Radar metal ball calibration method and device, computer device and medium

Abstract

The present application relates to a kind of radar metal ball calibration method, device, computer equipment and medium, comprising: the directional diagram data of radar transmitting antenna and receiving antenna is acquired, the normalized processing is carried out to directional diagram data, and the normalized data after obtaining;Based on the normalized data of corresponding angle, construct discrete grid, calculate the solid angle microelement of each grid in discrete grid;Based on solid angle microelement, the normalized data of corresponding angle is carried out discrete integration operation, and the integral data of corresponding angle is obtained;The input parameter of radar calibration is acquired, and based on input parameter and integral data, the theoretical reflectivity factor of receiving antenna at each angle is calculated;Based on the theoretical reflectivity factor of each angle, corresponding radar calibration parameter is calculated, and radar calibration parameter is transmitted to signal processor, and system calibration is completed.This method can improve the calibration precision of radar system under wide emission narrow collection mode.

Description

Technical Field

[0001] This invention relates to the field of radar detection technology, and in particular to a radar metal ball calibration method, apparatus, computer equipment, and medium. Background Technology

[0002] Weather radar retrieves meteorological parameters by measuring the echo power of precipitation particles, among which the reflectivity factor is a core parameter for measuring precipitation intensity. To ensure measurement accuracy, the radar system must be calibrated.

[0003] The metal sphere calibration method is one of the most commonly used absolute calibration methods. Its principle is to use a metal sphere with a known radar cross-section (RCS) as a standard point target, calculate its "theoretical meteorological reflectivity factor" under specific conditions using radar equations, and compare it with the actual radar measurement value to obtain the radar's calibration constant.

[0004] Traditional mechanically scanned radars or conventional phased array radars typically employ a "narrow transmit, narrow receive" mode, where both the transmit and receive beams are narrow, and their shapes approximate a Gaussian distribution. This mode results in a small beam coverage area, requiring extremely high alignment accuracy for the calibrated target. Furthermore, in multi-beam receiving scenarios, narrow beams exhibit poor adaptability and insufficient effective echo coverage, making it difficult to meet the demands for high-precision, stable, and reliable calibration. Additionally, narrow beam scanning efficiency is low, leading to long calibration times and hindering the need for rapid and efficient system calibration.

[0005] Therefore, with the development of phased array technology, in order to improve scanning efficiency or achieve multi-beam reception, more and more weather radars are adopting a "wide transmit, narrow receive" working mode. That is, the transmitting antenna generates a wide beam covering a large angular range, usually a flat-top beam or a shaped beam, while the receiving end generates multiple narrow beams through digital beamforming (DBF).

[0006] In this mode, the following problems also exist. First, since the radiation pattern of a wide transmit beam often has a flat middle and steep edges, it no longer conforms to a Gaussian distribution. Furthermore, the difference between the transmit and receive beam widths increases, causing the Gaussian assumption in the "narrow transmit, narrow receive" mode to fail. In this case, continuing to use the approximate formula based on the Gaussian model to calculate the effective illumination volume will result in a huge deviation between the calculated sampling volume and the actual physical volume. In the existing technology, there are relatively few studies on the calculation of theoretical reflectivity under the condition of inconsistent transmit and receive beam shapes and non-Gaussian distribution. There is a lack of suitable calculation models, which makes the calibration accuracy of wide transmit, narrow receive radar unable to meet the requirements of quantitative precipitation estimation (QPE). Summary of the Invention

[0007] The purpose of this invention is to provide a radar metal sphere calibration method, device, computer equipment, and medium. By performing numerical overlap integration calculation on the radiation patterns of the transmitting antenna and the receiving antenna to obtain a two-way integral term, the invention addresses the problem that the traditional Gaussian beam approximation formula is no longer applicable in the existing "wide transmit, narrow receive" mode, thereby improving the accuracy of radar calibration.

