Near-field antenna measurement method based on phase reduction

Abstract

The application discloses a near-field antenna measurement method based on phase reduction, and mainly solves the problem that the high-frequency antenna near-field phase is difficult to obtain in the existing antenna measurement technology, and the high-frequency antenna near-field cannot be accurately measured. The implementation scheme is as follows: the amplitude of two planes of the high-frequency antenna near-field is obtained through near-field antenna measurement, the optimal initial phase of the first plane is calculated according to the amplitudes of the two planes by using a global optimization algorithm, and the phase of the first plane of the high-frequency antenna near-field is restored from the optimal initial phase and the amplitudes of the two planes by using an iterative Fourier algorithm; the electric field of the first plane is composed of the amplitude and the restored phase of the first plane, and the far-field pattern of the high-frequency antenna is calculated from the electric field. The phase of the high-frequency antenna is obtained by using the optimization and restoration algorithm, and the measurement is not needed, so that the problem that the antenna near-field phase is difficult to obtain in the prior art is solved, the cost of the near-field antenna measurement is saved, and the method is compatible with the high-frequency and low-frequency antenna measurement, and has strong practicability.

Description

Technical Field

[0001] This invention belongs to the field of microwave technology, and specifically designs a near-field antenna measurement method that can be used for high-frequency antenna measurement. Background Technology

[0002] In the many research areas of electromagnetics, antenna measurement technology is an important research direction. Existing antenna measurement methods can be divided into two main categories: first, direct methods, including far-field methods, focusing methods, and compact field methods; second, indirect methods, namely near-field measurement methods. Near-field antenna measurement technology, performed in an anechoic chamber, has the advantages of obtaining a large amount of information, high testing efficiency, and low requirements for the surrounding environment and weather, making it the mainstream trend in antenna measurement technology. Near-field antenna measurement can be further divided into planar measurement, cylindrical measurement, and spherical measurement, depending on the measurement surface.

[0003] Traditional near-field measurement methods for antennas involve acquiring the amplitude and phase information of the tangential electric field on a scanning plane in the near-field region of the antenna, and then using near-field-far-field transformation theory to derive the antenna's far-field radiation characteristics. However, as the antenna operating frequency increases, phase acquisition becomes increasingly difficult due to factors such as probe position error, temperature and humidity variations, transmission device accuracy, and receiver stability and accuracy. This makes high-frequency antenna measurement a major challenge. Some active array antennas may lack a reference channel, making accurate phase test data impossible and hindering precise near-field measurements. Furthermore, the short wavelength of high-frequency antennas places higher demands on equipment accuracy, significantly increasing measurement costs. To address the problems of traditional near-field measurement methods, several techniques have been proposed to solve these issues.

[0004] In his article "The Correct Selection of Mixing Methods for Antenna Testing," published in the journal *Microwave and RF*, John W. Boyles proposed using mixing methods or harmonic mixing methods to measure high-frequency antennas. The harmonic mixing measurement system he mentioned is low-cost, achieving cost savings by increasing the conversion loss of the mixing system. This system can measure high-frequency antennas, obtaining the far-field radiation pattern by measuring the amplitude and phase of the antenna under test. However, because this method is greatly affected by the surrounding environment, the measurement sensitivity decreases as the measurement frequency increases, resulting in an inaccurate far-field radiation pattern.

[0005] In his master's thesis, "Research on Field Measurement Methods for Antennas," Song Kang proposed using the field plane to obtain the far-field radiation pattern of an antenna. He employed a cylindrical unfolding method to acquire the field plane data, extending near-field measurement from cylindrical to the cylindrical field plane. Compared to traditional near-field measurements, this method requires less data acquisition and can measure antenna characteristics from a relatively long test distance, ensuring measurement accuracy. The amplitude and phase of the antenna are measured using the field plane. However, for high-frequency antenna measurements, this method yields inaccurate far-field radiation patterns due to insufficient precision in the measured phase data.

