A method and system for calibrating the pointing of a shaped antenna cover based on quartic interpolation iteration
By employing a calibration method based on quartic interpolation iteration, we can perform grid subdivision and regional calibration on irregularly shaped radomes, thus solving the problems of low efficiency and accuracy of traditional calibration methods in irregularly shaped radome scenarios and achieving a highly efficient and accurate calibration process.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- UNIV OF ELECTRONICS SCI & TECH OF CHINA
- Filing Date
- 2026-02-28
- Publication Date
- 2026-06-02
AI Technical Summary
Traditional calibration and testing of phased array antennas with radomes is inefficient in irregular radome scenarios and cannot accurately capture local nonlinear distortions. Existing calibration technologies cannot meet the requirements for efficient and accurate calibration.
A calibration method based on quartile interpolation iteration is adopted, which achieves efficient subdivision and accurate calibration of grid cells by initializing grid division, iterative subdivision using quartile interpolation algorithm, constructing second-order polynomial fitting function, calculating fitting residual and calibrating by region.
It improves testing accuracy and reduces testing time, while also increasing testing efficiency while ensuring calibration accuracy. In particular, it achieves a more efficient calibration process by automatically encrypting in high distortion areas and sparsely sampling in low distortion areas.
Smart Images
Figure CN122131029A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of phased array antenna technology, and in particular to a method and system for calibrating the pointing of irregular radomes based on quartic interpolation iteration. Background Technology
[0002] Because the radome affects the phased array scanning at different angles differently, it is necessary to calibrate the phased array antenna with the radome separately at different angles. Traditional calibration and testing of phased array antennas with radomes uses a calibration technique based on the rotation vector method. During calibration, a fixed step (such as 2°) is often used for wave position grid division, which leads to low testing efficiency in irregular radome scenarios and cannot accurately capture local nonlinear distortions. Summary of the Invention
[0003] The purpose of this invention is to provide a method and system for calibrating the pointing of irregular radomes based on quartic interpolation iteration, so as to solve the problems mentioned in the background art.
[0004] To achieve the above objectives, this invention provides a method for calibrating the pointing of irregularly shaped radomes based on quartic interpolation iteration, comprising the following steps: Including the following steps: S1. Initialize the test area of the irregular radome and set the initial wave position grid step; S2. Based on the initial wave position grid stepping, the test area is divided into multiple initial grid cells; S3. For each initial grid cell, iterative subdivision is performed using a quartile interpolation algorithm, including: S31. Collect amplitude and phase response data within the current grid cell based on preset sampling points; S32. Based on the amplitude and phase response data, construct a second-order polynomial fitting function and calculate the fitting residual of each sampling point relative to the fitting surface; S33. If the fitting residual is greater than the first preset threshold, the current grid cell is divided into four sub-grid cells, and steps S31-S33 are repeated for each sub-grid cell; if the fitting residual is less than or equal to the first preset threshold, the iteration is stopped, the current grid cell is marked as a valid calibration cell, and the iteration depth is recorded. S34. Traverse all grid cells until the maximum iteration depth is reached or the convergence condition is met; S4. Based on the fitting residuals and iteration depth of the subdivided grid cells, the test area is calibrated. S5. Obtain the calibration data of all grid cells and construct a calibration table based on the calibration data of all calibrated grid cells.
[0005] Preferably, in step S1, the initial wave position grid step range is 10°-16°.
[0006] Preferably, in step S2, the test area is divided into multiple initial grid cells according to the azimuth and elevation angles, wherein the grid cells are rectangular, and the range of values for the azimuth and elevation angles is determined according to the installation attitude of the radome under test.
[0007] Preferably, step S31 involves selecting the four vertices and the center point of the grid cell as sampling points to collect amplitude and phase response data within the current grid cell.
[0008] Preferably, step S32 specifically includes: S321. Construct a second-order polynomial fitting function. Based on the second-order polynomial fitting function, perform least-squares fitting on the amplitude and phase response data of each sampling point to generate a local fitting surface. The formula for the second-order polynomial fitting surface is: ; In the formula, Indicates azimuth. Indicates pitch angle, , , , , , They represent the fitting coefficients, respectively; S322. Calculate the root mean square of the difference between the measured values of all sampling points and the predicted values of the local fitting surface, as the fitting residual. The formula for calculating the fitting residual is: ; In the formula, This represents the fitted residual value. Indicates the first The measured amplitude and phase values at each sampling point Indicates the number of sampling points. This represents the predicted value calculated by the second-order polynomial function.
