Method and apparatus for testing antenna parameters of a solar test weather radar

Abstract

This invention relates to the field of weather radar technology, and more particularly to a method and apparatus for testing weather radar antenna parameters using the sun. The method includes: controlling the radar to acquire scanning data in a preset sector volume scan mode, and identifying and processing the data to obtain a set of effective solar signals containing observed power, azimuth angle, and corrected true elevation angle; constructing and fitting a local quadratic surface model based on the deviation of the signal from the theoretical center of the sun to obtain model coefficients; and retrieving antenna parameters from the model coefficients: obtaining the true beamwidth from the quadratic coefficients after deconvolution correction, and calculating the antenna gain from the vertex power, the pre-input theoretical solar power, and the receiver link system constant. This method solves the technical problem of poor accuracy in the absolute calibration of weather radar antenna parameters using the sun.

Description

Technical Field

[0001] This invention relates to the field of weather radar technology, and in particular to a method and apparatus for testing the parameters of a weather radar antenna using the sun. Background Technology

[0002] The antenna system is the core component of the weather radar detection link. Its key electrical performance parameters, such as antenna gain, beamwidth, and beam pointing accuracy, directly determine the radar's ability to quantitatively measure precipitation systems and its positioning accuracy.

[0003] For a long time, the absolute calibration of radar antenna parameters has mainly relied on two traditional external methods: the standard gain method and the field beacon method. The standard gain method typically requires setting up a dedicated standard gain horn and associated tower in the radar's far-field region, calculating the antenna gain by measuring known transmitted or received signals. The field beacon method often uses tethered balloons or fixed towers to suspend metal spheres or corner reflectors of known radar cross-sections as calibration targets, achieving end-to-end system calibration by measuring their echo power. However, these methods have significant limitations: they usually require expensive far-field towers or the release of tethered balloons, and have extremely high requirements for site conditions, making such calibration exceptionally difficult and impractical to implement at operational radar stations located in complex terrain or urban areas.

[0004] In recent years, using the sun as a natural radio source for weather radar calibration has become a research hotspot. However, when the solar method is applied to the absolute calibration of antenna parameters for operational radar, the challenges in accuracy control are often coupled and complex. First, the extended source effect leads to an overestimation of beamwidth. If the sun is considered a point source, its finite size effect is not negligible relative to the weather radar beamwidth. If this size effect is ignored, the beamwidth obtained by direct Gaussian fitting will be significantly larger than the true value of the antenna. Second, dynamic scanning introduces beam distortion. To obtain high-resolution sampled data, the antenna is usually in a state of continuous rotating oversampling. The integration effect of the signal processor will cause a "scan tail" phenomenon in the azimuth beam, resulting in asymmetric broadening of the inversion results. Third, the low signal-to-noise ratio environment increases the difficulty of sample identification. The intrinsic strength of the solar signal received by the radar is low, and the low elevation angle observation path is susceptible to contamination and interference from ground clutter and atmospheric multipath effects.

[0005] These three factors are intertwined in operational radar, causing a significant increase in systematic errors when directly transferring existing methods to this scenario. Therefore, there is an urgent need for a method and apparatus for testing weather radar antenna parameters using sunlight. Summary of the Invention

[0006] In view of the above-mentioned shortcomings and deficiencies of the prior art, the present invention provides a method and apparatus for testing the antenna parameters of a weather radar using the sun, which solves the technical problem of poor accuracy when using the sun to calibrate the antenna parameters of a weather radar.

[0007] To achieve the above objectives, the main technical solutions adopted by the present invention include: In a first aspect, the present invention provides a method for testing weather radar antenna parameters using the sun, comprising: The system acquires scanning data collected by weather radar in sector volume scan mode and identifies the set of valid solar signals from the scanning data. The sector volume scan mode is a sector volume scan mode that uses the theoretical position of the sun at the midpoint of the scan as the center of the scan target. Each valid solar signal includes: observed power value, observed azimuth angle, and true solar elevation angle. Based on the observed azimuth angle, the actual solar elevation angle, and the theoretical position of the sun, the azimuth and elevation deviations of each effective solar signal relative to the theoretical center of the sun are determined. Using the azimuth and elevation deviations as independent variables and the observed power value as the dependent variable, a local quadratic surface model is constructed based on the set of effective solar signals to obtain the model coefficients. Based on the model coefficients, parameter inversion is performed: the apparent beamwidth of the weather radar is determined based on the quadratic coefficients of the local quadric surface model, and the apparent beamwidth is deconvolved to correct for solar spread source effect and scanning tail effect, so as to obtain the true beamwidth of the weather radar; the antenna gain of the weather radar is inverted based on the vertex power of the local quadric surface model, the pre-input solar theoretical power, and the receiver link system constant of the weather radar.