[0006] Both of the above methods fail to accurately obtain the near-field phase data of the high-frequency antenna, resulting in a large error between the measured far-field radiation characteristics of the high-frequency antenna and the actual values. Consequently, the far-field radiation characteristics of the high-frequency antenna cannot be accurately obtained. Summary of the Invention

[0007] The present invention addresses the aforementioned technical challenges by designing a near-field antenna measurement method based on phase restoration. This method accurately reconstructs and acquires near-field phase data of high-frequency antennas, reduces measurement errors, and improves the precision of high-frequency antenna measurements. The technical solution achieving this objective is as follows: During near-field measurement of a high-frequency antenna, only amplitude data from two near-field planes are acquired. The phase data of one plane is then reconstructed using an optimized restoration algorithm. Finally, near-field and far-field transformations are used to accurately calculate the far-field radiation pattern of the high-frequency antenna. The implementation steps include the following:

[0008] (1) Measure the tangential electric field amplitude information M1 and M2 of the two planes in the near field of the high-frequency antenna according to the Nyquist sampling theorem;

[0009] (2) Set a random phase ψ0, and obtain the initial electric field of the first plane of the high-frequency antenna from the random phase ψ0 and the amplitude information M1 of the first plane.

[0010] (3) Based on the plane wave theory, the initial electric field E1 of the first plane is derived to obtain the initial electric field E2 of the second plane, and the error fx2 between the amplitude abs(E2) of E2 and the amplitude information M2 of the second plane is calculated.

[0011] (4) Keeping the phase angle(E2) of E2 unchanged, replace the amplitude abs(E2) of E2 with the amplitude information M2 of the second plane to obtain the iterative electric field of the second plane E2(M2) = M2·e j·angle(E2) The second plane iterative electric field E2(M2) is reduced to the first plane reduced electric field E1' using plane wave theory. The phase of E1' is angle(E1') and the amplitude is abs(E1').

[0012] (5) Calculate the error fx1 between the amplitude abs(E1’) of the restored electric field E1’ in the first plane and the amplitude information M1 of the first plane;

[0013] (6) Calculate the total error value fx3 = fx1 + fx2, and compare it with the set minimum error value fx of the global optimization algorithm: If fx3 ≤ fx, then retain the phase angle(E1’) at this time, and let ψ' = angle(E1’) be the phase of the initial restored electric field Ea in the first plane, and obtain the initial restored electric field Ea in the first plane as Ea = M1·e j·ψ' , and execute step (8);

[0014] Otherwise, execute step (7);

[0015] (7) Perform iterative calculation on the initial phase of the first plane:

[0016] Set P as the current number of times for calculating fx3 in step (6), and Q as the maximum number of iterations, and compare the two:

[0017] If P = Q, then find the minimum value fx3(min) among all fx3, and retain the corresponding phase angle(E1’), and let ψ' = angle(E1’) be the phase of the initial restored electric field Ea in the first plane, and obtain the initial restored electric field Ea in the first plane as Ea = M1·e j·ψ' , and execute step (8);

[0018] If P < Q, then perform the global optimization algorithm on the phase of the initial electric field E1 in the first plane to obtain the random phase ψ1 of the initial electric field E1 in the first plane, and let Return to step (3);

[0019] (8) According to the plane wave spectrum theory, calculate the initial restored electric field Eb in the second plane from the initial restored electric field Ea in the first plane. The phase of this Eb is angle(Eb), and the amplitude is abs(Eb);

[0020] (9) Replace the amplitude abs(Eb) of the initial restored electric field Eb in the second plane with the tangential field amplitude information M2 of the second plane, and keep the phase angle(Eb) of Eb unchanged, and obtain the iterative electric field Eb(M2) in the second plane as Eb(M2) = M2·e j·angle(Eb) , and use the plane wave spectrum theory to calculate Eb(M2) to obtain the iterative restored electric field Ea’ in the first plane. The phase of this Ea’ is angle(Ea’), and the amplitude is abs(Ea’);

[0021] (10) Calculate the error fy1 between the amplitude abs(Ea’) of Ea’ and the amplitude information M1 of the first plane, and compare it with the set minimum error value fy of the local optimal algorithm:

[0022] If fy1≤fy, then retain the phase angle(Ea') at this time, and let ψ=angle(Ea') as the phase of the final restored electric field E of the first plane, thus obtaining the final restored electric field E=M1·e of the first plane. j·ψ Execute step (12);

[0023] Otherwise, proceed to step (11);

[0024] (11) Perform iterative calculations on the phase of the iteratively restored electric field Ea' in the first plane:

[0025] Set U to the current number of times fy1 is calculated in step (10), and V to the maximum number of iterations, and compare the two:

[0026] If U = V, then find the minimum value fy1(min) among all fy1 values, retain its corresponding phase angle(Ea'), and let ψ = angle(Ea') as the phase of the final restored electric field E of the first plane, thus obtaining the final restored electric field E = M1·e of the first plane. j·ψ Execute step (12);

[0027] Otherwise, the phase angle (Ea') of Ea' is kept unchanged, and the amplitude of Ea' is replaced by the amplitude information M of the first plane to obtain the initial restored electric field of the first plane Ea = M1·e j·angle(Ea ' ) Return to step (9);

[0028] (12) Using the planar near-field and far-field transformation theory, the far-field radiation pattern of the high-frequency antenna can be obtained based on the final restored electric field E of the first plane.

