Antenna pattern data processing method and apparatus, device, and storage medium

Abstract

This application relates to the field of wireless communication technology, and provides an antenna pattern data processing method, apparatus, device, and storage medium. The method includes: controlling the antenna under test to rotate according to a predefined motion curve and acquiring a first antenna pattern of the antenna under test; performing SG filtering on the first antenna pattern to convert it into a smoother and more continuous second antenna pattern; decomposing the second antenna pattern into approximation coefficients and detail coefficients; performing wavelet threshold denoising on the detail coefficients, and reconstructing the approximation coefficients and the wavelet threshold denoised detail coefficients into a third antenna pattern to preserve the main lobe and side lobe structure and suppress high-frequency noise; and extracting antenna feature parameters from the third antenna pattern. Embodiments of this application can improve the automation level and data reliability of antenna pattern processing.

Description

Technical Field

[0001] This application relates to the field of wireless communication technology, and in particular to an antenna pattern data processing method, apparatus, device, and storage medium. Background Technology

[0002] In fields such as wireless communication, satellite telemetry and control, and unmanned aerial vehicles (UAVs), antenna radiation patterns are the core basis for evaluating antenna radiation performance. The accurate extraction of its key parameters (such as main lobe direction, beamwidth, and sidelobe level) directly affects the overall system performance.

[0003] Traditional antenna pattern data processing methods mainly rely on manual interpretation combined with simple thresholding methods, or employ a single filtering and smoothing technique, which has the following inherent drawbacks: 1. The contradiction between noise sensitivity and feature distortion: To suppress measurement noise, fixed-parameter moving averages or low-pass filtering are often used, but this easily leads to feature distortions such as main lobe peak attenuation and beamwidth broadening, seriously affecting parameter accuracy. 2. Insufficient automation and accuracy: Existing automated methods are mostly based on peak search and fixed threshold judgment, which have poor robustness to noise and sidelobe interference.

[0004] Therefore, there is an urgent need for a technical solution that can improve the automation level and data reliability of antenna pattern processing. Summary of the Invention

[0005] The purpose of this application is to provide an antenna pattern data processing method, apparatus, device, and storage medium to improve the automation level and data reliability of antenna pattern processing.

[0006] To achieve the above objectives, in one aspect, embodiments of this application provide an antenna pattern data processing method, including: Control the antenna under test to rotate according to a predefined motion curve, and acquire the first antenna pattern of the antenna under test; The first antenna pattern is subjected to SG filtering to transform it into a smoother and more continuous second antenna pattern. The second antenna pattern is decomposed into approximation coefficients and detail coefficients; The detail coefficients are subjected to wavelet threshold denoising, and the approximation coefficients and the wavelet threshold denoised detail coefficients are reconstructed into a third antenna pattern to preserve the main lobe and side lobe structure and suppress high-frequency noise. Extract the antenna feature parameters from the third antenna pattern.

[0007] In the processing method of this application embodiment, the motion curve includes an acceleration segment, a constant speed segment, and a deceleration segment; controlling the antenna under test to rotate according to a predefined motion curve and acquiring the first antenna pattern of the antenna under test includes: The rotating platform, on which the antenna under test is fixed, is controlled to move in a manner that includes the acceleration segment, the constant speed segment, and the deceleration segment, and the first antenna pattern of the antenna under test is synchronously acquired at a constant angular velocity during the constant speed segment.

[0008] In the processing method of this application embodiment, the method further includes: During the SG filtering process on the first antenna pattern, the filtering parameters corresponding to the SG filtering are dynamically adjusted; and / or, During the wavelet threshold denoising process on the detail coefficients, the filtering parameters corresponding to the wavelet threshold denoising are dynamically adjusted.

[0009] In the processing method of this application embodiment, the dynamic adjustment of the filtering parameters corresponding to the SG filter includes: Determine the real-time steepness of the main lobe region in the first antenna pattern; The window length of the SG filter is adaptively adjusted based on the real-time steepness; the window length is negatively correlated with the real-time steepness.