[0008] To achieve the above objectives, the technical solution adopted by the present invention is: a radar metal sphere calibration method, characterized by comprising the following steps:

[0009] S1: Acquire radiation pattern data of radar transmitting antenna and receiving antenna, and normalize the radiation pattern data to obtain normalized data, wherein the radiation pattern data of receiving antenna includes gain sampling value at at least one angle;

[0010] S2: Based on the normalized data of the corresponding angle, construct a discrete grid and calculate the solid angle micro-element of each grid in the discrete grid;

[0011] S3: Based on the solid angle element, perform discrete integration on the normalized data of the corresponding angle to obtain the integral data of the corresponding angle;

[0012] S4: Obtain the input parameters for radar calibration, and calculate the theoretical reflectivity factor of the receiving antenna at each angle based on the input parameters and integral data;

[0013] S5: Calculate the corresponding radar calibration parameters based on the theoretical reflectivity factor for each angle, and transmit the radar calibration parameters to the signal processor to complete the system calibration.

[0014] This invention calculates the solid angle micro-elements of each grid in a discrete grid and performs discrete grid weighted integration on the transmit and receive radiation patterns, replacing the traditional Gaussian approximation calculation method. This significantly improves the accuracy of theoretical reflectivity calculation in the wide transmit and narrow receive mode, thereby achieving more accurate radar calibration.

[0015] Furthermore, in S1, acquiring the radiation pattern data of the radar transmitting and receiving antennas includes: measuring the radiation patterns of the far-field strength of the transmitting and receiving antennas after digital beamforming at at least one angle at the radar operating frequency point; wherein, the measurement range of the radiation pattern covers the main lobe of the beam and other angles with gain, clarifying the measurement frequency band, measurement object and sampling range of the radiation pattern, which can more completely and realistically reflect the actual gain distribution of the transmitting and receiving antennas, and provide a reliable data foundation for subsequent high-precision integration calculations.

[0016] Furthermore, in S1, the radiation pattern data is normalized using the following formula to obtain normalized data:

[0017] ;

[0018] in, In azimuth angle Pitch angle Normalized gain of the emission pattern in the direction of transmission. In azimuth angle Pitch angle Normalized gain of the received radiation pattern in the direction; and These are the launch pattern data. and receive pattern data The maximum value; i is the sequential number of the discrete sampling points in the azimuth angle, and M is the total number of samples in the azimuth angle direction; , j is the sequential number of the discrete sampling points in the pitch angle, and N is the total number of samples in the pitch angle direction.

[0019] By normalizing the transmit and receive antenna pattern data, the antenna gain is normalized to a relative gain scale, eliminating computational interference caused by differences in the absolute gain of different antennas, which facilitates subsequent weighted integral calculation of the discrete grid.

[0020] Furthermore, in S2, the calculation process of the solid angle element includes:

[0021] Establish azimuth and pitch angle Two-dimensional discrete mesh;

[0022] The solid angle infinitesimal element of each grid in the discrete grid is calculated using the following formula. :

[0023] ;

[0024] in, The sampling interval for the azimuth angle is... The sampling interval is for the pitch angle; Let be the azimuth angle of the i-th discrete grid. i is the sequential number of the discrete sampling points in the azimuth angle, and M is the total number of samples in the azimuth angle direction; Let j be the pitch angle of the j-th discrete grid. , j is the sequential number of the discrete sampling points in the pitch angle, and N is the total number of samples in the pitch angle direction.

[0025] The continuous spatial angle domain of the antenna pattern is transformed into a computable discrete grid cell, providing a computational basis for subsequent calculations of solid angle micro-elements and discrete integration operations of the pattern data. This transforms the difficult-to-solve integration operations into discretized numerical calculations, significantly reducing the complexity of integration solutions. Furthermore, by combining the cosine factor of the elevation angle, the actual size of the solid angle at different angular positions in the spherical coordinate system is accurately characterized, avoiding the solid angle calculation errors caused by uniform planar grid division. This provides a foundation for subsequent discrete integration operations, making them more closely aligned with the spatial radiation characteristics of the antenna pattern.

[0026] Furthermore, in S3, the following formula is used to perform discrete integration on the normalized data for the corresponding angle:

[0027] ;

[0028] in, The integral data represents the total solid angle of the radar transmit-receive beam at each angle; In azimuth angle Pitch angle Normalized gain of the emission pattern in the direction of transmission. In azimuth angle Pitch angle Normalized gain of the received radiation pattern in the direction; For each grid, there is a solid angle element; i is the sequential number of the discrete sampling points in the azimuth angle, and M is the total number of samples in the azimuth angle direction; , j is the sequential number of the discrete sampling points in the pitch angle, and N is the total number of samples in the pitch angle direction.