[0029] Compared with the prior art, the present invention has the following advantages:

[0030] First, the present invention uses a global optimization algorithm to obtain the optimal initial phase of the first plane, and uses the iterative Fourier algorithm to calculate the restored phase of the first plane through this phase, which solves the problem of difficulty in obtaining the near-field phase of high-frequency antennas and enables accurate near-field measurement of high-frequency antennas.

[0031] Secondly, this invention obtains the amplitude of the near field of the high-frequency antenna by measuring it, and then reconstructs the phase of the near field of the high-frequency antenna from the amplitude. Compared with the traditional antenna measurement, which obtains the far-field radiation characteristics of the antenna by acquiring the amplitude and phase of the near field of the antenna, this invention not only avoids acquiring the phase of the near field of the high-frequency antenna and saves the cost of antenna measurement, but also provides a new measurement mode that shifts from the traditional "full-parameter measurement" to "semi-parameter measurement + data processing".

[0032] Third, since this invention only requires obtaining the amplitude when measuring high-frequency antennas, the method is also applicable to the measurement of low-frequency antennas, enabling the sharing of high and low frequency antennas in a single system, which is highly practical. Attached Figure Description

[0033] Figure 1 This is a flowchart illustrating the overall implementation of the present invention;

[0034] Figure 2 This is the flowchart of obtaining the optimal initial phase sub-flow of the first plane through a global optimization algorithm in this invention;

[0035] Figure 3 This is a schematic diagram of a phaseless near-field antenna measurement system.

[0036] Figure 4 This invention provides a flowchart of the phase sub-process for obtaining the first plane using an iterative Fourier algorithm.

[0037] Figure 5 This is a schematic diagram of a phased array antenna measured using the present invention.

[0038] Figure 6 This is a comparison diagram of the optimal phase distribution of the center row and column obtained by the initial restoration of this invention and the measured phase distribution of the center row and column of the phased array antenna.

[0039] Figure 7 This is a comparison diagram of the phase distribution of the first plane center row and column obtained by the final reconstruction using the present invention and the measured phase distribution of the first plane center row and column of the phased array antenna.

[0040] Figure 8 This is a comparison chart of the far-field radiation characteristics calculated using this invention and the far-field radiation characteristics of a standard phased array antenna. Detailed Implementation

[0041] The embodiments and effects of the present invention will be further described in detail below with reference to the accompanying drawings:

[0042] Reference Figure 1 The implementation steps of this invention are as follows:

[0043] Step 1: Perform amplitude scanning on the two near-field fields of the high-frequency antenna. The actual measurement environment is referenced. Figure 5 The tangential electric field amplitudes M1 and M2 of the two near-field planes of the high-frequency antenna are measured according to the Nyquist sampling theorem.

[0044] (1.1) Near-field measurement of the distance d1 from the first plane to the antenna under test and the distance d2 from the second plane to the antenna under test;

[0045] (1.2) According to the measurement criteria for near-field antennas, the plane for antenna measurement must meet a specific size so that the collected antenna radiation information is not lost, that is, the minimum scanning side length L of the second plane. x satisfy:

[0046] L x ≥2d2tanθ+a

[0047] Where θ is the maximum reliable far-field angle of the antenna under test, and a is the aperture width of the antenna under test;

[0048] (1.3) Set the scanning side length of the first and second near-field planes of the antenna to be L. x Based on the Nyquist sampling theorem, which states that the scanning interval of the plane under test during near-field measurements of an antenna must not exceed half the wavelength of the antenna under test, the scanning interval m is determined, and the side length and number of scanning points N = L of the second plane are obtained. x / m;

[0049] (1.4) The dimensions of both the first and second scanning surfaces of the near-field measurement are set to L. x *L x The number of planar scanning points is set to N*N, and the amplitude of the antenna under test is sampled according to the number of scanning points to obtain the first planar amplitude sampling information M1 and the second planar amplitude sampling information M2 of the antenna under test.