[0008] Optionally, the apparent beamwidth of the weather radar includes the apparent beamwidth in the azimuth direction and the apparent beamwidth in the elevation direction. The apparent beamwidth is deconvoluted to compensate for solar spread source effects and scanning tail effects. This includes: determining the Gaussian equivalent half-power width of the solar radio disk based on the effective radio diameter of the sun; determining the equivalent half-power width of the scanning tail based on the antenna scanning angular displacement during radar integration of a single radial sample; correcting the apparent beamwidth in the azimuth direction based on the principle of variance additivity under Gaussian equivalence, using the equivalent half-power width of the solar radio disk and the equivalent half-power width of the scanning tail, to obtain the true beamwidth in the azimuth direction; and correcting the apparent beamwidth in the elevation direction based on the principle of variance additivity under Gaussian equivalence, using the equivalent half-power width of the solar radio disk, to obtain the true beamwidth in the elevation direction.

[0009] Optionally, based on the vertex power of the local quadratic surface model, the pre-input theoretical solar power, and the receiver link system constant of the weather radar, the antenna gain of the weather radar is inverted, expressed by the following formula: ; in, Antenna gain; The vertex power is the peak power observed when the center of the antenna's main lobe is pointed directly at the sun. Theoretical solar power; and Here are the system constants of the receiver link for the weather radar. For receiver gain, This refers to the losses in the feeder and receiving branches.

[0010] Optionally, the parameter inversion based on the model coefficients also includes: inverting the beam pointing deviation of the weather radar antenna main lobe in the azimuth and elevation directions based on the vertex coordinates of the local quadratic surface model.

[0011] Optionally, a local quadric surface model, expressed by the formula: ; in, The fitted smooth power is given by x, which is the azimuth deviation of the effective solar signal relative to the theoretical center of the sun; and y is the elevation deviation of the effective solar signal relative to the theoretical center of the sun. , , , , These are the model coefficients; Based on the vertex coordinates of the local quadric surface model, the beam pointing deviation of the weather radar antenna main lobe in the azimuth and elevation directions is retrieved, including: determining the beam pointing deviation in the azimuth direction based on the condition that the first derivative of the local quadric surface model is zero. Beam pointing deviation in the pitch direction The formula is expressed as: ; .

[0012] Optionally, the process of constructing a quadratic surface model includes: A1. Use the current sample set to perform local quadratic surface fitting to obtain the surface model under the current iteration; the current sample set under the first iteration is the set of valid solar signals; A2. Based on the surface model, determine the fitting residual between the observed power and the model fitting power of each sample in the current sample set, and determine the current residual standard deviation based on all fitting residuals; A3. Compare the absolute value of the fitting residual of each sample with the first threshold, which is the product of the preset elimination factor and the current standard deviation of the residual. Retain samples whose absolute value of the fitting residual does not exceed the first threshold to form an updated sample set. A4. Determine whether the rate of change of the current residual standard deviation from the residual standard deviation of the previous iteration is less than the preset second threshold. If yes, use the surface model obtained in the current iteration as the final local quadratic surface model. If no, use the updated sample set as the new current sample set and return to step A1 for the next iteration.

[0013] Optionally, identifying a set of valid solar signals from the scanned data includes: identifying solar signals from the scanned data; performing unit conversion and filtering on each solar signal to obtain a preprocessed solar signal expressed as a received power value; for each preprocessed solar signal, performing atmospheric refraction correction on the observation elevation angle when the radar observes the sun to obtain the true solar elevation angle; and compensating for the solar energy attenuated by gas absorption in the propagation path by the received power to obtain the radar's observation power; the true solar elevation angle and the observation power constitute the data of valid solar signals.

[0014] Optionally, the sector volume scan mode is the VCPSun mode, with an azimuth coverage range of ±5° centered on the theoretical position of the sun and an azimuth resolution of 0.25°; and an elevation coverage range of ±1.0° centered on the theoretical position of the sun.

[0015] Optionally, the effective solar signal set is identified from the scan data, including identifying the effective solar signal subsets of horizontal polarization and vertical polarization from the scan data of the horizontal polarization channel and the vertical polarization channel, respectively. The process involves constructing a local quadratic surface model, obtaining model coefficients, and performing parameter inversion, including performing the inversion on the horizontal and vertical polarization subsets respectively to obtain the antenna parameters for the horizontal and vertical polarization channels.

[0016] In a second aspect, the present invention provides an apparatus for testing the parameters of a weather radar antenna using the sun, comprising a memory, a processor, and a program for testing the parameters of a weather radar antenna using the sun stored in the memory and executable on the processor. When the processor executes the program for testing the parameters of a weather radar antenna using the sun, it implements the method for testing the parameters of a weather radar antenna using the sun as described above.

