An automated antenna cover data acquisition nulling method and system

Abstract

The application provides an automatic antenna cover data acquisition zero searching method and system, and belongs to the technical field of antenna cover testing. By collecting amplitude data of multiple frequency points, respective zero depth positions are identified, a zero depth position distribution interval, i.e. a Null list, is formed, and then in the interval where all the zero depth positions are distributed, a global optimal position that is most fair to all the frequency points is found through a minimum absolute error and optimization algorithm. Through the automatic zero position searching method, the best zero position can be given in real time, thereby solving the problems of aiming error and too large error of aiming error slope calculation caused by too large zero position offset of multi-frequency point data. The method performs global optimization from a higher dimension, ensures that the probe can collect data at a position closest to the real zero depth of all the frequency points in the whole test frequency band, and thus fundamentally improves the overall precision and consistency of the multi-frequency point test result.

Description

Technical Field

[0001] This invention belongs to the field of radome testing technology, specifically relating to an automated radome data acquisition and zero-finding method and system. Background Technology

[0002] As a critical component protecting antenna systems from external environmental influences, the electrical performance of a radome directly impacts the signal transmission and reception quality of the entire antenna device. Electrical performance testing has long been a crucial method for evaluating the quality of radome products, and boresight error (BSE), a core technical indicator for measuring radome electrical performance, has a decisive influence on the pointing accuracy of the antenna system. Therefore, achieving high-precision and high-stability boresight error measurement has always been an important research direction in radome technology and microwave testing.

[0003] In aiming error testing, the difference pattern of a single-pulse antenna is typically used for measurement. However, the gain level of the difference pattern is extremely low near the null point, making it susceptible to system noise and external interference, leading to null point positioning deviations and introducing significant testing errors. Therefore, establishing a reliable and accurate method for measuring and processing radome aiming line errors is crucial for improving the effectiveness and engineering applicability of test results. In calculating aiming error and its slope, baseline data without the radome is typically acquired first to calibrate the system's inherent offset. Subsequently, line data with the radome is collected at different angles, and the aiming error and slope are calculated by comparing and analyzing the data differences at corresponding frequencies. The accuracy of the data without the radome, especially the determination of the probe's null position, directly determines the reliability of all subsequent measurements and calculations. Therefore, the precision of the probe's null-finding operation becomes a critical factor affecting the overall testing accuracy.

[0004] Currently, the commonly used probe nulling method determines the probe null position based on the null depth position of the data from a single frequency point. While this method can accurately locate the null point at a single frequency, it exhibits significant limitations in multi-frequency testing scenarios. Because the null depth positions differ across frequencies, using only the null depth of a single frequency as the probe null position will introduce substantial systematic errors when calculating aiming errors at other frequencies. In other words, while existing methods can guarantee measurement accuracy at a single frequency, they struggle to maintain consistency and accuracy across the entire frequency band, thus limiting their application in broadband or multi-band radome testing.

[0005] Therefore, there is an urgent need to develop a new zero-finding method that can effectively reduce the error caused by inaccurate probe zero position, so as to improve the overall accuracy and reliability of radome aiming error and aiming error slope calculation under multi-frequency conditions, and further promote the development of radome testing technology and the improvement of practical engineering application level. Summary of the Invention

[0006] The purpose of this invention is to overcome the above-mentioned shortcomings and provide an automated method and system for radome data acquisition and zero-finding.

[0007] To achieve the above objectives, the present invention adopts the following technical solution:

[0008] In a first aspect, the present invention provides an automated method for zero-finding data acquisition from a radome, comprising the following steps:

[0009] Acquire signal amplitude data and test location without radome;

[0010] Determine the zero depth position based on the collected signal amplitude data;

[0011] Determine whether the zero-depth position coincides with the current test position. If they coincide, keep the probe position unchanged; otherwise, move the probe to the zero-depth position. After the probe is positioned, collect the data with the radome.

[0012] When acquiring signal amplitude data and test locations without an antenna radome, a one-dimensional list of real numbers is obtained when the test frequency is a single frequency point; and an n-dimensional list of real numbers is obtained when the test points are n frequency points.