[0009] Preferably, the calibration of the test area in step S4 specifically includes: S41. Obtain the iterative depth data and fitting parameter data of the subdivided grid cells; S42. Based on the iteration depth after subdivision and the fitting residual calculated in step S42, the calibration region is divided into low distortion region, medium distortion region and high distortion region, and calibration is performed in different regions according to the degree of distortion.
[0010] Preferably, step S42 specifically includes: When the fitting residual is less than or equal to the first preset threshold and the iteration depth is less than or equal to the first depth threshold, it is determined to be a low distortion region and a bilinear interpolation algorithm is used for calibration. When the first preset threshold < fitting residual ≤ second preset threshold, and the iteration depth ≤ first depth threshold, it is determined to be a medium distortion region, and high-order polynomial fitting or spline interpolation algorithm is used for calibration. When the fitting residual > the second preset threshold or the iteration depth > the first depth threshold, it is determined to be a high distortion region. The high distortion region is further subdivided into four sub-grid units. For each sub-grid unit, the four-part interpolation algorithm is used for iterative subdivision, and regional calibration is performed based on the subdivided grid units. The second preset threshold is greater than the first preset threshold.
[0011] The present invention also provides a non-standard radome pointing calibration system based on quartic interpolation iteration, including a control center, a data acquisition module, a region division module, a grid subdivision module and a calibration module; The data acquisition module is used to acquire the amplitude and phase response data of the irregular radome. It includes an FPGA hardware trigger module, a robotic arm, a vector network analyzer, a DAC signal generator, a high-precision turntable, and the phased array antenna under test. The control center, robotic arm, vector network analyzer, DAC signal generator, high-precision turntable, and microwave probe are connected to the FPGA hardware trigger module through a hardware trigger bus. The phased array antenna under test is equipped with an irregular radome at its front end and is mounted on the high-precision turntable. The control center is used to control the equipment in the data acquisition module; The region division module is used to divide the test area into multiple initial grid cells; The mesh subdivision module subdivides each initial mesh cell using a quartile interpolation algorithm based on the acquired amplitude and phase response data. The calibration module calibrates the subdivided grid cells.
[0012] Preferably, the robotic arm is equipped with a microwave probe and a four-arm spiral receiving antenna at its end, and the robotic arm is connected to the vector network analyzer through the four-arm spiral receiving antenna.
[0013] Therefore, the present invention adopts the above-mentioned non-standard radome pointing calibration method and system based on quartic interpolation iteration. By iteratively subdividing the test area through the quartic interpolation algorithm, it achieves automatic encryption in high-risk areas and sparse sampling in low-risk areas, thereby improving the test accuracy while ensuring calibration accuracy.
[0014] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description
[0015] Figure 1 This is a flowchart of the method in Embodiment 1 of the present invention. Detailed Implementation
[0016] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, 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. The components of the embodiments of the present invention described and shown in the accompanying drawings can be arranged and designed in various different configurations, and therefore should not be construed as limiting the present invention.
[0017] Example 1 like Figure 1 As shown, this invention provides a method for calibrating the pointing of irregular radomes based on quartic interpolation iteration, including the following steps: S1. Initialize the test area of the irregular radome and set the initial spectral density grid step. The initial spectral density grid step range is 10°-16°.
[0018] S2. Based on the initial azimuth grid stepping, the test area is divided into multiple initial grid cells according to the azimuth and elevation angles. The grid cells are rectangular, and the azimuth angle... The angle between the projection onto the horizontal plane (XOY plane) and the reference axis (usually the X-axis) is given, and its value ranges from [value missing]. Pitch angle The angle between the vector and the horizontal plane (XOY plane) has a range of values. , Pointing towards the zenith (positive Z direction). Pointing towards the nadir (negative Z direction).