[0029] By using this discrete integral operation formula, the normalized radiation pattern data and solid angle micro-elements are accumulated and calculated to accurately solve the two-way integral term after the radiation patterns of the transmitting and receiving antennas are superimposed, and to truly quantify the total solid angle of the radar transmit-receive beam in the wide transmit-narrow receive mode. Compared with the simplified calculation of the traditional Gaussian beam approximation, this method fully preserves the actual spatial distribution characteristics of the radiation pattern and effectively avoids the integration error caused by the approximation process.

[0030] Furthermore, the theoretical reflectivity factor Z of the receiving antenna at each angle is calculated using the following formula:

[0031] ;

[0032] Where r is the radius of the metal sphere, R is the calibration distance of the metal sphere, λ is the radar wavelength, τ is the radar pulse width, and c is the speed of light. For dielectric constant factor, Integral data for each angle.

[0033] Using the total solid angle of the transmit and receive beams, which is accurately calculated in the wide transmit and narrow receive mode, to replace the simplified approximation of the traditional Gaussian beam, can effectively solve the problem that the traditional method simulates using empirical formulas and does not integrate the actual radiation pattern, thereby significantly reducing the calculation error of the solid angle.

[0034] Furthermore, in S5, the calculation of the corresponding radar calibration parameters based on the theoretical reflectivity factor for each angle specifically includes:

[0035] Calculate the system calibration constants of the radar ;

[0036] Based on the system calibration constants, calculate the corresponding radar calibration parameters. ;

[0037] Where Z0 is the system calibration constant, Z is the theoretical reflectivity factor of the receiving antenna at each angle, and P m I0 is the center echo power of the metal sphere received by the radar, I0 is the radar receiver noise floor power, and R is the calibration distance of the metal sphere.

[0038] During radar calibration, calibration parameters are derived directly based on the actual beam superposition characteristics, making the radar detection results more closely match the actual scenario.

[0039] Based on the same concept, the present invention also provides a radar metal ball calibration device, the device comprising:

[0040] The antenna gain normalization calculation module is used to acquire radiation pattern data of radar transmitting antenna and receiving antenna, and to normalize the radiation pattern data to obtain normalized data. The radiation pattern data of the receiving antenna includes gain sampling values ​​at at least one angle.

[0041] The solid angle infinitesimal element calculation module is used to construct a discrete grid based on the normalized data of the corresponding angle, and to calculate the solid angle infinitesimal element of each grid in the discrete grid.

[0042] The integral data calculation module is used to perform discrete integral operations on the normalized data of the corresponding angle based on the solid angle element to obtain the integral data of the corresponding angle.

[0043] The theoretical reflectivity factor calculation module is used to obtain the input parameters of radar calibration and calculate the theoretical reflectivity factor of the receiving antenna at each angle based on the input parameters and integral data.

[0044] The radar calibration module is used to calculate the corresponding radar calibration parameters based on the theoretical reflectivity factor for each angle, and transmit the radar calibration parameters to the signal processor to complete the system calibration.

[0045] Based on the same concept, the present invention also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the method described above.

[0046] Based on the same concept, the present invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the method described above.

[0047] Compared with existing technologies, the beneficial effects of this invention are as follows: The method proposed in this invention calculates the two-way integral term by performing numerical overlap integration on the radiation patterns of the transmitting and receiving antennas. This eliminates the systematic bias introduced by beam model mismatch, without relying on the Gaussian distribution assumption of the beam. It also solves the problem that traditional Gaussian beam approximation relies on the model assumption that the beam is Gaussian distributed, which can only adapt to standard Gaussian beams and cannot handle irregular beams such as flat-top beams and cosecant square beams, thus greatly improving the universality of the method. At the same time, this invention introduces the cosine factor of the elevation angle in the calculation of the solid angle element, correcting the error caused by spherical geometry, so that the calculated value of the solid angle element is closer to the spatial radiation characteristics of the actual beam. Based on the calculation of the integral term of the solid angle element, the theoretical reflectivity under any beam shape can be accurately calculated. Attached Figure Description

[0048] To more clearly illustrate the technical solution of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only one embodiment of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0049] Figure 1 This is a flowchart of the radar metal ball calibration method in an embodiment of the present invention;

[0050] Figure 2 This is the radiation pattern of the wide-beam transmitting antenna according to an embodiment of the present invention;

[0051] Figure 3 This is the radiation pattern of the narrow beam receiving antenna according to an embodiment of the present invention;

[0052] Figure 4 This is a schematic diagram of the calculation of the micro-element area according to an embodiment of the present invention;

[0053] Figure 5 The radar metal ball calibration method of this invention is used to obtain the normalized antenna pattern in the elevation direction under a 7.5° wide beam with wide transmission and narrow reception.