[0017] The beneficial effects of this invention are: This invention provides a method for testing weather radar antenna parameters using the sun. Through sector volume scanning, it can acquire high-density azimuth-elevation two-dimensional samples near the theoretical position of the sun, laying a data foundation for subsequent high-precision inversion. Based on a unified modeling technique for the main lobe response characteristics using two-dimensional Gaussian surface fitting, stable inversion of beam pointing deviations in the H and V polarization channels is achieved without significant main lobe center separation. By applying Gaussian equivalent deconvolution correction to the apparent beamwidth for solar spread source effects and scanning tail effects, the system measurement error is significantly reduced. In experimental tests, the antenna gain results obtained by this method exhibit good repeatability and reliability, with absolute deviations all less than 0.2 dB. Overall, this method can achieve in-situ quantitative measurement of key parameters of operational weather radar without relying on dedicated far-field beacons or complex field test conditions. As a low-cost and scalable technical approach, it can effectively support antenna parameter calibration, network consistency evaluation, and long-term performance monitoring of operational radar sites under complex terrain conditions. Attached Figure Description

[0018] Figure 1 This is a flowchart of a method for testing key parameters of a weather radar antenna using the sun, according to Example 1. Figure 2 A 5-minute time series of horizontal polarization beam azimuth and elevation pointing deviations; Figure 3 A 5-minute time series of vertically polarized beam azimuth and elevation pointing deviations; Figure 4 Hourly boxline statistics for the apparent beamwidth of horizontal polarization; Figure 5 Hourly boxline statistics for apparent beamwidth of vertical polarization; Figure 6 Hourly boxline statistics for the true beamwidth of horizontal polarization; Figure 7 Hourly boxline statistics for the true beamwidth of vertical polarization; Figure 8 This is a 5-minute time series of antenna gain retrieved by the horizontal / vertical polarization solar method. Detailed Implementation

[0019] To better explain and facilitate understanding of the present invention, it will be described in detail below with reference to the accompanying drawings and specific embodiments. While exemplary embodiments of the invention are shown in the drawings, it should be understood that the invention can be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided to enable a clearer and more thorough understanding of the invention and to fully convey the scope of the invention to those skilled in the art.

[0020] Example 1.

[0021] Figure 1 This is a flowchart of the method for testing key parameters of a weather radar antenna using the sun in Example 1.

[0022] like Figure 1 As shown, the method for testing key parameters of a weather radar antenna using solar energy includes the following steps: Step S1: Acquire the scanning data collected by the weather radar in sector volume scan mode, and identify the set of valid solar signals from the scanning data.

[0023] The sector volume scan mode uses the theoretical position of the sun at the midpoint of the scan as the center of the scanning target. Further, the sector volume scan mode is the VCPSun mode, with an azimuth coverage range of ±5° centered on the theoretical position of the sun and an azimuth resolution of 0.25°; and an elevation coverage range of ±1.0° centered on the theoretical position of the sun, employing an oversampling step size superior to that of conventional operational volume scans. In this mode, the radar performs high-density sampling with the goal of acquiring solar main lobe samples, providing a data foundation for subsequent high-precision inversion.

[0024] Each valid solar signal includes: the observed power value, the observed azimuth angle, and the true solar elevation angle.

[0025] Preferably, identifying the set of valid solar signals from the scanned data includes: identifying preliminary solar signals from the scanned data; performing unit conversion and filtering on each preliminary solar signal to obtain a preprocessed solar signal expressed as a received power value; for each preprocessed solar signal, performing atmospheric refraction correction on the observation elevation angle when the radar observes the sun to obtain the true solar elevation angle; and compensating the received power for the solar energy attenuated by gas absorption in the propagation path to obtain the radar's observation power; the true solar elevation angle and the observation power constitute the data of valid solar signals.

[0026] In the acquired scan data, solar signals typically appear as continuous radial stripes extending along a specific azimuth. Using radial beams as the basic discrimination unit, automatic identification can be performed by leveraging the continuous characteristics of solar signals in geometric space and time. Specifically, identifying the initial solar signal from the scan data includes: determining the nth radial beam. Does it meet the condition of falling within the solar main lobe region? If so, it is identified as a preliminary solar signal. The formula is expressed as: ; in, The percentage of effective radial data; As the percentage threshold, it is usually set to about 3 times the beamwidth to ensure that the main lobe region is completely captured; and These are the azimuth and elevation angles of the nth radial beam, respectively. and These are the elevation and azimuth angles of the theoretical position of the sun, respectively. and These are the tolerance thresholds for azimuth and pitch deviations, respectively.