[0019] S3. For each initial grid cell, iterative subdivision is performed using a quartile interpolation algorithm, including: S31. Set the maximum iteration depth and minimum step size, where the maximum iteration depth is... minimum step size .
[0020] S32. Select the four vertices and the center point of the grid cell as sampling points to collect the amplitude and phase response data within the current grid cell.
[0021] S33. Based on the amplitude and phase response data, construct a second-order polynomial fitting function and calculate the fitting residual of each sampling point relative to the fitting surface, specifically including: S331. Construct a second-order polynomial fitting function. Based on the second-order polynomial fitting function, perform least-squares fitting on the amplitude and phase response data of each sampling point to generate a local fitting surface. The formula for the second-order polynomial fitting surface is: ; In the formula, Indicates azimuth. Indicates pitch angle, , , , , , These represent the fitting coefficients, which are calculated from the sampling point data of the current grid cell using the least squares method.
[0022] S332. Calculate the root mean square of the difference between the measured values of all sampling points and the predicted values of the local fitting surface, as the fitting residual. The formula for calculating the fitting residual is: ; In the formula, This represents the fitted residual value. Indicates the first The measured amplitude and phase values at each sampling point Indicates the number of sampling points. This represents the predicted value calculated by the second-order polynomial function.
[0023] S34. If the fitting residual is greater than the first preset threshold, the current grid cell is divided into four sub-grid cells, and steps S31-S33 are repeated for each sub-grid cell; if the fitting residual is less than or equal to the first preset threshold, the iteration is stopped, the current grid cell is marked as a valid calibration cell, and the iteration depth is recorded.
[0024] S35. Traverse all grid cells until the maximum iteration depth is reached or the convergence condition is met.
[0025] S4. Based on the fitting residuals and iteration depth of the subdivided grid cells, calibrate the test area. Specifically, this includes: S41. Obtain the iterative depth data and fitting parameter data of the subdivided grid cells; S42. Based on the iteration depth after subdivision and the fitting residual calculated in step S42, the calibration region is divided into low distortion, medium distortion, and high distortion regions, and calibration is performed according to the degree of distortion in each region. Specifically: When the fitting residual is less than or equal to the first preset threshold and the iteration depth is less than or equal to the first depth threshold, it is determined to be a low distortion region and a bilinear interpolation algorithm is used for calibration. When the first preset threshold < fitting residual ≤ second preset threshold, and the iteration depth ≤ first depth threshold, it is determined to be a medium distortion region, and high-order polynomial fitting or spline interpolation algorithm is used for calibration. When the fitting residual > the second preset threshold or the iteration depth > the first depth threshold, it is determined to be a high distortion region. The high distortion region is further subdivided into four sub-grid units. For each sub-grid unit, the four-part interpolation algorithm is used for iterative subdivision, and regional calibration is performed based on the subdivided grid units. The second preset threshold is greater than the first preset threshold.
[0026] S5. Obtain the calibration data of all grid cells and construct a calibration table based on the calibration data of all calibrated grid cells.
[0027] In this embodiment, a right-handed coordinate system is used for definition. Azimuth angle With counterclockwise as the positive direction (viewed from the positive Z-axis), pitch angle Upward is considered positive. It should be noted that, although this invention is preferably... This refers to the range of elevation angles, but in actual radome calibration tests, the elevation angle range can also be defined as [specific range missing] depending on the antenna's mounting orientation. As long as the sampling points cover the effective beam range of the radome under test, it is sufficient.
[0028] Example 2 This invention also provides a non-standard radome pointing calibration system based on quartic interpolation iteration, including a control center, a data acquisition module, a region division module, a mesh subdivision module, and a calibration module. The functions of each module are as follows: The control center is used to control the equipment in the data acquisition module.
[0029] The region division module is used to divide the test area into multiple initial grid cells.
[0030] The data acquisition module is used to acquire the amplitude and phase response data of the irregular radome. It includes an FPGA hardware trigger module, a robotic arm, a vector network analyzer, a DAC signal generator, a high-precision turntable, and the phased array antenna under test. The control center, robotic arm, vector network analyzer, DAC signal generator, high-precision turntable, and microwave probe are connected to the FPGA hardware trigger module through a hardware trigger bus. The phased array antenna under test is equipped with an irregular radome at its front end and is mounted on the high-precision turntable. The robotic arm is equipped with a microwave probe and a four-arm spiral receiving antenna at its end. The robotic arm is connected to the vector network analyzer through the four-arm spiral receiving antenna.