[0054] Figure 6The radar metal ball calibration method of this invention is used to obtain the theoretical reflectivity of each pointing narrow beam under a 7.5° wide beam.

[0055] Figure 7 This is a comparison chart of the radar metal ball calibration method of this invention and the theoretical reflectivity calculated by the Gaussian fitting method under a 7.5° wide beam in the wide transmit and narrow receive mode.

[0056] Figure 8 The radar metal ball calibration method of this invention is used to obtain the normalized antenna pattern in the elevation direction under a 15° wide beam with wide transmission and narrow reception.

[0057] Figure 9 The radar metal ball calibration method of this invention is used to obtain the theoretical reflectivity of each pointing narrow beam under a 15° wide beam.

[0058] Figure 10 This is a comparison chart of the radar metal ball calibration method of this invention and the theoretical reflectivity calculated by the Gaussian fitting method in narrow transmit and narrow receive mode.

[0059] Figure 11 This is a comparison chart of the radar metal ball calibration method of this invention and the theoretical reflectivity calculated by the Gaussian fitting method under a 15° wide beam in the wide transmit and narrow receive mode. Detailed Implementation

[0060] The technical methods of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0061] The technical methods of this application will be described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments.

[0062] Example 1

[0063] Figure 1 A flowchart of the radar metal sphere calibration method provided by an embodiment of the present invention is shown. Figure 1 As shown, the method includes the following steps:

[0064] S1: Acquire radiation pattern data from the radar transmitting antenna and receiving antenna, and normalize the radiation pattern data to obtain normalized data. The radiation pattern data of the receiving antenna includes gain sampling values ​​at at least one angle. The gain sampling includes the antenna normal and gain sampling within ±60° of the azimuth and elevation directions centered on the normal direction. In this embodiment, at least one angle is at least one elevation angle, and each narrow beam corresponds to one elevation angle, while the azimuth angle remains unchanged.

[0065] Using a microwave anechoic chamber, the far-field intensity patterns of the transmitting and receiving antennas after digital beamforming are measured at the radar's operating frequency. The measurement range needs to cover the main lobe and other angles with gain. In this embodiment, both the azimuth and elevation angles are ±60°, and the sampling interval is... , The value can be as small as possible, for example, 0.1°, to ensure integration accuracy. This operation is a routine practice for those skilled in the art and is common knowledge in the field.

[0066] Figure 2 and Figure 3 The radiation patterns of the wide-beam transmitting antenna and the narrow-beam receiving antenna according to embodiments of the present invention are shown respectively, and the transmission radiation pattern matrix is ​​searched respectively. and receiver pattern matrix maximum value and Then, normalization is performed using the following formula to obtain a normalized pattern function with values ​​in the range [0,1]:

[0067] ;

[0068] in, In azimuth angle Pitch angle Normalized gain of the emission pattern in the direction of transmission. In azimuth angle Pitch angle Normalized gain of the received radiation pattern in the direction; and These are the launch pattern data. and receive pattern data The maximum value; i is the sequential number of the discrete sampling points in the azimuth angle, and M is the total number of samples in the azimuth angle direction; , j is the sequential number of the discrete sampling points in the pitch angle, and N is the total number of samples in the pitch angle direction.

[0069] S2: Based on the normalized data of the corresponding angle, construct a discrete grid and establish the azimuth angle. and pitch angle The two-dimensional discrete grid is obtained, and the solid angle micro-element of each grid in the discrete grid is calculated.

[0070] The calculation of the solid angle infinitesimal element of each grid in the discrete grid specifically includes the following steps:

[0071] Based on the geometric properties of the spherical coordinate system, the first... The projected area of ​​each grid point is:

[0072] ;

[0073] The following will combine Figure 4 Explain its principle, in , When sufficiently small, the projected infinitesimal element can be approximated as a square, and its area can be calculated by multiplying its length by its height. According to the arc length formula, the height h of the square can be calculated using the following formula:

[0074] ;

[0075] The length of the rectangle can be calculated using the following formula:

[0076] ;

[0077] Therefore, we can conclude that:

[0078] .