[0010] In the processing method of this application embodiment, the step of dynamically adjusting the filtering parameters corresponding to the wavelet threshold denoising includes: Determine the noise level in the first antenna pattern; The number of decomposition layers and the denoising threshold of the wavelet threshold denoising are adaptively adjusted based on the noise level; the number of decomposition layers is positively correlated with the noise level, and the denoising threshold is positively correlated with the noise level.

[0011] In the processing method of this application embodiment, the step of extracting antenna feature parameters from the third antenna pattern includes: Determine the angular range of the main lobe region of the third antenna pattern, and extract the main lobe peak value from the angular range of the main lobe region; Determine the specified power points on both sides of the main lobe peak, and define the main lobe region located between the specified power points as the beamwidth; Determine the envelope and gain of the third antenna pattern.

[0012] On the other hand, embodiments of this application also provide an antenna pattern data processing apparatus, including: The acquisition module is used to control the antenna under test to rotate according to a predefined motion curve and to acquire the first antenna pattern of the antenna under test. The filtering module is used to perform SG filtering on the first antenna pattern to convert the first antenna pattern into a second antenna pattern that tends to be smooth and continuous. The decomposition module is used to decompose the second antenna pattern into approximation coefficients and detail coefficients; The denoising module is used to perform wavelet threshold denoising on the detail coefficients and reconstruct the approximation coefficients and the wavelet threshold denoised detail coefficients into a third antenna pattern to preserve the main lobe and side lobe structure and suppress high-frequency noise. The extraction module is used to extract antenna feature parameters from the third antenna pattern.

[0013] On the other hand, embodiments of this application also provide a computer device, including a memory, a processor, and a computer program stored in the memory, wherein the computer program, when run by the processor, executes instructions of the above-described method.

[0014] On the other hand, embodiments of this application also provide a computer storage medium storing a computer program thereon, wherein the computer program, when run by the processor of a computer device, executes instructions for the above-described method.

[0015] On the other hand, this application also provides a computer program product, which includes a computer program that, when run by the processor of a computer device, executes instructions for the above-described method.

[0016] As can be seen from the technical solutions provided in the embodiments of this application above, by performing SG filtering on the noisy original antenna pattern, the smoothness and continuity of the antenna pattern can be enhanced, thereby transforming the original antenna pattern into a smoother and more continuous antenna pattern. Using the smoother and more continuous antenna pattern as prior knowledge, wavelet threshold denoising is then performed on the antenna pattern, which can effectively suppress high-frequency noise while preserving important physical features such as the main lobe and side lobes (i.e., balancing the structural conformity preservation and noise suppression of the antenna pattern). This provides accurate data support for the automatic extraction of antenna feature parameters, thereby improving the automation level and data reliability of antenna pattern processing. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. In the drawings: Figure 1 A schematic diagram of an antenna pattern data processing system in some embodiments of this application is shown; Figure 2 A flowchart of an antenna pattern data processing method in some embodiments of this application is shown; Figure 3 It shows Figure 2The flowchart shown illustrates the method for dynamically adjusting the filter parameters corresponding to the SG filter. Figure 4 It shows Figure 2 The flowchart shown illustrates the method for dynamically adjusting the filtering parameters corresponding to wavelet threshold denoising. Figure 5 A schematic diagram of the original antenna pattern in an exemplary embodiment of this application is shown; Figure 6 It shows Figure 5 The diagram shows the gain and physical layer parameters of the antenna pattern obtained after processing the original antenna pattern. Figure 7 It shows Figure 6 A schematic diagram of the superimposed power spectrum of the antenna pattern shown; Figure 8 It shows Figure 6 A schematic diagram of the power amplitude of the antenna pattern shown; Figure 9 This application shows a structural block diagram of an antenna pattern data processing apparatus in some embodiments; Figure 10 A structural block diagram of a computer device in some embodiments of this application is shown.

[0018] [Explanation of Labels in the Attached Image]

[0019] 10. The antenna under test; 20. Rotate the platform; 30. Data acquisition equipment; 40. Host computer; 91. Data Acquisition Module; 92. Filtering module; 93. Decomposition Module; 94. Noise reduction module; 95. Extraction module; 1002. Computer equipment; 1004, Processor; 1006. Memory; 1008. Drive mechanism; 1010. Input / output interface; 1012. Input devices; 1014. Output devices; 1016. Presentation device; 1018. Graphical User Interface; 1020. Network interface; 1022. Communication link; 1024. Communication bus. Detailed Implementation

[0020] To enable those skilled in the art to better understand the technical solutions in this application, the technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of this application.