[0013] The single-frequency point zero-finding method is as follows:

[0014] Acquire amplitude data of the probe at a location point and generate a location list. and amplitude data list :

[0015] ,

[0016] Where m is the number of test locations;

[0017] Find the list The index of the minimum value The location of zero depth is:

[0018] If x=0, the probe remains stationary and data with the cover is collected; if x≠0, the probe is moved to position x and then data with the cover is collected.

[0019] The method for finding zeros at the n frequency points is as follows:

[0020] Acquire amplitude data of the probe at m locations and generate a location list. and amplitude data list , A list of n-dimensional real numbers;

[0021] Based on the amplitude data of each frequency point in the amplitude data list, a candidate location list is generated, the distance sum of each candidate point in the candidate location list is calculated, a distance sum list is obtained, and the optimal zero-depth test location is determined based on the distance sum list.

[0022] Determine whether the optimal zero-depth test position is equal to the preset reference position; if the position is the reference position, do not move the probe to collect data with the radome; if it is not the reference position, move the probe to the optimal position to collect zero-depth data, and then collect data with the radome.

[0023] The amplitude data of each frequency point is verified for symmetry, and the frequency point data that fails the verification is removed.

[0024] Based on the amplitude data of the verified frequency points in the amplitude data list, the optimal zero-depth test position is determined. The specific method is as follows:

[0025] Find the minimum amplitude data at each frequency point The corresponding positions are summed up to form an initial list of zero-depth positions for all frequency points. ; Minimum value The corresponding position;

[0026] Calculate the maximum value max and minimum value min in the initial zero-depth position list Null, and generate a candidate position list containing multiple candidate points within the interval [min, max] with a preset step size d. ;

[0027] For the candidate location list For each candidate point in the list, calculate the sum of its distances to all points in the initial zero-depth position list Null, forming a distance sum list dis;

[0028] Find the minimum value in the distance and list dis, and the corresponding candidate point is the optimal zero-depth test position.

[0029] Take preset step size ,but Then calculate The sum of distances from each candidate point to all points in Null is calculated using the following formula:

[0030] Right now

[0031] Where int is the floor function, and distance list .

[0032] Secondly, the present invention provides an automated radome data acquisition and null-finding system, comprising:

[0033] The data acquisition module is used to acquire signal amplitude data and test location without an antenna radome.

[0034] The zero-depth position determination module is used to determine the zero-depth position based on the acquired signal amplitude data;

[0035] The judgment module is used to determine whether the zero-depth position coincides with the current test position. If they coincide, the probe position remains unchanged; otherwise, the probe is moved to the zero-depth position. After the probe is positioned, data with the radome is collected.

[0036] Thirdly, the present invention provides an electronic 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 an automated radome data acquisition and zero-finding method.

[0037] Fourthly, the present invention provides a storage medium storing a computer program thereon, wherein the computer program, when executed by a processor, implements the steps of an automated radome data acquisition and zero-finding method.

[0038] Compared with the prior art, the present invention has the following beneficial effects:

[0039] This invention provides an automated method and system for zero-point acquisition of radome data. By acquiring amplitude data from multiple frequency points, the zero-depth positions of each point are identified, forming a zero-depth position distribution interval, i.e., a null list. Then, within all zero-depth position distribution intervals, a globally optimal position that is fairest to all frequency points is found through minimizing absolute error and an optimization algorithm. This automated zero-point acquisition method provides the optimal zero-point in real time, thus solving the problem of excessive aiming error and excessive errors in the calculation of aiming error slope caused by excessive zero-point offset in multi-frequency data. This method performs global optimization from a higher dimension, ensuring that the probe can acquire data at a position closest to the true zero depth of all frequency points throughout the entire test frequency band, thereby fundamentally improving the overall accuracy and consistency of results in multi-frequency testing. By finding an optimal common test point within the frequency band, the baseline zero-point is found for data acquisition with or without a radome across the entire frequency band with only one zero-point location. It minimizes the number of probe movements while maintaining accuracy, achieving an optimal balance between accuracy and efficiency, making it particularly suitable for automated testing scenarios involving multiple frequency points and large-scale testing. The multi-frequency automatic zero-finding method described in this invention, through its core idea of ​​global optimization, successfully solves the key problems faced by traditional single-point zero-finding methods in multi-frequency testing, such as insufficient accuracy, strong subjectivity, and low efficiency, providing a solid technical foundation for achieving high-precision, high-efficiency, and fully automated radome electrical performance testing.