[0079] Through formula Calculate the solid angle infinitesimal element, in solid angle element in direction The value is:

[0080] ;

[0081] The solid angle element, i.e., the solid angle corresponding to a unit projection, reflects the overall beamwidth of the radar. The larger the value, the larger the area of ​​the target illuminated by the radar at the same distance. Conversely, the smaller the value, the smaller the beamwidth.

[0082] S3: Based on the solid angle element, perform discrete integration on the normalized data of the corresponding angle to obtain the integral data of the corresponding angle;

[0083] In the traditional "narrow transmission and narrow reception" mode, based on the assumption that the beam shape approximately conforms to a Gaussian distribution model, the classic weather radar equation (Probert-Jones equation) uses analytical formulas to calculate the effective integral term of the beam:

[0084] ;

[0085] In the "wide transmit, narrow receive" mode, the radiation pattern of the wide transmit beam no longer conforms to a Gaussian distribution. Therefore, this invention abandons the traditional Gaussian beam approximation algorithm and adopts an effective filling volume calculation method based on numerical integration of the measured antenna radiation pattern. By accurately calculating the integral term of the spatial overlap between the wide transmit beam and the narrow receive beam, a formula for calculating the theoretical reflectivity factor of a metal sphere suitable for the wide transmit, narrow receive mode is derived, thereby achieving high-precision calibration. Specifically, the discrete integration operation is performed using the following formula:

[0086] ;

[0087] in, The integral data represents the total solid angle of the radar transmit-receive beam at each angle; In azimuth angle Pitch angle Normalized gain of the emission pattern in the direction of transmission. In azimuth angle Pitch angle Normalized gain of the received radiation pattern in the direction; For each grid, there is a solid angle element; i is the sequential number of the discrete sampling points in the azimuth angle, and M is the total number of samples in the azimuth angle direction; , j is the sequential number of the discrete sampling points in the pitch angle, and N is the total number of samples in the pitch angle direction.

[0088] S4: Obtain the input parameters for radar calibration, and calculate the theoretical reflectivity factor Z of the receiving antenna at each angle based on the input parameters and integral data;

[0089] The input parameters required for radar calibration include the radius r of the metal sphere, the calibration distance R of the metal sphere (i.e., the slant distance from the metal sphere to the radar), the radar frequency f, the radar pulse width τ, the speed of light c, and the dielectric constant factor. The selection of the dielectric constant factor is based on whether the object of theoretical reflectivity calculation is liquid water or ice. For example, in the field of weather radar, the dielectric constant factor approximating liquid water is commonly used. The dielectric constant factor of ice .

[0090] The theoretical reflectivity factor Z (in units) is calculated using the following formula. ):

[0091] ;

[0092] Where λ is the radar wavelength, through The theoretical meteorological reflectance of the metal sphere was calculated using the above formula, and then... Replacing the Gaussian model The antenna radiation characteristics are fully preserved.

[0093] S5: Calculate the corresponding radar calibration parameters based on the theoretical reflectivity factor for each angle, and transmit the radar calibration parameters corresponding to each narrow beam to the signal processor to complete the system calibration.

[0094] The specific steps of performing radar calibration include:

[0095] Point the radar antenna at a clear, cloudless airspace and turn on the radar to transmit a signal. The signal received at this time is the radar receiver noise floor power I0. Record this receiver noise floor power.

[0096] A metal sphere of known radius is suspended in the far-field region of a radar system, and the radar beam is controlled to be aimed at the sphere. The radar echo power P of the metal sphere received by the radar is recorded. m .

[0097] The radar calibration parameters are calculated based on the theoretical reflectivity factor for each angle, including:

[0098] Calculate the radar system calibration constant Z0, which is the reflectivity at 1 km with a signal-to-noise ratio of 0 dB:

[0099] ;

[0100] Calculate the radar calibration parameters based on the system calibration constants. The unit is converted to decibels and sent to the radar signal processor as a radar calibration parameter to complete the system calibration process.