[0021] Antenna radiation patterns are graphical descriptions of the distribution characteristics (e.g., angle-gain or angle-power) of electromagnetic wave energy radiated or received by an antenna in various spatial directions. This application provides an antenna radiation pattern processing scheme based on SG filtering (Savitzky-Golay filtering) and wavelet threshold denoising, to improve the automation and data reliability of antenna radiation pattern processing. By applying SG filtering to the noisy original antenna radiation pattern, the smoothness and continuity of the antenna radiation pattern can be enhanced, transforming the original antenna radiation pattern into a more smooth and continuous one. Using this more smooth and continuous antenna radiation pattern as prior knowledge, wavelet threshold denoising is then applied to it, effectively suppressing high-frequency noise while preserving important physical features such as the main lobe and side lobes (i.e., balancing the structure conformance and noise suppression of the antenna radiation pattern). This provides accurate data support for automatically extracting antenna feature parameters (main lobe peak value, wavelength, envelope, etc.), thereby improving the automation and data reliability of antenna radiation pattern processing. It is beneficial for meeting the dual requirements of accuracy and efficiency in next-generation antenna testing systems and is applicable to scenarios such as batch antenna testing, communication system debugging, and satellite payload calibration.

[0022] Figure 1The diagram shows a schematic of an antenna pattern data processing system in some embodiments of this application; the application environment includes an antenna under test 10, a rotating platform 20, a data acquisition device 30, and a host computer 40. The antenna under test 10 is detachably fixed to the rotating platform 20. The host computer 40 can control the rotating platform 20 to rotate according to a predefined motion curve, thereby controlling the antenna under test 10 to rotate synchronously according to the same motion curve. During the rotation of the antenna under test 10, the host computer 40 can control the acquisition device 30 to scan and acquire the original antenna pattern (first antenna pattern) of the antenna under test 10, perform SG filtering (i.e., Savitzky-Golay filtering) on ​​the original antenna pattern to convert it into a smoother and more continuous antenna pattern (second antenna pattern). The smoother and more continuous antenna pattern is decomposed into approximation coefficients and detail coefficients. Wavelet threshold denoising is performed on the detail coefficients, and the approximation coefficients and the wavelet threshold denoised detail coefficients are reconstructed into a new antenna pattern (third antenna pattern) to preserve the main lobe and side lobe structure and suppress high-frequency noise. Then, antenna feature parameters are extracted from the new antenna pattern.

[0023] In some embodiments of this application, the antenna under test can be configured as a transmitting or receiving antenna on electronic devices in fields such as wireless communication, satellite remote sensing, and unmanned systems. These electronic devices may include, for example, mobile terminals (such as smartphones), tablets, laptops, wearable devices, virtual reality (VR) devices, augmented reality (AR) devices, wireless communication devices, wireless terminals in industrial control, wireless terminals in self-driving (such as drones), wireless terminals in remote medical surgery, wireless terminals in smart grids, wireless terminals in transportation safety, wireless terminals in smart cities, wireless terminals in smart homes, Internet of Things (IoT) devices, narrowband Internet of Things (NB-IoT) devices, vehicle-to-everything (V2X) devices, in-vehicle equipment, shipborne equipment, satellite-borne base stations, and satellites.

[0024] In some embodiments of this application, the rotating platform is a mechanical device that carries and controls the precise angular rotation of the antenna under test in space. For example, it can be a precision electric rotating platform. The rotating platform can have programmable motion control and high-precision angle feedback functions. The programmable motion control function means that the rotating platform can receive instructions from a host computer and execute preset angle ranges, speeds, and accelerations (i.e., realize a continuous scanning mode of acceleration-uniform speed-deceleration). The high-precision angle feedback function means that the rotating platform has a built-in high-resolution angular velocity sensor (such as an encoder) that can provide real-time and accurate feedback of the rotation angle position for synchronization with parameters such as the acquired RF power value or RF gain value.