[0031] The mesh subdivision module subdivides each initial mesh cell using a quartile interpolation algorithm based on the acquired amplitude and phase response data. The calibration module calibrates the subdivided grid cells.
[0032] After the calibration task is issued, the test area is first divided into multiple initial grid cells using the area division module. At the same time, the control center generates instructions and outputs a unified trigger signal through the FPGA hardware trigger module, causing the high-precision turntable, robotic arm, signal generator, and network analyzer to start working simultaneously, avoiding amplitude and phase data distortion caused by timing deviations.
[0033] Then, the amplitude and phase response data of the irregular radome are acquired in real time. Specifically, the DAC signal generator generates an excitation signal with a preset frequency and power, which is input to the phased array antenna under test mounted on a high-precision turntable. The phased array antenna radiates electromagnetic waves through the irregular radome at its front end. Due to the irregular structure of the radome, the propagation path of the electromagnetic waves is distorted, and the amplitude and phase characteristics are changed. The four-arm helical receiving antenna at the end of the robotic arm captures the electromagnetic waves after the distortion by the radome and transmits them to the vector network analyzer. The network analyzer performs amplitude comparison between the received signal and the excitation signal, outputs the amplitude and phase response data (amplitude attenuation and phase shift) under this attitude, and feeds it back to the control center for storage. The robotic arm can adjust its spatial position relative to the four-arm helical antenna using a microwave probe.
[0034] Finally, based on the acquired amplitude and phase data, the data is subdivided using a quartile interpolation algorithm, and then calibrated according to the subdivided grid cells.
[0035] Example 3 Calibration was performed using a biconical radome (front section of a hypersonic vehicle). The initial wavefront grid step was 16°, and the test area was [missing information]. The maximum iteration depth is 4 and the minimum step size is 1°. The calibration results are shown in Table 1.
[0036] Table 1 Calibration Results
[0037] Compared with traditional methods, which require 8100 points for a 1° positioning step of the wave position grid, the method of this invention saves 46% of the testing time while achieving better error accuracy.
[0038] Therefore, the present invention adopts the above-mentioned non-standard radome pointing calibration method and system based on quartic interpolation iteration. By iteratively subdividing the test area through the quartic interpolation algorithm, it achieves automatic encryption in high-risk areas and sparse sampling in low-risk areas, thereby improving the test accuracy while ensuring calibration accuracy.
[0039] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the technical solutions of the present invention, and these modifications or equivalent substitutions cannot cause the modified technical solutions to deviate from the spirit and scope of the technical solutions of the present invention.
Claims
1. A pointing calibration method for irregularly shaped radomes based on quartic interpolation iteration, characterized in that, Including the following steps: S1. Initialize the test area of the irregular radome and set the initial wave position grid step; S2. Based on the initial wave position grid stepping, the test area is divided into multiple initial grid cells; S3. For each initial grid cell, iterative subdivision is performed using a quartile interpolation algorithm, including: S31. Collect amplitude and phase response data within the current grid cell based on preset sampling points; S32. Based on the amplitude and phase response data, construct a second-order polynomial fitting function and calculate the fitting residual of each sampling point relative to the fitting surface; S33. If the fitting residual is greater than the first preset threshold, the current grid cell is divided into four sub-grid cells, and steps S31-S33 are repeated for each sub-grid cell; if the fitting residual is less than or equal to the first preset threshold, the iteration is stopped, the current grid cell is marked as a valid calibration cell, and the iteration depth is recorded. S34. Traverse all grid cells until the maximum iteration depth is reached or the convergence condition is met; S4. Based on the fitting residuals and iteration depth of the subdivided grid cells, the test area is calibrated. S5. Obtain the calibration data of all grid cells and construct a calibration table based on the calibration data of all calibrated grid cells.
2. The method for calibrating the pointing of an irregular radome based on quartic interpolation iteration according to claim 1, characterized in that: In step S1, the initial wave position grid step range is 10°-16°.