[0101] Figure 5 This paper illustrates the radar metal sphere calibration method according to an embodiment of the present invention, under the conditions of 9.3 GHz, 7.5° wide beam, slant range R of 409 m, and metal sphere radius r of 0.1524 m, and the normalized antenna radiation pattern in the elevation direction. The transmit beam is a wide beam, and the receive beams are narrow beams at elevation angles of -2.7°, -1.8°, -0.9°, 0°, 0.9°, 1.8°, and 2.7°. The wide transmit beam forms the main lobe radiation region in the elevation angle range of -2° to 4°, with a normalized intensity peak close to 1.0, representing the main energy region of the antenna radiation. After the narrow receive beams are superimposed with the wide transmit beam, the radiation pattern exhibits a "high center, low sides" main lobe characteristic, and side lobes are formed in the region outside the elevation angle ±4°. The normalized intensity of the side lobes is approximately 0.2 to 0.6, reflecting the spatial superposition law of the transmit and receive beams in the wide transmit / narrow receive mode. Meanwhile, the superposition curves of different narrow receiving beam angles are interspersed in the main lobe region, reflecting the spatial superposition characteristics of the transmitting and receiving beams under different narrow receiving beam angles.

[0102] Figure 6The theoretical reflectivity for each pointing narrow beam under a 7.5° wide beam is shown. Simulation results show that the theoretical reflectivity distribution exhibits a notch-like characteristic: the closer the narrow beam is to the center of the wide beam, the lower the theoretical reflectivity, a pattern consistent with theoretical derivation. The reason for this is that the reflected energy of the metal sphere is constant, and reflectivity is a parameter characterizing energy density. When the alignment accuracy between the narrow and wide beams improves, the radar detection volume increases, and the energy density of the fixed reflected energy decreases within a larger volume, thus resulting in the aforementioned notch-like distribution of the theoretical reflectivity. Figure 7 The diagram shows a comparison between the radar metal sphere calibration method of this invention and the theoretical reflectivity calculated using the Gaussian fitting method under a 7.5° wide beam in the wide transmit and narrow receive mode.

[0103] Figure 8 The radar metal sphere calibration method according to an embodiment of the present invention is shown, with a slant range R of 409 meters and a metal sphere radius r of 0.1524 meters, under the conditions of 9.3 GHz, 15° wide beam, and normalized antenna radiation pattern in the elevation direction. The transmit beam is a wide beam, and the receive beams are narrow beams at elevation angles of -6.3°, -5.4°, -4.5°, -3.6°, -2.7°, -1.8°, -0.9°, 0.0°, 0.9°, 1.8°, 2.7°, 3.6°, 4.5°, 5.4°, and 6.3°. Figure 9 The theoretical reflectivity of each directional narrow beam is shown under a 15° wide beam.

[0104] Figure 10 This is a comparison of the radar metal sphere calibration method of this invention and the theoretical reflectivity calculated using the Gaussian fitting method, under narrow transmit / narrow receive mode, at 9.3 GHz, slant range R of 409 meters, and a metal sphere radius r of 0.1524 m. The calculated theoretical RCS of the metal sphere is 43 dBsm (hereinafter abbreviated as dB). As can be seen from the figure, both the radar metal sphere calibration method and the Gaussian fitting method of this invention achieve good results, with the calculated theoretical reflectivity around 43 dB and an error below 0.4 dB. Furthermore, the method of this invention has a smaller variance.

[0105] Figure 11This is a comparison of the theoretical reflectivity calculated using the radar metal sphere calibration method of this invention and the Gaussian fitting method under a 15° wide beam configuration in wide transmit / narrow receive mode. As can be seen from the figure, the theoretical reflectivity calculated using the radar metal sphere calibration method of this invention is still around 43dB, while the reflectivity calculated using the Gaussian fitting method shows a significant attenuation, with a calculated reflectivity of 34dB. This is a large difference from the theoretical RCS of the metal sphere. Therefore, the method described in this invention can adapt to various situations, including wide transmit / narrow receive and narrow transmit / narrow receive modes. The Gaussian fitting method, however, fails in wide transmit / narrow receive mode. Furthermore, the method of this invention achieves good results under both 7.5° and 15° wide beam configurations.