[0025] In some embodiments of this application, the acquisition device may include a gain acquisition device (such as a spectrum analyzer, vector network analyzer, etc.) and an angular velocity acquisition device (such as an encoder on a rotating platform, etc.). Taking a spectrum analyzer and an encoder as examples, under the control commands of the host computer, the spectrum analyzer can continuously sample the transmit / receive signals of the antenna under test; the encoder returns the angle sequence in real time, and the spectrum analyzer returns the power sequence in real time. The two are aligned in the host computer through precise timestamps to form the original (initial) antenna pattern.

[0026] In some embodiments of this application, the host computer can be a computer device such as a desktop computer or a laptop computer. Of course, the host computer is not limited to the aforementioned physical computer device; it can also be software running on the aforementioned computer device that provides processing logic for antenna pattern data.

[0027] This application provides an antenna pattern data processing method, which can be applied to the aforementioned host computer side. (Refer to...) Figure 2 As shown, in some embodiments of this application, the antenna pattern data processing method may include the following steps: Step 201: Control the antenna under test to rotate according to a predefined motion curve, and acquire the first antenna pattern of the antenna under test.

[0028] In some embodiments of this application, the predefined motion curve includes an acceleration segment, a constant speed segment, and a deceleration segment; correspondingly, controlling the antenna under test to rotate according to the predefined motion curve and acquiring the first antenna pattern of the antenna under test may include: controlling a rotating platform on which the antenna under test is fixed to move in a manner that includes the acceleration segment, the constant speed segment, and the deceleration segment, and synchronously acquiring the first antenna pattern of the antenna under test at a constant angular velocity during the constant speed segment.

[0029] In some embodiments of this application, the antenna under test can be pre-fixed to the rotating platform, and relevant parameters of the motion curve (such as rotation angle range, speed, and acceleration) can be set to form a motion curve including an acceleration segment, a constant speed segment, and a deceleration segment. Setting an "acceleration segment" allows the turntable to quickly reach a target angular velocity; the stage of maintaining the target angular velocity is the "constant speed segment." In the "constant speed segment," time and angle have a linear relationship. At this time, the antenna power values ​​and other data collected synchronously can be mapped very accurately to each angle at equal or known intervals, ensuring the physical accuracy of the original data; the "deceleration segment" is to achieve a rapid and smooth stop and prepare for the next scan.

[0030] Step 202: Perform SG filtering on the first antenna pattern to convert the first antenna pattern into a smoother and more continuous second antenna pattern.

[0031] Savitzky-Golay (SG) filtering, also known as least squares smoothing filtering, is a digital filtering method based on local polynomial least squares fitting. Its core idea is not to simply average the data within a window, but to fit a polynomial curve to the data points within the window, and to use the value of this fitted curve at the center point of the window as the smoothed output.

[0032] Given an original discrete signal y={y_{N} of length N i Define a window length of 2k+1 and a fitting order d (d < 2k+1). Within each sliding window, solve the following least-squares fitting problem:

[0033] In the current window, for data points i Smoothing results That is:

[0034] in, j For relative position index within the window, k The number of points on one side; a 0、 a 1, ... a d These are the polynomial coefficients obtained by least-squares fitting within each sliding window. a 0 is the center point of the polynomial in the window; a n The coefficients of the nth polynomial obtained by least squares fitting within the window; y i+j The original signal is at position i + j The result is a smooth one.

[0035] SG filtering allows for the simultaneous output of the first and second derivatives of the smoothed curve (for main lobe extraction):

[0036] in, These are the filter coefficients used to calculate the nth derivative, which depend on the window size and the polynomial order. x It refers to the relative position of the data points within the sliding window; Step 203: Decompose the second antenna pattern into approximation coefficients and detail coefficients.

[0037] In some embodiments of this application, decomposing the second antenna pattern into approximation coefficients and detail coefficients means performing wavelet decomposition on the second antenna pattern to decompose the signal x(t) of the second antenna pattern into approximation coefficients cA and detail coefficients cD.

[0038] Where t is time (corresponding to angular position); cA k This is an approximation coefficient for the angular position k; Ф j0,k(t) Let be the scaling function of angular position k(t) at a fixed scale j0; J is the number of scales (i.e., the number of decomposition layers); cD j,k Here is the detail factor at angular position k at scale j; ψ j,k(t) Let be the wavelet function of the angular position k(t) at scale j.

