining whether a command to generate a new calibration table has been received, if no command has been received, it is determined whether a first new calibration coefficient exists. If a first new calibration coefficient exists, the step of calibrating based on the new calibration table and performing an angle-dimensional FFT according to the calibration parameters to calculate the angular spectrum phase of the target is directly executed. If a first new calibration coefficient does not exist, the step of determining whether the traversal of the predetermined number of targets has been completed is executed until the traversal of the predetermined number of targets is completed.

[0066] In this embodiment, if no command is received, it's because commands to generate new calibration coefficients are typically only sent during installation and when data quality deteriorates after prolonged device operation. Commands to generate new calibration coefficients are not sent every time; therefore, in some cases, a command to generate a new calibration table will not be received.

[0067] Furthermore, in this embodiment, the step of determining whether a first new calibration coefficient exists is to check whether the radar has already stored the new calibration coefficient (previously generated) if no command to generate a new calibration coefficient is received. If a generation command is received, the first new calibration coefficient will be regenerated, overwriting the previously generated first new calibration coefficient. It should be noted that there are two types of calibration coefficients in this embodiment: one is the factory calibration coefficient, which is generated during the radar's manufacturing process and is guaranteed to exist; the other is the first new calibration coefficient, which is generated upon receiving a command and can be overwritten.

[0068] In the step where a first new calibration coefficient does not exist, the angle spectrum phase is also obtained when calculating the angle using the factory calibration coefficient. If there is no new calibration coefficient, the angle spectrum phase value is used (equivalent to not using a new calibration scheme).

[0069] In some embodiments, the step of generating a new calibration table based on the 2D data includes:

[0070] Obtain the distance parameters and angle calibration parameters of the target in the 2D data;

[0071] The point cloud targets are matched according to the distance parameters and the angle calibration parameters, and the distance values ​​and Doppler index values ​​between the matched point cloud targets are obtained.

[0072] The complex data of the MIMO channel is obtained based on the distance value and the Doppler index value;

[0073] Select one channel of the millimeter-wave radar as a reference channel, and obtain the data of the reference channel as a reference value;

[0074] Acquire all channel data from the millimeter-wave radar and calculate the absolute values;

[0075] The phase compensation coefficient is calculated using the absolute value, the reference value, and the channel data used.

[0076] The absolute value of the phase compensation coefficient is calculated and the amplitude is normalized to obtain the first new calibration coefficient.

[0077] This embodiment describes the steps of calibrating the first calibration coefficient of a single target and generating the second calibration coefficient. The reference channel can be represented as T1R1, the reference value as ref, the channel data (including the reference channel) as cur, and the absolute value as abs. The formula is as follows:

[0078] pha_calib=(ref*conj(cur)) / abs (2)

[0079] The phase compensation coefficient pha_calib is obtained, where conj() represents the calculation of the conjugate operation on the complex number. In the step of calculating the first new calibration coefficient, the absolute value of the phase compensation coefficient pha_calib is cal_abs, and the formula for calculating the first new calibration coefficient calib is:

[0080] calib=pha_calib / cal_abs (3)

[0081] In the above embodiments, it should be noted that this scheme does not require an anechoic chamber environment. Instead, it utilizes a target (angle reflector) in the field environment to calibrate the antenna phase and amplitude of the millimeter-wave radar, generating new calibration coefficients. Here, the angle of the angle reflector is treated as zero degrees (the actual angle of the angle reflector may not be zero) for calibration. This way, it is only necessary to compensate the phase of the data from different channels to the same value and normalize the amplitude. Although this calibration method will cause the angle reflector measurement angle to become zero degrees, and the generated calibration coefficients are not applicable to targets with other angles, its angle spectrum signal-to-noise ratio will be significantly improved, and the angle spectrum phase accuracy will also be improved accordingly, which is beneficial to improving the bridge deflection monitoring effect.

[0082] To address the issue of the angle value becoming zero, the factory calibration coefficients of the radar are used to calculate the angle of reflection, while the angle spectrum phase value calculated using the new calibration coefficients is retained.

[0083] To ensure applicability to all targets, this solution calibrates all targets and maintains a set of calibration coefficients for each target. This ensures optimal accuracy of the angular phase measurement at each target point.