[0027] Since raw radar data is typically stored in dBZ format for reflectivity factors, and subsequent physical corrections and modeling require received power values, a unit conversion is performed on each solar signal using the meteorological radar equations to convert the reflectivity factor. Reconstructed to horizontally polarized received power The formula is expressed as: ; Where r is the distance; This is the single-pass gas attenuation coefficient; is the radar constant for horizontal polarization.

[0028] For single-polarization radar, its hardware system only has a horizontal polarization channel, so there is no need to collect, identify and process the solar echo signal of the vertical polarization channel. The reconstruction and inversion of the horizontal polarization received power described above is the complete process.

[0029] For dual-polarization radars, operational baseline data typically does not directly provide vertical polarization reflectivity factors and received power suitable for fitting the solar main lobe. To achieve unified modeling of the H and V polarization main lobe responses, based on the dual-polarization radar equations, the horizontal polarization received power obtained through inversion is used... Differential reflectivity And the difference in H / V polarization radar constants, reconstructing the equivalent received power of vertical polarization. The formula is expressed as: ; in, is the radar constant for vertical polarization.

[0030] To reduce near-field clutter and sidelobe contamination, iterative 3σ statistical filtering was used to remove discrete values ​​from the identified preliminary solar signals.

[0031] Considering that the sun is an extraterrestrial radiation source and its propagation path penetrates the atmosphere, physical corrections are needed to the preprocessed solar signals to improve the physical consistency of beam pointing inversion. Therefore, for each preprocessed solar signal, atmospheric refraction correction is performed on the observation elevation angle when the radar observes the sun to obtain the true solar elevation angle. The received power is then compensated for the solar energy attenuated by gas absorption in the propagation path to obtain the radar's observation power.

[0032] Specifically, atmospheric refraction correction is applied to the elevation angle of radar observations of the sun, expressed by the following formula: ; ; in, This is the true elevation angle; The viewing angle is at elevation. is the angle of refraction; k is the equivalent Earth radius coefficient; is the atmospheric refractive index at the Earth's surface.

[0033] Specifically, the energy attenuation of gas absorption in a single pass. The formula is expressed as: ; Where a is the equivalent gas ratio attenuation coefficient, in dB / km; This is the effective oblique path length of solar rays from radar to the top of the atmosphere.

[0034] Step S2: Based on the observed azimuth angle, the actual solar elevation angle, and the theoretical position of the sun, determine the azimuth deviation and elevation deviation of each effective solar signal relative to the theoretical center of the sun; using the azimuth deviation and elevation deviation as independent variables and the observed power value as the dependent variable, construct a local quadratic surface model based on the set of effective solar signals to obtain the model coefficients.

[0035] Define the azimuth angle actually measured by the radar and the true solar elevation angle after atmospheric refraction correction as: The theoretical position of the sun is .

[0036] To quantify the degree to which the solar signal deviates from the theoretical center, a local relative deviation coordinate system is established with the theoretical solar center as the origin. The specific coordinate transformation formula is as follows: ; .

[0037] In the azimuth-elevation plane, the main lobe power distribution of a weather radar antenna can typically be approximated as a two-dimensional Gaussian shape. To better handle potential asymmetry and edge attenuation during the fitting process, this invention represents the solar scan samples as a local quadratic surface model in the logarithmic power domain. The local quadratic surface model is expressed by the following formula: ; in, The fitted smooth power is given by x, which is the azimuth deviation of the effective solar signal relative to the theoretical center of the sun; and y is the elevation deviation of the effective solar signal relative to the theoretical center of the sun. , , , , These are the model coefficients.

[0038] Although step S1 has performed initial screening of solar signals, discrete outliers caused by radio frequency interference, ground object sidelobes, or birds may still remain in the data. Direct fitting would severely affect the estimation of surface opening, vertex position, and peak power. Therefore, an iterative quadratic surface robust filtering method based on residuals is used to fit the quadratic surface.

[0039] Specifically, the process of constructing a quadratic surface model includes: A1. Use the current sample set to perform local quadratic surface fitting to obtain the surface model under the current iteration; the current sample set under the first iteration is the set of valid solar signals; A2. Based on the surface model, determine the fitting residual between the observed power and the model fitting power of each sample in the current sample set, and determine the current residual standard deviation based on all fitting residuals; A3. Compare the absolute value of the fitting residual of each sample with the first threshold, which is the product of the preset elimination factor and the current standard deviation of the residual. Retain samples whose absolute value of the fitting residual does not exceed the first threshold to form an updated sample set. A4. Determine whether the rate of change of the current residual standard deviation from the residual standard deviation of the previous iteration is less than the preset second threshold. If yes, use the surface model obtained in the current iteration as the final local quadratic surface model. If no, use the updated sample set as the new current sample set and return to step A1 for the next iteration.

[0040] In this way, a high-precision solar power surface can be obtained for subsequent parameter inversion.