[0106] This invention proposes a radar metal sphere calibration method. This method achieves accurate calibration of the radar reflectivity factor in a wide transmit beam and narrow receive beam operating mode. It solves the problem of inaccurate calculation of theoretical values ​​for metal sphere calibration caused by beam shape mismatch and non-Gaussian distribution in this mode, thus affecting the calibration accuracy of the radar system. Specifically, this invention constructs a discrete grid based on measured radiation pattern data and performs solid angle-weighted integration, enabling accurate calculation of the theoretical reflectivity under any beam shape without the need for approximate assumptions about the beam shape. Compared to the traditional Gaussian approximation method, it fundamentally eliminates the systematic bias (typically reaching several dB) introduced by beam model mismatch, thereby significantly improving radar calibration accuracy. Furthermore, this invention is independent of the specific beam shape; whether it is a narrow beam, wide beam, flat-top beam, cosecant square beam, or other shaped beam, as long as measured radiation pattern data in an anechoic chamber is available, this method can be directly used for calculation, exhibiting strong versatility and engineering applicability. Simulation results show that the theoretical reflectivity distribution exhibits a low-to-high ratio in the middle and high-to-the-side characteristics, which is highly consistent with the physical law that "fixed energy and beam extension lead to a decrease in energy density". Based on the calibration verification logic of this "notch effect", the physical characteristic that the theoretical reflectivity is lowest when the beam center is aligned can be used as the basis for verifying the correctness of the calculation of the sampling volume of the wide-transmitter, narrow-receiver radar.

[0107] Example 2

[0108] Based on the same concept, embodiments of the present invention also provide a radar metal ball calibration device, the device comprising:

[0109] The antenna gain normalization calculation module is used to acquire radiation pattern data of radar transmitting antenna and receiving antenna, and to normalize the radiation pattern data to obtain normalized data. The radiation pattern data of the receiving antenna includes gain sampling values ​​at at least one angle.

[0110] The solid angle infinitesimal element calculation module is used to construct a discrete grid based on the normalized data of the corresponding angle, and to calculate the solid angle infinitesimal element of each grid in the discrete grid.

[0111] The integral data calculation module is used to perform discrete integral operations on the normalized data of the corresponding angle based on the solid angle element to obtain the integral data of the corresponding angle.

[0112] The theoretical reflectivity factor calculation module is used to obtain the input parameters of radar calibration and calculate the theoretical reflectivity factor of the receiving antenna at each angle based on the input parameters and integral data.

[0113] The radar calibration module is used to calculate the corresponding radar calibration parameters based on the theoretical reflectivity factor for each angle, and transmit the radar calibration parameters to the signal processor to complete the system calibration.

[0114] Example 3

[0115] Based on the same concept, embodiments of the present invention also provide a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the method described in Embodiment 1 above.

[0116] Example 4

[0117] Based on the same concept, embodiments of the present invention also provide a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the method described in Embodiment 1 above.

[0118] In the embodiments disclosed in this application, a computer storage medium may be a tangible medium that may contain or store programs for use by or in conjunction with an instruction execution system, apparatus, or device. The computer storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of computer storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0119] The above embodiments should be understood as being used only to illustrate the present invention more clearly, and not to limit the scope of the present invention. After reading the present invention, any modifications of the present invention in various equivalent forms by those skilled in the art fall within the scope defined by the appended claims.

Claims

1. A method for calibrating a radar metal sphere, characterized in that, Includes the following steps: S1: Acquire radiation pattern data of radar transmitting antenna and receiving antenna, and normalize the radiation pattern data to obtain normalized data, wherein the radiation pattern data of receiving antenna includes gain sampling value at at least one angle; S2: Based on the normalized data of the corresponding angles, construct a discrete mesh and calculate the solid angle micro-element of each mesh in the discrete mesh; the calculation process of the solid angle micro-element includes: Establish azimuth and pitch angle Two-dimensional discrete mesh; The solid angle infinitesimal element of each grid in the discrete grid is calculated using the following formula. : ； in, The sampling interval for the azimuth angle is... The sampling interval is for the pitch angle; For the first i The azimuth angle of a discrete grid. , i The sequential numbering of the discrete sampling points for the azimuth angle. M This represents the total number of samples in the azimuth direction. For the first j The pitch angle of a discrete grid. , j The discrete sampling points for pitch angle are numbered sequentially. N This represents the total number of samples in the pitch direction; S3: Based on the solid angle element, perform discrete integration on the normalized data of the corresponding angle to obtain the integral data of the corresponding angle; S4: Obtain the input parameters for radar calibration, and calculate the theoretical reflectivity factor of the receiving antenna at each angle based on the input parameters and integral data; S5: Calculate the corresponding radar calibration parameters based on the theoretical reflectivity factor for each angle, and transmit the radar calibration parameters to the signal processor to complete the system calibration.