[0084] To more clearly illustrate the effects achievable by the embodiments of this application, practical verification has also been conducted, as follows:

[0085] Because this scheme can achieve optimal compensation for a single fixed target (point calibration can only provide optimal compensation at 0°, while linear calibration provides optimal estimation for the entire target), the angular spectrum signal-to-noise ratio of the target will be significantly improved after calibration using this scheme. In a real-world bridge deflection monitoring scenario, Figure 3 and 4 The figures show the phase curves of the target for the traditional scheme and the proposed scheme, respectively (horizontal axis corresponds to time, vertical axis corresponds to phase). It can be seen that the proposed scheme has a significant improvement in the angle spectrum signal-to-noise ratio (AngleSnr) compared to the traditional (old) calibration scheme (from 11dB to 17dB), and therefore the phase accuracy will also be improved accordingly, which is reflected in the more consistent and smooth phase curve on the left.

[0086] This solution can effectively improve the problem of increased phase noise caused by aging in the field. Figure 5This is a phase curve diagram of a bridge target (horizontal axis corresponds to time, vertical axis corresponds to phase). In the early stages of installation, the phase curve is relatively smooth, without... Figure 5 The image shows a burr phenomenon. After a considerable period of time, the burr noise shown in the image begins to appear. After calibration using this method, as shown... Figure 6 As shown, the phase glitch noise problem has been significantly improved.

[0087] In addition, to verify the universality of this solution, a bridge with abnormal deflection monitoring results was selected for verification. For example... Figure 7 and 8 As shown, the phase curve of the target is significantly improved after calibration using this method.

[0088] Please see Figure 9 The calibration system for bridge deflection monitoring provided in this application includes: a parameter acquisition module 1, a 2D data generation module 2, a point cloud target generation module 3, a matching module 4, an angle spectrum phase calculation module 5, and a deflection value calculation module 6.

[0089] The parameter acquisition module 1 is used to acquire the total number of targets to be monitored installed on the bridge, the calibration parameters and factory calibration coefficients of each target, and to acquire the first new calibration coefficients generated after the millimeter-wave radar and all targets are installed and calibrated.

[0090] The 2D data generation module 2 is used to acquire radio frequency data from millimeter-wave radar and process the radio frequency data to obtain 2D data;

[0091] Point cloud target generation module 3 is used to generate point cloud targets using the 2D data and the factory calibration coefficients;

[0092] The matching module 4 is used to match a corresponding point cloud target for each target using the calibration parameters of each target, wherein the calibration parameters include distance information and angle information;

[0093] The angle spectrum phase calculation module 5 is used to calculate the angle spectrum phase for each target to be detected that matches the point cloud target using the 2D data, the calibration parameters, and the first new calibration coefficient.

[0094] The deflection value calculation module 6 is used to calculate the deflection value of each target to be detected using the angular spectrum phase.

[0095] In some embodiments, the parameter acquisition module 1 includes: a first judgment unit and a first loop unit; the first judgment unit is used to determine whether the first new calibration coefficient corresponding to the nth target to be detected exists; the first loop unit is used to read the first new calibration coefficient into memory if the first new calibration coefficient exists, and set n=n+1 to obtain the first new calibration coefficient corresponding to the next monitoring target, until n is not less than the total number of targets to be detected.

[0096] In some embodiments, the point cloud target generation module 3 includes: a constant false alarm rate (CFAR) processing unit, an antenna channel calibration unit, and an angle-dimensional FFT processing unit; the CFAR processing unit is used to perform CFAR processing on the 2D data to obtain first processed data; the antenna channel calibration unit is used to calibrate the antenna channel of the millimeter-wave radar based on the factory calibration coefficient; the angle-dimensional FFT processing unit is used to perform angle-dimensional FFT using the first processed data and the calibrated antenna channel to obtain the point cloud target.

[0097] In some embodiments, the matching module 4 includes a second judgment unit, used to determine whether the target in the point cloud target has a matching target. If not, the target is traversed for a predetermined number of targets to obtain the point cloud target that matches the current target.

[0098] In some embodiments, the angle spectrum phase calculation module 5 includes: a third judgment unit, a new calibration table generation unit, a calibration unit, and a traversal unit; the third judgment unit is used to determine whether a command to generate a new calibration table has been received; the new calibration table generation unit is used to generate a new calibration table based on the 2D data and save it as a new calibration file if a command to generate a new calibration table has been received; the calibration unit is used to perform calibration based on the new calibration table and perform angle-dimensional FFT according to the calibration parameters to calculate the angle spectrum phase of the target; the traversal unit is used to determine whether the step of traversing a predetermined number of targets has been completed, and if completed, the step of calculating the deflection value of each target to be detected using the angle spectrum phase is executed until the traversal of the predetermined number of targets is completed.