[0041] Step S3: Perform parameter inversion based on model coefficients: Based on the vertex coordinates of the local quadratic surface model, invert the beam pointing deviation of the weather radar antenna main lobe in the azimuth and elevation directions; Based on the quadratic coefficients of the local quadratic surface model, determine the apparent beamwidth of the weather radar, and perform deconvolution correction on the apparent beamwidth for solar spread source effect and scanning tail effect to obtain the true beamwidth of the weather radar; Based on the vertex power of the local quadratic surface model, the pre-input theoretical solar power, and the receiver link system constant of the weather radar, invert the antenna gain of the weather radar.

[0042] The vertex of the local quadric surface model corresponds to the center of the main lobe. Based on the condition that the first derivative of the local quadric surface model is zero, the beam pointing deviation in the azimuth direction can be determined. Beam pointing deviation in the pitch direction The formula is expressed as: ; .

[0043] This method determines the beam center based on the overall information of the two-dimensional main lobe, and is less sensitive to sparse sampling and local outliers than the single profile peak method.

[0044] The main lobe width observed by radar is the "apparent width" resulting from the convolution of the antenna's actual beamwidth, the finite solar disk, and the continuous scan integral. The actual beamwidth needs to be restored by deconvolving the apparent beamwidth to account for solar spread source effects and scan tail effects.

[0045] Specifically, the apparent beamwidth of a weather radar includes the apparent beamwidth in the azimuth direction and the apparent beamwidth in the elevation direction. Deconvolution correction of the apparent beamwidth for solar spread source effects and scanning tail effects is performed, including: determining the Gaussian equivalent half-power width of the solar radio disk based on the effective radio diameter of the sun; determining the equivalent half-power width of the scanning tail based on the antenna scanning angular displacement during a single radial sample integration; correcting the apparent beamwidth in the azimuth direction based on the principle of variance additivity under Gaussian equivalence, using the equivalent half-power widths of the solar radio disk and the scanning tail, to obtain the true azimuth beamwidth; and correcting the apparent beamwidth in the elevation direction based on the principle of variance additivity under Gaussian equivalence, using the equivalent half-power width of the solar radio disk, to obtain the true elevation beamwidth.

[0046] Furthermore, determining the apparent beamwidth of the weather radar includes: the quadratic coefficients based on the local quadratic surface model. and The apparent half-power beamwidth is determined in both the azimuth and elevation directions; wherein, the apparent beamwidth in the azimuth direction is... The calculation formula is: ; Pitch direction apparent beamwidth The calculation formula is: .

[0047] Furthermore, considering the sun as a two-dimensional uniform brightness disk, the Gaussian equivalent half-power width of the solar radio disk is determined. The formula is expressed as: ; in, The effective radio diameter of the sun.

[0048] Furthermore, the equivalent half-power width of the scan tail is determined. The formula is expressed as: ; in, This represents the antenna scanning angular displacement of the radar during a single radial sample integration.

[0049] Furthermore, based on the Gaussian equivalent half-power width of the solar radio disk and the equivalent half-power width of the scanning tail, the apparent beamwidth in the azimuth direction is calculated. The formula is modified and expressed as follows: ; Based on the Gaussian equivalent half-power width of the solar radio disk, the apparent beamwidth in the pitch direction is... The formula is modified and expressed as follows: .

[0050] The antenna gain inversion is based on the observed peak power when the main lobe center is aligned with the sun, and corrected by incorporating the pre-input theoretical solar power and the receiver link loss of the weather radar. Specifically, the antenna's peak power can be derived from the vertex power of the local quadratic surface model. The formula is given as follows: ; To avoid errors caused by inconsistencies in the reference planes for different power, gain, and loss terms, this paper unifies all quantities to the same reference plane. The relationship between the antenna peak power and the theoretical solar power term is then as follows: ; in, Can be taken as , Theoretical solar power; The antenna gain to be inverted; and Here are the system constants of the receiver link for the weather radar. For receiver gain, This refers to the losses in the feeder and receiving branches.

[0051] Therefore, the inversion yields: .

[0052] Specifically, the pre-input theoretical solar power is obtained through the following steps: Obtain the standard solar radio flux at a frequency of 2800 MHz .

[0053] Based on the radar's actual operating frequency f, and using the solar flux conversion formula, f is converted to... Solar flux converted to frequency.

[0054] For S-band weather radar, the solar flux conversion formula is as follows: , For S-band weather radar Solar flux converted to frequency; For C-band weather radar, the solar flux conversion formula is expressed as: , For C-band weather radar Solar flux converted to frequency; For X-band weather radar, the formula for converting solar flux is expressed as: , For X-band weather radar Solar flux converted to frequency.

[0055] According to the formula Determine the theoretical power of the sun in, This represents the flux density corresponding to solar flux. For radar operating wavelength, This is the receiver's equivalent noise bandwidth.