[0050] Step 2: The amplitude information M1 and M2 of the two measured planes are processed by an optimization and restoration algorithm to obtain the optimal initial phase ψ' of the first plane.

[0051] Existing optimization algorithms include local optimization algorithms and global optimization algorithms. This step uses a global optimization algorithm to calculate the optimal initial phase ψ' of the first plane.

[0052] Reference Figure 2 The implementation of this step is as follows:

[0053] (2.1) Set a random phase ψ0, and obtain the initial electric field of the first plane of the high-frequency antenna from the random phase ψ0 and the amplitude information M1 of the first plane.

[0054] (2.2)Reference Figure 3 The antenna under test is placed on the xoy plane. According to the plane wave theory, the initial electric field E2 of the second plane is calculated from the initial electric field E1 of the first plane:

[0055]

[0056] Where, k z For space wavenumber, For two-dimensional Fourier operators, This is the two-dimensional Fourier inverse operator, where d1 is the distance between the first plane and the antenna under test, and d2 is the distance between the second plane and the antenna under test.

[0057] (2.3) Calculate the error fx2 between the amplitude abs(E2) of E2 and the amplitude information M2 of the second plane:

[0058]

[0059] Where N is the number of sampling points for the side length;

[0060] (2.4) Keeping the initial electric field E2 of the second plane unchanged, the amplitude abs(E2) of E2 is replaced by the amplitude information M2 of the second plane, resulting in the iterative electric field E2(M2) of the second plane = M2·e j·angle(E2) The second planar iterative electric field E2(M2) is then reduced using plane wave theory to obtain the first planar reduced electric field E1':

[0061]

[0062] Where, k z For space wavenumber, For two-dimensional Fourier operators, This is a two-dimensional Fourier inverse operator, where d1 is the distance between the first plane and the antenna under test, d2 is the distance between the second plane and the antenna under test, and the phase of E1' is angle(E1'), and the amplitude is abs(E1').

[0063] (2.5) Calculate the error fx1 between the amplitude abs(E1') of the reduced electric field E1' in the first plane and the amplitude information M1 of the first plane:

[0064]

[0065] (2.6) Calculate the total error value fx3 = fx1 + fx2, and compare it with the set minimum error value fx of the global optimization algorithm:

[0066] If fx3 ≤ fx, then retain the phase angle(E1') at this time, and let ψ' = angle(E1') as the phase of the initial restored electric field Ea of the first plane, thus obtaining the initial restored electric field Ea = M1·e of the first plane. j·ψ' Proceed to step 3;

[0067] Otherwise, proceed to step (2.7);

[0068] (2.7) Select the operation based on the number of calculations of fx3:

[0069] Set P as the current number of times to calculate fx3 in step (2.6), and Q as the maximum number of iterations. Compare the two:

[0070] If P = Q, find the minimum value fx3(min) in all fx3, and retain the corresponding phase angle(E1’). Let ψ' = angle(E1’) be the phase of the initial restored electric field Ea of the first plane, and obtain the initial restored electric field Ea of the first plane as Ea = M1·e j·ψ' , and execute step 3;

[0071] If P < Q, execute step (2.8);

[0072] (2.8) Optimize the phase of the initial electric field E1 of the first plane to obtain the random phase ψ1 of the initial electric field E1 of the first plane:

[0073] (2.8.1) Let the phase angle(E1’) of the initial electric field of the first plane be (θ1, φ1), and use a random number generator to generate N groups of x i =(θ i , φ i );

[0074] (2.8.2) Set a mutation probability P c = 0.9, and generate a random number urand for each group in x i . Compare urand with P c :

[0075] If the urand in the P i group is < P c , then mutate the phase of this group to obtain the mutated phase where (θ1, φ1) is the initial phase so far, and P r and P s are any two individual combinations that satisfy r ≠ s and are not equal to P i , and are the mutated phase combinations;

[0076] If urand ≥ P c , then this group does not need to be mutated, and its phase remains unchanged;

[0077] (2.8.3) Set the crossover probability factor P m = 0.1, and generate a random number rand for each mutated individual . Compare the crossover probability factor P m with rand:

[0078] If rand < P m Then, a crossover operation is performed on the phase of that individual, i.e. in, This represents the phase of the individual after the mutation. Indicates the phase of the individual before the mutation;

[0079] If rand≥P m Then the phase before the individual mutation is preserved. constant;

[0080] (2.8.4) The difference between the restored field amplitude and the measured field amplitude calculated from this phase is selected as the fitness function error:

[0081]

[0082] (2.8.5) The initial phase angle(E1') and the phase after mutation and crossover are respectively... Substituting these values ​​into the fitness function `error` in step (2.8.4), we can calculate the fitness function value `error(angle(E1'))` for `angle(E1')` and `error(angle(E1'))`. fitness function value

[0083] (2.8.6) Compare error(angle(E1')) and Size:

[0084] like Then, angle(E1') is taken as the random phase ψ1 of the initial electric field E1 of the first plane, and the process returns to step (2.2).

[0085] like Then Let ψ1 be the random phase of the initial electric field E1 in the first plane. Return to step (2.2);

[0086] Step 3: The restored phase ψ of the first plane is calculated using the initial electric field Ea of the first plane through an iterative Fourier algorithm.

[0087] Reference Figure 4 The specific implementation of this step is as follows:

[0088] (3.1) Based on the plane wave theory, the initial reduced electric field Ea of the first plane is used to calculate the initial reduced electric field Eb of the second plane:

[0089]

[0090] Where, kz For space wavenumber, For two-dimensional Fourier operators, This is a two-dimensional Fourier inverse operator, where d1 is the distance between the first plane and the antenna under test, d2 is the distance between the second plane and the antenna under test, and the phase of Eb is angle(Eb), and the amplitude is abs(Eb).

[0091] (3.2) Replace the initial reduced electric field amplitude Eb abs(Eb) of the second plane with the tangential field amplitude information M2 of the second plane, keeping the phase angle(Eb) of Eb unchanged, to obtain the iterative electric field Eb(M2) of the second plane = M2·e j ·angle(Eb) Then, using plane wave theory to calculate Eb(M2), the iteratively reduced electric field Ea' of the first plane is obtained:

[0092]

[0093] The phase of Ea' is angle(Ea'), and the amplitude is abs(Ea').

[0094] (3.3) Calculate the error fy1 between the amplitude abs(Ea') of the iteratively restored electric field Ea' of the first plane and the amplitude information M1 of the first plane:

[0095]

[0096] (3.4) Compare the error fy1 calculated in (3.3) with the minimum error value fy of the local optimum algorithm:

[0097] If fy1≤fy, then retain the phase angle(Ea') at this time, and let ψ=angle(Ea') as the phase of the final restored electric field E of the first plane, thus obtaining the final restored electric field E=M1·e of the first plane. j·ψ Proceed to step 4;

[0098] Otherwise, proceed to step (3.5);

[0099] (3.5) Select the operation based on the number of calculations of fy1:

[0100] Let U be the current number of times fy1 is calculated in step (3.3), and V be the maximum number of iterations, and then compare the two:

[0101] If U = V, then find the minimum value fy1(min) among all fy1 values, retain its corresponding phase angle(Ea'), and let ψ = angle(Ea') as the phase of the final restored electric field E of the first plane, thus obtaining the final restored electric field E = M1·e of the first plane.j·ψ Proceed to step 4;

[0102] Otherwise, the phase angle (Ea') of Ea' is kept unchanged, and the amplitude of Ea' is replaced by the amplitude information M1 of the first plane to obtain the initial restored electric field of the first plane Ea = M1·e j·angle(Ea') Return to step (3.1);

[0103] Step 4: Using the planar near-field and far-field transformation theory, based on the final restored electric field E of the first plane and the distance d1 between the first plane and the high-frequency antenna under test, the far-field radiation pattern of the high-frequency antenna is obtained.

[0104] (4.1) The final restored electric field E of the first plane is scanned once along the x-axis and once along the y-axis to obtain the electric field Ex in the x-direction and the electric field Ey in the y-direction of the final restored electric field E of the first plane.