[0099] In some embodiments, the calibration system for bridge deflection monitoring further includes: a logic judgment module, configured to, after the step of judging whether a command to generate a new calibration table has been received, if no command has been received, judge whether a first new calibration coefficient exists; if a first new calibration coefficient exists, directly execute the step of calibrating based on the new calibration table and performing an angle-dimensional FFT according to the calibration parameters to calculate the angular spectrum phase of the target; if a first new calibration coefficient does not exist, execute the step of judging whether the traversal of a predetermined number of targets has been completed, until the traversal of the predetermined number of targets is completed.

[0100] In some embodiments, the new calibration table generation unit includes: a parameter acquisition subunit, a point cloud target matching acquisition subunit, a channel complex data acquisition subunit, a reference channel selection subunit, an absolute value calculation subunit, a phase compensation coefficient calculation subunit, and a first new calibration coefficient calculation subunit;

[0101] The parameter acquisition subunit is used to acquire the distance parameters and angle calibration parameters of the target in the 2D data;

[0102] The point cloud target matching acquisition subunit is used to match the point cloud targets according to the distance parameter and the angle calibration parameter, and to acquire the distance value and Doppler index value between the matched point cloud targets;

[0103] The channel complex data acquisition subunit is used to acquire MIMO channel complex data based on the distance value and the Doppler index value;

[0104] The reference channel selection subunit is used to select one channel of the millimeter-wave radar as a reference channel and acquire the reference channel data as a reference value;

[0105] The absolute value calculation subunit is used to acquire all channel data of the millimeter-wave radar and calculate the absolute value;

[0106] The phase compensation coefficient calculation subunit is used to calculate the phase compensation coefficient using the absolute value, the reference value, and the channel data used.

[0107] The first new calibration coefficient calculation subunit is used to calculate the absolute value of the phase compensation coefficient and perform amplitude normalization to obtain the first new calibration coefficient.

[0108] This application provides an electronic device; please refer to [link / reference]. Figure 10 The electronic device includes a memory 601, a processor 602, and a computer program stored in the memory 601 and executable on the processor 602. When the processor 602 executes the computer program, it implements the bridge deflection monitoring method described above.

[0109] Furthermore, the electronic device also includes at least one input device 603 and at least one output device 604.

[0110] The aforementioned memory 601, processor 602, input device 603, and output device 604 are connected via bus 605.

[0111] The input device 603 can specifically be a camera, touch panel, physical buttons, or mouse, etc. The output device 604 can specifically be a display screen.

[0112] The memory 601 can be a high-speed random access memory (RAM) or a non-volatile memory, such as a disk storage device. The memory 601 is used to store a set of executable program code, and the processor 602 is coupled to the memory 601.

[0113] Furthermore, this application embodiment also provides a computer-readable storage medium, which may be disposed in the electronic device in the above embodiments, and may be the memory 601 in the foregoing embodiments. The computer-readable storage medium stores a computer program, which, when executed by the processor 602, implements the bridge deflection monitoring method described in the foregoing method embodiments.

[0114] Furthermore, the storage medium of this computer can also be a USB flash drive, a portable hard drive, a read-only memory (ROM), RAM, a magnetic disk, or an optical disk, or any other medium that can store program code.

[0115] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules 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 interfaces; the indirect coupling or communication connection between apparatuses or modules may be electrical, mechanical, or other forms.

[0116] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical modules; that is, they may be located in one place or distributed across multiple network modules. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0117] Furthermore, the functional modules in the various embodiments of the present invention can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module. The integrated modules described above can be implemented in hardware or as software functional modules.

[0118] If the integrated module is implemented as a software functional module and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, 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 storage medium and includes several instructions to cause a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention.

[0119] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that the present invention is not limited to the described order of actions, because according to the present invention, some steps can be performed in other orders or simultaneously. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to the present invention.

[0120] 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 of other embodiments.

[0121] In summary, although the present invention has been disclosed above with reference to preferred embodiments, the above preferred embodiments are not intended to limit the present invention. Those skilled in the art can make various modifications and refinements without departing from the spirit and scope of the present invention. Therefore, the scope of protection of the present invention shall be determined by the scope defined in the claims.

Claims

1. A calibration method for bridge deflection monitoring, characterized in that, include: Obtain the total number of targets to be monitored installed on the bridge, the calibration parameters and factory calibration coefficients of each target, and obtain the first new calibration coefficients generated after the millimeter-wave radar and all targets are installed and calibrated. Acquire radio frequency data from millimeter-wave radar and process the radio frequency data to obtain 2D data; Point cloud targets are generated using the 2D data and the factory calibration coefficients; Each target is matched with a corresponding point cloud target using the calibration parameters of each target, wherein the calibration parameters include distance information and angle information; Using the 2D data, the calibration parameters, and the first new calibration coefficient, the angular spectrum phase is calculated for each target to be detected that matches the point cloud target; The deflection value of each target to be detected is calculated using the angular spectrum phase.