[0056] It should be noted that for dual-polarization radar, identifying the effective solar signal set from the scanning data includes identifying the effective solar signal subsets of horizontal polarization and vertical polarization from the scanning data of the horizontal polarization channel and the vertical polarization channel, respectively; constructing a local quadratic surface model, obtaining model coefficients, and performing parameter inversion, including performing the inversion on the horizontal polarization subset and the vertical polarization subset, respectively, to obtain the antenna parameters of the horizontal polarization channel and the vertical polarization channel.

[0057] Preferably, after performing parameter inversion, a polarization channel consistency verification step is also included: comparing the beam pointing deviation, actual beamwidth, and antenna gain obtained from the horizontal polarization and vertical polarization channel inversion; if the difference of any parameter exceeds the corresponding preset consistency tolerance, it is determined that there is a mismatch in the radar dual polarization channels, and an alarm message is output.

[0058] Preferably, the method provided in this embodiment further includes: continuously performing the antenna parameter tests as described above multiple times; and statistically obtaining the average value of the antenna parameters based on the results of multiple tests, thereby reducing the impact of the environment on the antenna parameter testing.

[0059] This invention provides a method for testing weather radar antenna parameters using the sun. Through sector volume scanning, it can acquire high-density azimuth-elevation two-dimensional samples near the theoretical position of the sun, laying a data foundation for subsequent high-precision inversion. Based on a unified modeling technique for the main lobe response characteristics using two-dimensional Gaussian surface fitting, stable inversion of beam pointing deviations in the H and V polarization channels is achieved without significant main lobe center separation. Furthermore, by introducing a residual-based iterative quadratic surface robust filtering method, high-frequency anomalies and local spikes superimposed on the smooth solar main lobe are effectively removed, preserving the overall geometric structure of the main lobe and significantly improving the stability of parameter inversion. Further, by applying Gaussian equivalent deconvolution correction to the apparent beamwidth for solar spread source effects and scanning tail effects, the system measurement error is significantly reduced. The antenna gain results obtained by this method exhibit good repeatability and reliability, with absolute deviations all less than 0.2 dB. Overall, this method can achieve in-situ quantitative measurement of key parameters of operational weather radar without relying on dedicated far-field beacons or complex field test conditions. As a low-cost and scalable technical approach, it can effectively support antenna parameter calibration, network consistency assessment and long-term performance monitoring of operational radar sites under complex terrain conditions.

[0060] Example 2.

[0061] This embodiment proposes an apparatus for testing weather radar antenna parameters using the sun, including a memory, a processor, and a program for testing weather radar antenna parameters using the sun stored in the memory and executable on the processor. When the processor executes the program for testing weather radar antenna parameters using the sun, it implements the method for testing weather radar antenna parameters using the sun as described in Embodiment 1 above.

[0062] The effect produced by the device for testing weather radar antenna parameters using the sun proposed in this embodiment is similar to that in Embodiment 1, and will not be repeated here.

[0063] Experimental testing.

[0064] To verify the actual performance of the method of this invention, a continuous observation experiment was conducted using the CINRAD / SA-D dual-polarization weather radar as the test object. The observation period was from 22:00 UTC on April 18, 2026 to 11:00 UTC on April 19, 2026. During the experiment, the radar periodically executed the VCPSun sector volume scan mode to acquire solar main lobe samples and simultaneously recorded the radar system status, such as transmit power, receiver gain, and ambient temperature, to ensure the continuity and traceability of the data.

[0065] Based on the scanning data acquired using the VCPSun mode, the beam pointing deviations of the radar in the azimuth and elevation directions were retrieved using the method described in Example 1. The results are as follows: Figure 2 and Figure 3 As shown. Figure 2 This is a 5-minute time series of azimuth and elevation pointing deviations of the horizontally polarized beam, where blue dots represent azimuth pointing deviations and red dots represent elevation pointing deviations. Figure 3 This is a 5-minute time series of azimuth and elevation pointing deviations of the vertically polarized beam, where blue dots represent azimuth pointing deviations and red dots represent elevation pointing deviations. Figure 2 and Figure 3 Statistical results show that the mean pointing deviation of the horizontally polarized azimuth beam is -0.04° with a standard deviation of 0.04°, and the mean pointing deviation of the horizontally polarized elevation beam is -0.01° with a standard deviation of 0.03°; the mean pointing deviation of the vertically polarized azimuth beam is -0.04° with a standard deviation of 0.04°, and the mean pointing deviation of the horizontally polarized elevation beam is -0.00° with a standard deviation of 0.03°. This indicates that the beam pointing accuracy inversion results have good repeatability. Furthermore, the beam center variation trends of the two polarization channels are highly consistent, demonstrating good consistency and the ability to reliably identify small pointing errors in CINRAD / SA-D weather radars.