[0105] (4.2) The wave spectral density Ax and Ay of the final reduced electric field E of the first plane are calculated from Ex and Ey respectively:

[0106]

[0107]

[0108] Where, k x k y k z Indicates a space beam;

[0109] (4.3) The far-field radiation pattern F of the high-frequency antenna is derived from the calculated electric field spectrum. θ (θ,φ) and F φ (θ,φ):

[0110] F θ (θ,φ)=jk(cosφA x +sinφA y ),

[0111] F φ (θ,φ)=jkcosθ(-sinφA x +cosφA y ),

[0112] Where (θ,φ) represents the beam direction of the high-frequency antenna, θ represents the angle between the line connecting the origin and the target and the positive z-axis, and φ represents the angle between the projection of the line connecting the origin and the target onto the xy plane and the positive x-axis.

[0113] The effects of the present invention can be further illustrated by the following experimental treatment.

[0114] I. Processing Conditions

[0115] Using MATLAB software

[0116] The phase distribution of the first plane of the phased array antenna is obtained through actual antenna measurements and used as the standard phase distribution of the first plane. The far-field radiation characteristics of the standard phased array antenna are obtained from the obtained phase distribution and amplitude information of the first plane.

[0117] II. Measured Phase Reconstruction Content

[0118] Actual reconstruction 1: The optimal phase distribution ψ' of the center row and column obtained from the initial reconstruction of this invention is compared with the measured phase distribution of the center row and column of a standard phased array antenna. The results are as follows: Figure 6 As shown. From Figure 6 It can be seen that the phase distribution of the center row and column obtained by the present invention is consistent with the trend of the phase distribution of the center row and column of the measured standard phased array antenna, indicating that the present invention can better restore the phase of the standard phased array antenna.

[0119] Actual measurement reconstruction 2: The phase distribution ψ of the first plane center row and column obtained by the final reconstruction of this invention is compared with the phase distribution of the first plane center row and column of the standard phased array antenna. The results are as follows: Figure 7 As shown, from Figure 7 It can be seen that the phase distribution restored by the present invention has a small error compared with the phase distribution of the first plane of the standard antenna, indicating that the present invention can restore the phase of the first plane of the phased array antenna very well.

[0120] Actual measurement restoration 3, the far-field radiation characteristics F calculated by this invention θ (θ,φ), F φ A comparison of the far-field radiation characteristics (θ,φ) and those of a standard phased array antenna yields the following results: Figure 8 As shown, from Figure 8 As can be seen, the antenna radiation characteristics calculated by this invention are in good agreement with the radiation characteristics of a standard phased array antenna in the main lobe region, indicating that this invention can obtain the far-field radiation characteristics of a standard phased array antenna and complete the measurement work of high-frequency antennas.