[0039] Step 204: Perform wavelet threshold denoising on the detail coefficients, and reconstruct the third antenna pattern from the approximation coefficients and the wavelet threshold denoised detail coefficients to preserve the main lobe and side lobe structure and suppress high-frequency noise.

[0040] In some embodiments of this application, wavelet thresholding denoising of the detail coefficients means: for each level of detail coefficient d, soft thresholding is applied. ;in, These are the new detail coefficients after soft thresholding, and sign(d) is the sign function of d. The absolute value of d. T Threshold and T = σ is the standard deviation of the noise estimate, and n is the data length.

[0041] Step 205: Extract the antenna feature parameters from the third antenna pattern.

[0042] In some embodiments of this application, extracting antenna feature parameters from the third antenna pattern may include: (1) Determine the angular range of the main lobe region of the third antenna pattern [ θ min , θ max And extract the main lobe peak value from the angular range of the main lobe region.

[0043] in, θ min , θ max These represent the lower and upper limits of the angle of the main lobe region, respectively. θ 0 The angle corresponding to the main lobe peak. G s ( θ ( ) is the angle θ The corresponding main lobe value, G 0 This is the main lobe value (i.e., the main lobe peak value) corresponding to angle 0.

[0044] (2) Determine the specified power points on both sides of the main lobe peak, and determine the main lobe region located between the specified power points as the beamwidth.

[0045] For example, in some embodiments, a half-power point (i.e., a 3dB wavelength) is used as an example for a specified power point: Left half-power point of the main lobe peak: G s ( θ 1)= G 0 -3dB, θ 1< θ 0 Half-power point to the right of the main lobe peak: G s ( θ 2)= G 0 -3dB, θ 2> θ 0 Beamwidth: BW= θ 2- θ 1 In other embodiments, the specified power point may also be other values ​​such as 10dB bandwidth.

[0046] (3) Determine the envelope and gain of the third antenna pattern and other antenna characteristic parameters.

[0047] In other embodiments of this application, the method may further include: dynamically adjusting the filtering parameters corresponding to the SG filtering during the SG filtering process on the first antenna pattern. Specifically, refer to... Figure 3As shown, dynamically adjusting the filtering parameters (such as window length) corresponding to the SG filter can include the following steps: Step 301: Determine the real-time steepness of the main lobe region in the first antenna pattern.

[0048] Real-time steepness refers to a parameter calculated in real time to quantify the degree of change in the main lobe edge.

[0049] Step 302: Adaptively adjust the window length of the SG filter based on the real-time steepness.

[0050] The window length is negatively correlated with the real-time steepness; thus, the problems of smoothing peaks (insufficient preservation of high-order details near the main lobe) when the window is too large or the smoothing effect is affected when the window is too small can be reduced or avoided, thereby achieving higher-order smoothness and boundary robustness.

[0051] In other embodiments of this application, the method may further include: dynamically adjusting the filtering parameters (such as the number of decomposition layers and the denoising threshold) corresponding to the wavelet threshold denoising during the wavelet threshold denoising process on the detail coefficients. Specifically, refer to... Figure 4 As shown, dynamically adjusting the filtering parameters corresponding to the wavelet threshold denoising may include the following steps: Step 401: Determine the noise level in the first antenna pattern.

[0052] Noise level can refer to, for example, the noise standard deviation of the main lobe region.

[0053] Step 402: Adaptively adjust the number of decomposition layers and the denoising threshold of the wavelet threshold denoising based on the noise level; the number of decomposition layers is positively correlated with the noise level, and the denoising threshold is also positively correlated with the noise level. This further improves the effect of preserving the main lobe and side lobe structure while suppressing high-frequency noise.