[0066] The apparent beamwidths in the azimuth and elevation directions of the radar are obtained through inversion, and the results are as follows: Figure 4 and Figure 5 As shown. Figure 4 This is a box-line statistical result of the hourly apparent beamwidth for horizontal polarization. Figure 5 This is a box plot showing the hourly statistics of the apparent beamwidth for vertical polarization; the blue boxes represent the azimuth apparent beamwidth, the red boxes represent the pitch apparent beamwidth, and the red line within each box represents the median. Each box consists of 5-minute statistical results for the corresponding hour. Figure 4 and Figure 5 As can be seen, both the horizontally polarized and vertically polarized apparent beamwidths exhibit good time stability with small fluctuation amplitudes. The true beamwidths in the azimuth and elevation directions of the radar are retrieved, and the results are as follows: Figure 6 and Figure 7 As shown. Figure 6 This is a boxline statistical result for the hourly true beamwidth of horizontal polarization. Figure 7 This is a box plot showing the hourly statistical results of the true beamwidth for vertical polarization; the blue boxes represent the true beamwidth in the azimuth direction, the red boxes represent the true beamwidth in the elevation direction, and the red line within each box represents the median. Each box consists of 5-minute statistical results for the corresponding hour. Figure 6 and Figure 7As can be seen, after deconvolution correction, the beamwidth of horizontal / vertical polarization in both azimuth and elevation directions is systematically reduced compared to the apparent beamwidth, and the temporal variation trend before and after correction is basically the same. This indicates that the correction model mainly removes the system broadening caused by the solar disk and scan integration, without introducing obvious non-physical temporal fluctuations.

[0067] The antenna gain of the radar obtained by inversion is as follows: Figure 8 As shown. Figure 8 This is a 5-minute time series of antenna gains retrieved via the solar method for horizontal / vertical polarization. Blue dots represent horizontally polarized antenna gains, and green dots represent vertically polarized antenna gains. Figure 8 The mean gain of the horizontally polarized inverted antenna is 45.47 dB with a standard deviation of 0.29 dB; the mean gain of the vertically polarized antenna is 45.68 dB with a standard deviation of 0.28 dB. This indicates that the antenna gain has good repeatability and stability during the main observation period.

[0068] In the description of this invention, it should be understood that 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 number of indicated technical features. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0069] In this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," "linking," and "fixing," etc., should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0070] In this invention, unless otherwise explicitly specified and limited, "above" or "below" the second feature can mean that the first and second features are in direct contact, or that they are in indirect contact through an intermediate medium. Furthermore, "above," "over," or "on top" the second feature can mean that the first feature is directly above or diagonally above the second feature, or simply indicates that the first feature is at a higher horizontal level than the second feature. "Below," "below," or "beneath" the second feature can mean that the first feature is directly below or diagonally below the second feature, or simply indicates that the first feature is at a lower horizontal level than the second feature.

[0071] In the description of this specification, the terms "one embodiment," "some embodiments," "embodiment," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0072] Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make modifications, alterations, substitutions and variations to the above embodiments within the scope of the present invention.

Claims

1. A method for testing weather radar antenna parameters using the sun, characterized in that, include: The system acquires scanning data collected by weather radar in sector volume scan mode and identifies the set of valid solar signals from the scanning data. The sector volume scan mode is a sector volume scan mode that uses the theoretical position of the sun at the midpoint of the scan as the center of the scan target. Each valid solar signal includes: observed power value, observed azimuth angle, and true solar elevation angle. Based on the observed azimuth angle, the actual solar elevation angle, and the theoretical position of the sun, the azimuth and elevation deviations of each effective solar signal relative to the theoretical center of the sun are determined. Using the azimuth and elevation deviations as independent variables and the observed power value as the dependent variable, a local quadratic surface model is constructed based on the set of effective solar signals to obtain the model coefficients. Based on the model coefficients, parameter inversion is performed: the apparent beamwidth of the weather radar is determined based on the quadratic coefficients of the local quadratic surface model, and the apparent beamwidth is deconvolved to correct for solar spread source effect and scanning tail effect to obtain the true beamwidth of the weather radar; the antenna gain of the weather radar is inverted based on the vertex power of the local quadratic surface model, the pre-input solar theoretical power, and the receiver link system constant of the weather radar. The apparent beamwidth of the weather radar includes the apparent beamwidth in the azimuth direction and the apparent beamwidth in the elevation direction. The apparent beamwidth is deconvoluted to compensate for solar spread source effects and scanning tail effects. This includes: determining the Gaussian equivalent half-power width of the solar radio disk based on the effective radio diameter of the sun; determining the equivalent half-power width of the scanning tail based on the antenna scanning angular displacement during radar integration of a single radial sample; correcting the apparent beamwidth in the azimuth direction based on the principle of variance additivity under Gaussian equivalence, using the equivalent half-power width of the solar radio disk and the equivalent half-power width of the scanning tail, to obtain the true beamwidth in the azimuth direction; and correcting the apparent beamwidth in the elevation direction based on the principle of variance additivity under Gaussian equivalence, using the equivalent half-power width of the solar radio disk, to obtain the true beamwidth in the elevation direction.