Claims

1. A phase-reduction based near-field antenna measurement method, characterized by, The method comprises the following steps: (1) measuring the tangential electric field amplitude information M1 and M2 of two planes of the near field of the high-frequency antenna according to the Nyquist sampling theorem; (2) setting a random phase ψ0, and obtaining the initial electric field of the first plane of the high-frequency antenna from the random phase ψ0 and the amplitude information M1 of the first plane (3) calculating the initial electric field E2 of the second plane from the initial electric field E1 of the first plane according to the plane wave P theory, and calculating the error fx2 of the amplitude abs(E2) of E2 and the amplitude information M2 of the second plane; (4) keeping the phase of E2 unchanged, angle(E2), and replacing the amplitude of E2, abs(E2), with the amplitude information M2 of the second plane, to obtain the second plane iterative electric field E2(M2) = M2 e j·angle(E2) reducing the second plane iterative electric field E2(M2) to the first plane reduced electric field E1' using the plane wave P theory, the phase of which is angle(E1') and the amplitude of which is abs(E1'); (5) calculating the error fx1 of the amplitude abs(E1') of the first plane restored electric field E1' and the amplitude information M1 of the first plane; (6) calculating the total error value fx3 = fx1 + fx2, and comparing it with the set global optimization algorithm minimum error value fx: If fx3≤fx, the phase angle(E1') at this time is reserved, and ψ' = angle(E1') is taken as the phase of the initial reduced electric field Ea of the first plane, and the initial reduced electric field Ea of the first plane is obtained as Ea = M1·e j·ψ , step (8) is executed; Otherwise, step (7) is performed; (7) performing iterative operation on the initial phase of the first plane: Setting P as the current number of times of calculating fx3 in step (6), Q as the maximum number of iterations, and comparing the two: If P = Q, find the minimum value fx3(min) in all fx3, and keep the phase angle(E1') corresponding to it, let ψ' = angle(E1') as the phase of the initial reduced electric field Ea of the first plane, get the initial reduced electric field Ea = M1·e j·ψ , execute step (8); If P < Q, the global optimization algorithm is performed on the phase of the first plane initial electric field E1 to obtain a random phase ψ1 of the first plane initial electric field E1, and let Return to step (3); (8) calculating the initial restored electric field Eb of the second plane from the initial restored electric field Ea of the first plane according to the plane wave P theory, the phase of Eb being angle(Eb), and the amplitude of Eb being abs(Eb); (9) The initial reduced electric field Eb of the second plane is replaced by the tangential field amplitude information M2 of the second plane, the phase angle(Eb) of Eb is kept unchanged, and the iterative electric field Eb(M2) of the second plane is obtained, Eb(M2)=M2·e j·angle(Eb) The iterative reduced electric field Ea' of the first plane is obtained by calculating Eb(M2) by using the plane wave P theory, the phase angle of the iterative reduced electric field Ea' is angle(Ea'), and the amplitude is abs(Ea'). (10) calculating the error fy1 of the amplitude abs(Ea') of Ea' and the amplitude information M1 of the first plane, and comparing it with the set local optimal algorithm minimum error value fy: If fy1≤fy, the phase angle(Ea') at this time is reserved, and let ψ=angle(Ea') be the phase of the final recovered electric field E of the first plane, and the final recovered electric field E of the first plane is obtained as M1·e j·ψ , step (12) is executed; Otherwise, step (11) is performed; (11) performing iterative operation on the phase of the first plane iterative restored electric field Ea': (11a) setting U as the current number of times of calculating fy1 in step (10), V as the maximum number of iterations, and comparing the two: If U=V, find the minimum value fy1(min) in all fy1, reserve its corresponding phase angle(Ea'), let ψ=angle(Ea') as the phase of the final recovered electric field E of the first plane, get the final recovered electric field E of the first plane=M1·e j·ψ , execute step (12); Otherwise, the phase of Ea' is kept unchanged, and the amplitude of Ea' is replaced by the amplitude information M of the first plane, and the initial reduced electric field of the first plane Eais obtained as Ea=M1·e j·angle(Ea ) , return to step (9);​ (12) using the plane near-far field transformation theory, obtaining the far field pattern of the high-frequency antenna according to the final restored electric field E of the first plane and the distance d1 of the first plane from the high-frequency antenna to be measured.

2. The method of claim 1, wherein, In step (1), the tangential electric field amplitude information M1 and M2 of two planes of the near field of the high-frequency antenna are measured according to the Nyquist sampling theorem, which is implemented as follows: (1a) the distance of the first plane from the antenna to be measured is d1, and the distance of the second plane from the antenna to be measured is d2; (1b) the minimum scan side length L of the second plane according to the measurement standard of near field antenna x satisfies: L x ≥2d2 tanθ+a Where θ is the maximum credible far field angle of the antenna to be measured, and a is the aperture width of the antenna to be measured. (1c) Determine the scanning interval m according to Nyquist sampling theorem, get the edge length scanning point number N = L of the second plane x / m; (1d) Set the scanning surface size of the first and second planes of the near-field measurement to L x *L x , the number of plane scanning points is N*N, and the amplitude sampling of the to-be-tested antenna is performed according to the scanning point number, to obtain the first plane amplitude sampling information M1 and the second plane amplitude sampling information M2 of the to-be-tested antenna.

3. The method of claim 1, wherein, In step (3), the initial electric field E2 of the second plane is calculated from the initial electric field E1 of the first plane according to the plane wave P theory, and the formula is as follows: where k z is the spatial wave number, is the two-dimensional Fourier operator, is the two-dimensional inverse Fourier operator, d1 is the distance of the first plane to the antenna under test, and d2 is the distance of the second plane to the antenna under test.

4. The method of claim 1, wherein, In step (3), the error fx2 of the amplitude abs(E2) of the electric field E2 of the second plane and the amplitude information M2 of the second plane is calculated, and the formula is as follows: Where N is the number of sampling points of the side length.

5. The method of claim 1, wherein, In step (5), the first plane restored electric field E1' is obtained from the second plane iterative electric field E2(M2) using the plane wave P theory, and the formula is as follows: where k z is the spatial wave number, is the two-dimensional Fourier operator, is the two-dimensional inverse Fourier operator, d1 is the distance of the first plane to the antenna under test, and d2 is the distance of the second plane to the antenna under test.