[0040] Furthermore, this invention fully proceduralizes and algorithms the zero-finding process. From data acquisition, zero-depth identification, optimal position calculation to the final probe movement decision, a complete closed-loop automated process is formed. This minimizes random errors introduced by human factors, standardizes the testing process, ensures reproducible results, and guarantees the objectivity and reliability of the data.

[0041] Furthermore, by using the minimization of absolute error as the optimization criterion, this method is less sensitive to individual anomalous zero-depth locations with large deviations compared to the least squares method, resulting in more stable results. This mathematical method provides a rigorous mathematical basis for determining the optimal location, ensuring that the final decision is no longer based on empirical estimation but on scientific judgment based on explicit numerical calculations. Attached Figure Description

[0042] Figure 1 This is a flowchart of the method of the present invention;

[0043] Figure 2 This is a zero-depth map of a single pitch difference scanned in this invention;

[0044] Figure 3 This is a system diagram of Embodiment 5 of the present invention. Detailed Implementation

[0045] To further understand the content of this invention, the invention will be described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the embodiments are merely illustrative and not limiting of the invention.

[0046] Example 1

[0047] like Figure 1 As shown, an automated method for acquiring and finding zeros in radome data includes the following steps:

[0048] S1: Obtain the signal amplitude data and test location without the radome, and obtain a one-dimensional or n-dimensional list of real numbers; This is a list of the amplitude data of the radome-less signal obtained from the test. This is a list of test locations.

[0049] S2: Determine the zero depth position based on the collected signal amplitude data;

[0050] S3: Determine whether the zero depth position coincides with the current test position (i.e., the current position of the probe). If they coincide, keep the probe position unchanged; otherwise, move the probe to the zero depth position and collect data with the radome after the probe is positioned.

[0051] Example 2

[0052] The signal amplitude data without the radome is collected to obtain a one-dimensional list of real numbers.

[0053] S1: Acquire amplitude data of the probe at a location point and generate a location list. and amplitude data list , and They are all one-dimensional lists of real numbers, that is

[0054] ,

[0055] Where m is the number of test locations.

[0056] S2: Determine if the zero depth position is at the test zero position. If it is, do not move the probe. If it is not, adjust the probe to the zero depth position according to the zero depth position.

[0057] That is, to obtain the list The index of the minimum value ,

[0058] make That is, the x position where the zero depth is located.

[0059] S3: If x=0, the probe remains stationary and data is collected with the cover on.

[0060] If x ≠ 0, move the probe to position x and then collect data with the cover on.

[0061] Assumption: , .

[0062] like for The minimum value, then For the zero depth position, according to To determine if the result is 0, proceed to the next data collection task.

[0063] like Figure 2 As shown, 17.5GHz is obviously asymmetrical. After removing this frequency point, the new zero depth position will be obtained by recalculating using the algorithm of this invention. The zero depth position of each frequency point will also be the global optimal solution.

[0064] Example 3

[0065] S1: When there are n (n>1) test frequency points, acquire the amplitude data of the probe at m location points and generate a location list. and amplitude data list , It is an n-dimensional list of real numbers, i.e.

[0066] ,

[0067] Where m is the number of test locations.

[0068] , .

[0069] Each element The set of amplitude values ​​measured at m locations corresponding to a given frequency point, i.e. ,i=1,2,…,n.

[0070] Furthermore, a symmetry verification is performed on the amplitude data of each frequency point, and frequency point data that fails the verification is removed. Specifically, for the amplitude data of any frequency point, the data to the left of its zero depth position is defined as the left half dataset; it is determined whether there are multiple preset specific ratio position points in the left half dataset; if they exist, the frequency point data is determined to have passed the symmetry verification and is retained; if they do not exist, the frequency point data is determined to be invalid and is removed from subsequent calculations.