2. The method for testing weather radar antenna parameters using the sun according to claim 1, characterized in that, Based on the vertex power of the local quadric surface model, the pre-input theoretical solar power, and the receiver link system constant of the weather radar, the antenna gain of the weather radar is inverted, expressed by the formula: ； in, Antenna gain; The vertex power is the peak power observed when the center of the antenna's main lobe is pointed directly at the sun. Theoretical solar power; and Here are the system constants of the receiver link for the weather radar. For receiver gain, This refers to the losses in the feeder and receiving branches.

3. The method for testing weather radar antenna parameters using the sun according to claim 1, characterized in that, Based on the model coefficients, parameter inversion is performed, which also includes: inverting the beam pointing deviation of the weather radar antenna main lobe in the azimuth and elevation directions based on the vertex coordinates of the local quadratic surface model.

4. The method for testing weather radar antenna parameters using the sun according to claim 3, characterized in that, The local quadric surface model is expressed by the following formula: ； in, The fitted smooth power is given by x, which is the azimuth deviation of the effective solar signal relative to the theoretical center of the sun; and y is the elevation deviation of the effective solar signal relative to the theoretical center of the sun. , , , , These are the model coefficients; Based on the vertex coordinates of the local quadric surface model, the beam pointing deviation of the weather radar antenna main lobe in the azimuth and elevation directions is retrieved, including: determining the beam pointing deviation in the azimuth direction based on the condition that the first derivative of the local quadric surface model is zero. Beam pointing deviation in the pitch direction The formula is expressed as: ； 。 5. The method for testing weather radar antenna parameters using the sun according to claim 1, characterized in that, The process of constructing a quadratic surface model includes: A1. Use the current sample set to perform local quadratic surface fitting to obtain the surface model under the current iteration; the current sample set under the first iteration is the set of valid solar signals; A2. Based on the surface model, determine the fitting residual between the observed power and the model fitting power of each sample in the current sample set, and determine the current residual standard deviation based on all fitting residuals; A3. Compare the absolute value of the fitting residual of each sample with the first threshold, which is the product of the preset elimination factor and the current standard deviation of the residual. Retain samples whose absolute value of the fitting residual does not exceed the first threshold to form an updated sample set. A4. Determine whether the rate of change of the current residual standard deviation from the residual standard deviation of the previous iteration is less than the preset second threshold. If yes, use the surface model obtained in the current iteration as the final local quadratic surface model. If no, use the updated sample set as the new current sample set and return to step A1 for the next iteration.

6. The method for testing weather radar antenna parameters using the sun according to claim 1, characterized in that, The process of identifying a set of valid solar signals from the scanned data includes: identifying solar signals from the scanned data; performing unit conversion and filtering on each solar signal to obtain a preprocessed solar signal expressed as received power value; for each preprocessed solar signal, performing atmospheric refraction correction on the observation elevation angle when the radar observes the sun to obtain the true solar elevation angle; and compensating for the solar energy attenuated by gas absorption in the propagation path by the received power to obtain the radar's observation power; the true solar elevation angle and observation power constitute the data of valid solar signals.

7. The method for testing weather radar antenna parameters using the sun according to claim 1, characterized in that, The sector volume scan mode is the VCPSun mode, with an azimuth coverage range of ±5° centered on the theoretical position of the sun and an azimuth resolution of 0.25°; the elevation coverage range is ±1.0° centered on the theoretical position of the sun.

8. The method for testing weather radar antenna parameters using the sun according to claim 1, characterized in that, Identify the effective solar signal set from the scan data, including identifying the effective solar signal subsets of horizontal polarization and vertical polarization from the scan data of the horizontal polarization channel and the vertical polarization channel, respectively. The process involves constructing a local quadratic surface model, obtaining model coefficients, and performing parameter inversion, including performing the inversion on the horizontal and vertical polarization subsets respectively to obtain the antenna parameters for the horizontal and vertical polarization channels.

9. A device for testing the parameters of a weather radar antenna using the sun, characterized in that, The method includes a memory, a processor, and a program stored in the memory and executable on the processor for testing weather radar antenna parameters using the sun. When the processor executes the program for testing weather radar antenna parameters using the sun, it implements the method for testing weather radar antenna parameters using the sun as described in any one of claims 1 to 8.

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