6. The method of claim 1, wherein, In step (5), the error fx1 of the amplitude abs(E1') of the first plane restored electric field E1' and the amplitude information M1 of the first plane is calculated, and the formula is as follows: Where N is the number of sampling points of the side length.

7. The method of claim 1, wherein, In step (7), the global optimization algorithm is performed on the phase angle(E1') of the initial electric field E1 of the first plane to obtain the random phase ψ1 of the initial electric field E1 of the first plane, which is implemented as follows: (7a) Set the phase of the first planar initial electric field angle(E1') = (θ1, φ1) and use a random number generator to produce N sets of x i = (θ i , φ i ) ; (7b) Set a mutation probability P c = 0.9, and for each group of x i generate a random number urand, and compare urand to P c : If P i urand < P in the group c Then the phase of this group needs to be considered. Perform a mutation operation to obtain the mutated phase. in (θ1,φ1) is the initial phase up to now, P r and P s It is any two that satisfy r≠s and are not equal to P. i Individual combinations, and For the mutated phase combination; If urand ≥ P c then the set does not need to be mutated, preserving its phase unchanged; (7c) Set the crossover probability factor P m = 0.1, and for each mutated individual Generate a random number rand, and the crossover probability factor P m Compare rand with P: If rand < P m then crossover operation is performed on the phase of the individual, i.e. wherein, denotes the phase of the individual after mutation, denotes the phase of the individual before mutation; If rand > P m then keep the phase of the individual unchanged before mutation unchanged. (7d) The difference between the reduced field amplitude calculated from the phase and the measured field amplitude is selected as the fitness function, i.e.: (7e) the initial phase angle (E1') and the mutated and crossed phase angle (E1'') are respectively substituted into the fitness function of step (7d) to calculate the fitness function value error(angle(E1')) of angle (E1'), and the fitness function value error(angle(E1'')) of angle (E1'') ​ (7f) compare the magnitude of error(angle(E1')) and error(angle(E1')) If angle(E1') is taken as the random phase ψ1 of the first plane initial electric field E1; If then the random phase ψ1 is taken as the first plane initial electric field E1.

8. The method of claim 1, wherein, Step (8) calculates the initial reduced electric field Eb of the second plane from the initial reduced electric field Ea of the first plane according to the plane wave spectrum theory, and the formula is as follows: where k z is the spatial wave number, is the two-dimensional Fourier operator, is the two-dimensional inverse Fourier operator, d1 is the distance of the first plane to the antenna under test, and d2 is the distance of the second plane to the antenna under test.

9. The method of claim 1, wherein, Step (9) calculates the iterative electric field Eb(M2) of the second plane using the plane wave spectrum theory to obtain the iterative reduced electric field Ea' of the first plane, and the formula is as follows: where k z is the spatial wave number, is the two-dimensional Fourier operator, is the two-dimensional inverse Fourier operator, d1 is the distance of the first plane to the antenna under test, and d2 is the distance of the second plane to the antenna under test.

10. The method of claim 1, wherein, Step (10) calculates the error fy1 of the amplitude abs(Ea') of the iterative reduced electric field Ea' of the first plane and the amplitude information M1 of the first plane, and the formula is as follows: Wherein, N is the number of sampling points of the side length.

11. The method of claim 1, wherein, Step (12) obtains the far-field pattern of the high-frequency antenna according to the final reduced electric field E of the first plane and the distance d1 between the first plane and the high-frequency antenna to be measured, and is realized as follows: (12a) The final reduced electric field E of the first plane is scanned along the x-axis and the y-axis respectively to obtain the x-direction electric field Ex and the y-direction electric field Ey of the final reduced electric field E of the first plane; (12b) The wave Pop Ax and Ay of the final reduced electric field E of the first plane are calculated from Ex and Ey respectively: where k x , k y , k z denotes a spatial beam; (12c) The far field pattern F of the high frequency antenna is calculated from the calculated reduced electric field wave θ (θ,φ) and F φ (θ,φ): F θ (θ,φ) = jk(cosφA x + sinφA y ), F φ (θ,φ) = jkcosθ(-sinφA x +cosφA y ), Wherein (θ, φ) represents the beam pointing of the high-frequency antenna, θ represents the included angle between the connecting line of the origin and the target and the positive direction of the z-axis, and φ represents the included angle between the projection line of the connecting line of the origin and the target in the xy plane and the positive direction of the x-axis.

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