[0071] Preferably, the preset multiple specific ratio position points include: 1 / 2 point, 1 / 4 point, 3 / 8 point, and 3 / 16 point. Taking points from half down can accommodate situations where amplitude values ​​on one side cannot be measured at certain special frequencies. This can shorten testing time in engineering without affecting actual needs. Check whether there are 4 position points corresponding to the specific ratio amplitude values. If so, the data is usable; otherwise, the frequency points corresponding to that set of amplitude data are unusable and need to be discarded. Only the optimal zero depth position of the usable frequency points is calculated.

[0072] S2: Based on the amplitude data of the verified frequency points in the amplitude data list, generate a candidate location list, calculate the distance sum of each candidate point in the candidate location list, obtain a list of distance sums, and determine the optimal zero-depth test location based on the list of distance sums, as follows:

[0073] 1) Find the minimum amplitude data for each frequency point. The corresponding positions are summed up for all frequency points to form an initial zero-depth position list NULL; if the minimum values ​​are respectively The corresponding zero depth position is ,make ; Minimum value The corresponding position;

[0074] 2) Calculate the maximum value max and minimum value min in the initial zero-depth position list Null, and generate a candidate position list containing multiple candidate points within the interval [min, max] with a preset step size d. ;

[0075] If all frequency amplitude data are almost symmetrical about the zero depth, then find the maximum value in Null. and minimum value ,make ;Will Split into List of points ;

[0076] 3) For the candidate location list For each candidate point in the list, calculate the sum of the absolute values ​​of its distances to all points in the initial zero-depth position list Null, forming a distance sum list dis;

[0077] Pick ,but Then calculate The sum of distances from each point in the null array to each point in the null array is calculated using the following formula:

[0078] Right now

[0079] Where int is the floor function, and distance list .

[0080] 4) Find the minimum value in the distance and list dis; the corresponding candidate point is the optimal zero-depth test position.

[0081] like ,but This is the optimal (least error) zero-depth test position.

[0082] S3: Determine whether the optimal zero-depth test position is equal to the preset reference position; if the position is the reference position, do not move the probe to collect data with the radome; if it is not the reference position, move the probe to the optimal position to collect zero-depth data, and then collect data with the radome. The specific formula is as follows:

[0083] like Then, without moving the probe, data acquisition is performed with the cover on.

[0084] like Then move the probe to Data was collected at the location with and without a cover.

[0085] Example 4

[0086] An automated radome data acquisition and null-finding system includes:

[0087] The data acquisition module is used to acquire signal amplitude data and test location without an antenna radome.

[0088] The zero-depth position determination module is used to determine the zero-depth position based on the acquired signal amplitude data;

[0089] The judgment module is used to determine whether the zero-depth position coincides with the current test position. If they coincide, the probe position remains unchanged; otherwise, the probe is moved to the zero-depth position. After the probe is positioned, data with the radome is collected.

[0090] Example 5

[0091] like Figure 3 As shown, the present invention also provides an electronic device 100 for an automated radome data acquisition and zero-finding method; the electronic device 100 includes a memory 101, at least one processor 102, a computer program 103 stored in the memory 101 and executable on the at least one processor 102, and at least one communication bus 104.

[0092] The memory 101 can be used to store the computer program 103. The processor 102 implements the steps of the automated radome data acquisition and nulling method described in Embodiment 1 by running or executing the computer program stored in the memory 101 and calling the data stored in the memory 101. The memory 101 may mainly include a program storage area and a data storage area. The program storage area may store the operating system, at least one application program required for a function (such as sound playback function, image playback function, etc.), etc.; the data storage area may store data created according to the use of the electronic device 100 (such as audio data), etc. In addition, the memory 101 may include non-volatile memory, such as hard disk, memory, plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, at least one disk storage device, flash memory device, or other non-volatile solid-state storage device.

[0093] The at least one processor 102 may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The processor 102 may be a microprocessor or any conventional processor. The processor 102 is the control center of the electronic device 100, connecting various parts of the electronic device 100 via various interfaces and lines.