2. The radar metal sphere calibration method according to claim 1, characterized in that, In S1, acquiring the radiation pattern data of the radar transmitting antenna and receiving antenna includes: measuring the radiation pattern of the far-field field strength of the transmitting antenna and receiving antenna after digital beamforming at at least one angle at the radar operating frequency point; wherein the measurement range of the radiation pattern covers the main lobe of the beam and other angles with gain.

3. The radar metal sphere calibration method according to claim 2, characterized in that, In S1, the radiation pattern data is normalized using the following formula to obtain the normalized data: ； in, In azimuth angle Pitch angle Normalized gain of the emission pattern in the direction of transmission. In azimuth angle Pitch angle Normalized gain of the received radiation pattern in the direction; and These are the launch pattern data. and receive pattern data The maximum value; , i The sequential numbering of the discrete sampling points for the azimuth angle. M This represents the total number of samples in the azimuth direction. , j The discrete sampling points for pitch angle are numbered sequentially. N This represents the total number of samples in the pitch direction.

4. The radar metal sphere calibration method according to claim 1, characterized in that, In S3, the following formula is used to perform discrete integration on the normalized data for the corresponding angle: ； in, The integral data represents the total solid angle of the radar transmit-receive beam at each angle; In azimuth angle Pitch angle Normalized gain of the emission pattern in the direction of transmission. In azimuth angle Pitch angle Normalized gain of the received radiation pattern in the direction; For each grid, there is a solid angle element; , i The sequential numbering of the discrete sampling points for the azimuth angle. M This represents the total number of samples in the azimuth direction. , j The discrete sampling points for pitch angle are numbered sequentially. N This represents the total number of samples in the pitch direction.

5. The radar metal sphere calibration method according to claim 1, characterized in that, The theoretical reflectivity factor of the receiving antenna at each angle is calculated using the following formula. Z : ； in, r Let R be the radius of the metal sphere, and R be the calibration distance of the metal sphere. λ τ is the radar wavelength, and τ is the radar pulse width. c At the speed of light, For dielectric constant factor, Integral data for each angle.

6. The radar metal sphere calibration method according to claim 1, characterized in that, In S5, the calculation of the corresponding radar calibration parameters based on the theoretical reflectivity factor for each angle specifically includes: Calculate the system calibration constants of the radar ; Based on the system calibration constants, calculate the corresponding radar calibration parameters. ; in, Z 0 Let Z be the system calibration constant, and Z be the theoretical reflectivity factor of the receiving antenna at each angle. P m The center echo power of the metal sphere received by the radar. I 0 R represents the radar receiver's noise floor power, and R represents the calibration distance of the metal sphere.

7. A radar metal ball calibration device, used to implement the method according to any one of claims 1 to 6, characterized in that, The device includes: The antenna gain normalization calculation module is used to acquire radiation pattern data of radar transmitting antenna and receiving antenna, and to normalize the radiation pattern data to obtain normalized data. The radiation pattern data of the receiving antenna includes gain sampling values ​​at at least one angle. The solid angle infinitesimal element calculation module is used to construct a discrete grid based on the normalized data of the corresponding angle, and to calculate the solid angle infinitesimal element of each grid in the discrete grid. The integral data calculation module is used to perform discrete integral operations on the normalized data of the corresponding angle based on the solid angle element to obtain the integral data of the corresponding angle. The theoretical reflectivity factor calculation module is used to obtain the input parameters of radar calibration and calculate the theoretical reflectivity factor of the receiving antenna at each angle based on the input parameters and integral data. The radar calibration module is used to calculate the corresponding radar calibration parameters based on the theoretical reflectivity factor for each angle, and transmit the radar calibration parameters to the signal processor to complete the system calibration.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, It stores a computer program that, when executed by a processor, implements the steps of the method according to any one of claims 1 to 6.

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