3. The method for calibrating the pointing of an irregular radome based on quartic interpolation iteration according to claim 1, characterized in that: In step S2, the test area is divided into multiple initial grid cells based on the azimuth and elevation angles. The grid cells are rectangular, and the range of values for the azimuth and elevation angles is determined based on the installation attitude of the radome under test.
4. The method for calibrating the pointing of an irregular radome based on quartic interpolation iteration according to claim 1, characterized in that: Step S31 involves selecting the four vertices and the center point of the grid cell as sampling points to collect amplitude and phase response data within the current grid cell.
5. The method for calibrating the pointing of an irregular radome based on quartic interpolation iteration according to claim 1, characterized in that, Step S32 specifically includes: S321. Construct a second-order polynomial fitting function. Based on the second-order polynomial fitting function, perform least-squares fitting on the amplitude and phase response data of each sampling point to generate a local fitting surface. The formula for the second-order polynomial fitting surface is: ； In the formula, Indicates azimuth. Indicates pitch angle, , , , , , They represent the fitting coefficients, respectively; S322. Calculate the root mean square of the difference between the measured values of all sampling points and the predicted values of the local fitting surface, as the fitting residual. The formula for calculating the fitting residual is: ； In the formula, This represents the fitted residual value. Indicates the first The measured amplitude and phase values at each sampling point Indicates the number of sampling points. This represents the predicted value calculated by the second-order polynomial function.
6. The method for calibrating the pointing of an irregular radome based on quartic interpolation iteration according to claim 4, characterized in that, The calibration of the test area in step S4 specifically includes: S41. Obtain the iterative depth data and fitting parameter data of the subdivided grid cells; S42. Based on the iteration depth after subdivision and the fitting residual calculated in step S42, the calibration region is divided into low distortion region, medium distortion region and high distortion region, and calibration is performed in different regions according to the degree of distortion.
7. The method for calibrating the pointing of an irregular radome based on quartic interpolation iteration according to claim 4, characterized in that, Step S42 specifically includes: When the fitting residual is less than or equal to the first preset threshold and the iteration depth is less than or equal to the first depth threshold, it is determined to be a low distortion region and a bilinear interpolation algorithm is used for calibration. When the first preset threshold < fitting residual ≤ second preset threshold, and the iteration depth ≤ first depth threshold, it is determined to be a medium distortion region, and high-order polynomial fitting or spline interpolation algorithm is used for calibration. When the fitting residual > the second preset threshold or the iteration depth > the first depth threshold, it is determined to be a high distortion region. The high distortion region is further subdivided into four sub-grid units. For each sub-grid unit, the four-part interpolation algorithm is used for iterative subdivision, and regional calibration is performed based on the subdivided grid units. The second preset threshold is greater than the first preset threshold.
8. A pointing calibration system for irregularly shaped radomes based on quartile interpolation iteration, comprising performing a pointing calibration method for irregularly shaped radomes based on quartile interpolation iteration as described in any one of claims 1-7, characterized in that: It includes a control center, a data acquisition module, a region division module, a grid subdivision module, and a calibration module; The data acquisition module is used to acquire the amplitude and phase response data of the irregular radome. It includes an FPGA hardware trigger module, a robotic arm, a vector network analyzer, a DAC signal generator, a high-precision turntable, and the phased array antenna under test. The control center, robotic arm, vector network analyzer, DAC signal generator, high-precision turntable, and microwave probe are connected to the FPGA hardware trigger module through a hardware trigger bus. The phased array antenna under test is equipped with an irregular radome at its front end and is mounted on the high-precision turntable. The control center is used to control the equipment in the data acquisition module; The region division module is used to divide the test area into multiple initial grid cells; The mesh subdivision module subdivides each initial mesh cell using a quartile interpolation algorithm based on the acquired amplitude and phase response data. The calibration module calibrates the subdivided grid cells.
9. The non-standard radome pointing calibration system based on quartic interpolation iteration according to claim 8, characterized in that: The robotic arm is equipped with a microwave probe and a four-arm spiral receiving antenna at its end, and the robotic arm is connected to a vector network analyzer through the four-arm spiral receiving antenna.