[0094] The memory 101 in the electronic device 100 stores multiple instructions to implement an automated radome data acquisition and nulling method, and the processor 102 can execute the multiple instructions to achieve the following:

[0095] Acquire signal amplitude data and test location without radome;

[0096] Determine the zero depth position based on the collected signal amplitude data;

[0097] Determine whether the zero-depth position coincides with the current test position. If they coincide, keep the probe position unchanged; otherwise, move the probe to the zero-depth position. After the probe is positioned, collect the data with the radome.

[0098] Example 6

[0099] If the modules / units integrated in the electronic device 100 are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, and a read-only memory (ROM).

[0100] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0101] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0102] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0103] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0104] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. An automated method for acquiring and finding zeros in radome data, characterized in that, Includes the following steps: Acquire signal amplitude data and test location without radome; Determine the zero depth position based on the collected signal amplitude data; Determine whether the zero depth position coincides with the current test position. If they coincide, keep the probe position unchanged; otherwise, move the probe to the zero depth position. After the probe is positioned, collect the data with the radome. Specifically, when acquiring signal amplitude data and test location without an antenna cover, a one-dimensional real number list is obtained when the test frequency is a single frequency point; and an n-dimensional real number list is obtained when the test points are n frequency points. The method for finding zeros at the n frequency points is as follows: Acquire amplitude data of the probe at m locations and generate a location list. and amplitude data list , A list of n-dimensional real numbers; Based on the amplitude data of each frequency point in the amplitude data list, a candidate location list is generated, the distance sum of each candidate point in the candidate location list is calculated, a distance sum list is obtained, and the optimal zero-depth test location is determined based on the distance sum list. Determine whether the optimal zero-depth test position is equal to the preset reference position; if the position is the reference position, do not move the probe to collect data with the radome; if it is not the reference position, move the probe to the optimal position to collect zero-depth data, and then collect data with the radome.

2. The automated radome data acquisition and nulling method according to claim 1, characterized in that, The single-frequency point zero-finding method is as follows: Acquire amplitude data of the probe at a location point and generate a location list. and amplitude data list : , Where m is the number of test locations; Find the list The index of the minimum value The location of zero depth is: If x=0, the probe remains stationary and data with the cover is collected; if x≠0, the probe is moved to position x and then data with the cover is collected.

3. The automated radome data acquisition and nulling method according to claim 1, characterized in that, The amplitude data of each frequency point is verified for symmetry, and the frequency point data that fails the verification is removed.

4. The automated radome data acquisition and nulling method according to claim 3, characterized in that, Based on the amplitude data of the verified frequency points in the amplitude data list, the optimal zero-depth test position is determined. The specific method is as follows: Find the minimum amplitude data at each frequency point The corresponding positions are then aggregated across all frequency points to form an initial zero-depth position list. , ; Minimum value The corresponding position; Calculate the initial zero-depth position list Given the maximum value max and the minimum value min, generate a candidate location list containing multiple candidate points within the interval [min, max] with a preset step size d. ; For the candidate location list For each candidate point in the list, calculate the sum of its distances to all points in the initial zero-depth position list Null, forming a distance sum list dis; Find the minimum value in the distance and list dis, and the corresponding candidate point is the optimal zero-depth test position.

5. The automated radome data acquisition and nulling method according to claim 4, characterized in that, Take preset step size ,but Then calculate The sum of distances from each candidate point to all points in Null is calculated using the following formula: Right now Where int is the floor function, and the distance list... .

6. An automated radome data acquisition and null-finding system, based on the automated radome data acquisition and null-finding method according to any one of claims 1 to 5, characterized in that, include: The data acquisition module is used to acquire signal amplitude data and test location without an antenna radome. The zero-depth position determination module is used to determine the zero-depth position based on the acquired signal amplitude data; The judgment module is used to determine whether the zero-depth position coincides with the current test position. If they coincide, the probe position remains unchanged; otherwise, the probe is moved to the zero-depth position. After the probe is positioned, data with the radome is collected.

7. An electronic 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 automated radome data acquisition and zero-finding method according to any one of claims 1 to 5.

8. A storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the automated radome data acquisition and zero-finding method according to any one of claims 1 to 5.

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