[0054] Figure 5 The diagram illustrates the original antenna radiation pattern acquired in an exemplary embodiment of this application; in this original antenna radiation pattern, the horizontal axis represents angle, and the vertical axis represents power (dB). Based on the antenna radiation pattern data processing method described above in this application, the following can be obtained: Figure 6 The processed antenna pattern is shown; in Figure 6 In the diagram, G1 in the AZ direction represents the peak gain of the azimuth (horizontal) radiation pattern, G2 in the EL direction represents the peak gain of the elevation (vertical) radiation pattern, PHY Base represents the beamwidth of the antenna physical layer's basic gain, PHY+3dB represents the beamwidth corresponding to a 3dB decrease in the antenna physical layer's gain, PHY+6dB represents the beamwidth corresponding to a 6dB decrease in the antenna physical layer's gain, and PHY compensation represents the peak gain after compensation of the antenna physical layer's gain. Figure 7, Figure 8 They are shown respectively Figure 6 The image shows the superimposed power spectrum and power amplitude of the antenna pattern. Figure 7 In the diagram, the horizontal axis represents the angle index, the vertical axis represents the gain (dB), the central red dot represents the gain corresponding to the main lobe peak, and the red dots on either side of the central red dot represent the gains corresponding to the left and right half-power points, respectively. Figure 8 In the diagram, the horizontal axis represents the angle index, and the vertical axis represents the power amplitude (dB).

[0055] Although the process described above includes multiple operations that occur in a specific order, it should be clearly understood that these processes may include more or fewer operations that can be executed sequentially or in parallel (e.g., using parallel processors or a multithreaded environment).

[0056] Corresponding to the antenna pattern data processing method described above, this application also provides an antenna pattern data processing device, which can be configured on the aforementioned host computer, as shown in the reference. Figure 9 As shown, in some embodiments of this application, the antenna pattern data processing apparatus may include: The acquisition module 91 is used to control the antenna under test to rotate according to a predefined motion curve and to acquire the first antenna pattern of the antenna under test. The filtering module 92 is used to perform SG filtering on the first antenna pattern to convert the first antenna pattern into a second antenna pattern that tends to be smooth and continuous. Decomposition module 93 is used to decompose the second antenna pattern into approximation coefficients and detail coefficients; The denoising module 94 is used to perform wavelet threshold denoising on the detail coefficients and reconstruct the approximation coefficients and the wavelet threshold denoised detail coefficients into a third antenna pattern to preserve the main lobe and side lobe structure and suppress high-frequency noise. Extraction module 95 is used to extract antenna feature parameters from the third antenna pattern.

[0057] For ease of description, the above devices are described separately by function as various units. Of course, in implementing this application, the functions of each unit can be implemented in one or more software and / or hardware.

[0058] Embodiments of this application also provide a computer device. For example... Figure 10As shown, in some embodiments of this application, the computer device 1002 may include one or more processors 1004, such as one or more central processing units (CPUs) or graphics processing units (GPUs), each of which may implement one or more hardware threads. The computer device 1002 may also include any memory 1006 for storing any kind of information such as code, settings, data, etc. In one specific embodiment, a computer program is stored on the memory 1006 and can run on the processor 1004. When the computer program is run by the processor 1004, it can execute instructions of the antenna pattern data processing method described in any of the above embodiments. Non-limitingly, for example, the memory 1006 may include any type of RAM, any type of ROM, flash memory, hard disk, optical disk, etc. More generally, any memory can use any technology to store information. Further, any memory can provide volatile or non-volatile retention of information. Further, any memory may represent a fixed or removable component of the computer device 1002. In one scenario, when processor 1004 executes associated instructions stored in any memory or combination of memories, computer device 1002 can perform any operation of the associated instructions. Computer device 1002 also includes one or more drive mechanisms 1008 for interacting with any memory, such as hard disk drive mechanisms, optical disk drive mechanisms, etc.

[0059] Computer device 1002 may also include an input / output interface 1010 (I / O) for receiving various inputs (via input device 1012) and providing various outputs (via output device 1014). A specific output mechanism may include a presentation device 1016 and an associated graphical user interface 1018 (GUI). In other embodiments, the input / output interface 1010 (I / O), input device 1012, and output device 1014 may be omitted, and the device may function solely as a computer device within a network. Computer device 1002 may also include one or more network interfaces 1020 for exchanging data with other devices via one or more communication links 1022. One or more communication buses 1024 couple the components described above together.