2. The calibration method for bridge deflection monitoring as described in claim 1, characterized in that, The steps for obtaining the first new calibration coefficients generated after the millimeter-wave radar and all targets are installed and calibrated include: Determine whether the first new calibration coefficient corresponding to the nth target to be detected exists; If it exists, the first new calibration coefficient is read into memory, and n = n + 1 is set to obtain the first new calibration coefficient corresponding to the next monitoring target, until n is not less than the total number of targets to be detected.

3. The calibration method for bridge deflection monitoring as described in claim 1, characterized in that, The step of generating a point cloud target using the 2D data and the factory calibration coefficients includes: The 2D data is subjected to constant false alarm rate (CFAR) processing to obtain the first processed data; The antenna channel of the millimeter-wave radar is calibrated based on the factory calibration coefficients. Using the first processed data and the calibrated antenna channel, perform an angular dimension FFT to obtain the point cloud target.

4. The calibration method for bridge deflection monitoring as described in claim 1, characterized in that, The step of matching each target with a corresponding point cloud target using the calibration parameters of each target includes: Determine whether the target in the point cloud has a matching target. If not, iterate through a predetermined number of targets to obtain the point cloud target that matches the current target.

5. The calibration method for bridge deflection monitoring as described in claim 4, characterized in that, The step of calculating the angular spectrum phase for each target to be detected that matches the point cloud target using the 2D data, the calibration parameters, and the first new calibration coefficient includes: Determine if a command to generate a new calibration table has been received; If received, a new calibration table is generated based on the 2D data and saved as a new calibration file; Calibration is performed based on the new calibration table, and angular-dimensional FFT is performed according to the calibration parameters to calculate the angular spectrum phase of the target. Determine whether the step of traversing the predetermined number of targets has been completed. If completed, execute the step of calculating the deflection value of each target to be detected using the angular spectrum phase, until the step of traversing the predetermined number of targets is completed.

6. The calibration method for bridge deflection monitoring as described in claim 5, characterized in that, The calibration method for bridge deflection monitoring also includes: After determining whether a command to generate a new calibration table has been received, if no command has been received, it is determined whether a first new calibration coefficient exists. If a first new calibration coefficient exists, the step of calibrating based on the new calibration table and performing an angle-dimensional FFT according to the calibration parameters to calculate the angular spectrum phase of the target is directly executed. If a first new calibration coefficient does not exist, the step of determining whether the traversal of the predetermined number of targets has been completed is executed until the traversal of the predetermined number of targets is completed.

7. The calibration method for bridge deflection monitoring as described in claim 5, characterized in that, The step of generating a new calibration table based on the 2D data includes: Obtain the distance parameters and angle calibration parameters of the target in the 2D data; The point cloud targets are matched according to the distance parameters and the angle calibration parameters, and the distance values ​​and Doppler index values ​​between the matched point cloud targets are obtained. The complex data of the MIMO channel is obtained based on the distance value and the Doppler index value; Select one channel of the millimeter-wave radar as a reference channel, and obtain the data of the reference channel as a reference value; Acquire all channel data from the millimeter-wave radar and calculate the absolute values; The phase compensation coefficient is calculated using the absolute value, the reference value, and the channel data used. The absolute value of the phase compensation coefficient is calculated and the amplitude is normalized to obtain the first new calibration coefficient.

8. A calibration system for bridge deflection monitoring, characterized in that, include: The parameter acquisition module is used to acquire the total number of targets to be monitored installed on the bridge, the calibration parameters and factory calibration coefficients of each target, and to acquire the first new calibration coefficients generated after the millimeter-wave radar and all targets are installed and calibrated. A 2D data generation module is used to acquire radio frequency data from millimeter-wave radar and process the radio frequency data to obtain 2D data. A point cloud target generation module is used to generate point cloud targets using the 2D data and the factory calibration coefficients; The matching module is used to match a corresponding point cloud target for each target using the calibration parameters of each target, wherein the calibration parameters include distance information and angle information; An angular spectrum phase calculation module is used to calculate the angular spectrum phase of each target to be detected that matches the point cloud target using the 2D data, the calibration parameters, and the first new calibration coefficient. The deflection value calculation module is used to calculate the deflection value of each target to be detected using the phase of the angular spectrum.

9. An electronic device comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, when the processor executes the computer program, it implements the method of any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the method of any one of claims 1 to 7.

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