[0060] The communication link 1022 can be implemented in any way, such as via a local area network, a wide area network (e.g., the Internet), a point-to-point connection, or any combination thereof. The communication link 1022 may include any combination of hardwired links, wireless links, routers, gateway functions, name servers, etc., governed by any protocol or combination of protocols.

[0061] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), computer-readable storage media, and computer program products according to some embodiments of this application. 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 processor to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processor, create a machine 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.

[0062] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processor 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.

[0063] These computer program instructions may also be loaded onto a computer or other programmable data processor, causing a series of operational steps to be performed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable device 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.

[0064] In a typical configuration, a computer device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0065] Memory may include non-persistent storage in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0066] Computer-readable media, including both permanent and non-permanent, removable and non-removable media, can store information using any method or technology. Information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by computer equipment. As defined in this application, computer-readable media does not include transient media, such as modulated data signals and carrier waves.

[0067] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, embodiments of this application can take the form of entirely hardware embodiments, entirely software embodiments, or embodiments combining software and hardware aspects. Furthermore, embodiments of this application can take the form of computer program products implemented 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.

[0068] The embodiments of this application can be described in the general context of computer-executable instructions, such as program modules, that are executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform a specific task or implement a specific abstract data type. The embodiments of this application can also be practiced in distributed computing environments where tasks are performed by remote processors connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0069] It should also be understood that, in the embodiments of this application, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Additionally, the character " / " in this document generally indicates that the preceding and following related objects have an "or" relationship.

[0070] The various embodiments in this application are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the system embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions of the method embodiments.

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

[0072] The above description is merely an embodiment of this application and is not intended to limit the scope of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.

Claims

1. A method for processing antenna pattern data, characterized in that, include: Control the antenna under test to rotate according to a predefined motion curve, and acquire the first antenna pattern of the antenna under test; The first antenna pattern is subjected to SG filtering to transform it into a smoother and more continuous second antenna pattern. The second antenna pattern is decomposed into approximation coefficients and detail coefficients; Wavelet threshold denoising is performed on the detail coefficients, and the approximation coefficients and wavelet threshold denoised detail coefficients are reconstructed into a third antenna pattern to preserve the main lobe and side lobe structure and suppress high-frequency noise. Extract the antenna feature parameters from the third antenna pattern.

2. The processing method according to claim 1, characterized in that, The motion curve includes an acceleration segment, a constant speed segment, and a deceleration segment; The control of the antenna under test to rotate according to a predefined motion curve and the acquisition of the first antenna radiation pattern of the antenna under test include: The rotating platform, on which the antenna under test is fixed, is controlled to move in a manner that includes the acceleration segment, the constant speed segment, and the deceleration segment, and the first antenna pattern of the antenna under test is synchronously acquired at a constant angular velocity during the constant speed segment.

3. The processing method according to claim 1, characterized in that, The method further includes: During the SG filtering process on the first antenna pattern, the filtering parameters corresponding to the SG filtering are dynamically adjusted; and / or, During the wavelet threshold denoising process on the detail coefficients, the filtering parameters corresponding to the wavelet threshold denoising are dynamically adjusted.

4. The processing method according to claim 3, characterized in that, The dynamic adjustment of the filtering parameters corresponding to the SG filter includes: Determine the real-time steepness of the main lobe region in the first antenna pattern; The window length of the SG filter is adaptively adjusted based on the real-time steepness; the window length is negatively correlated with the real-time steepness.

5. The processing method according to claim 3, characterized in that, The dynamic adjustment of the filtering parameters corresponding to the wavelet threshold denoising includes: Determine the noise level in the first antenna pattern; The number of decomposition layers and the denoising threshold of the wavelet threshold denoising are adaptively adjusted based on the noise level; the number of decomposition layers is positively correlated with the noise level, and the denoising threshold is positively correlated with the noise level.

6. The processing method according to claim 1, characterized in that, The extraction of antenna feature parameters from the third antenna pattern includes: Determine the angular range of the main lobe region of the third antenna pattern, and extract the main lobe peak value from the angular range of the main lobe region; Determine the specified power points on both sides of the main lobe peak, and define the main lobe region located between the specified power points as the beamwidth; Determine the envelope and gain of the third antenna pattern.

7. An antenna pattern data processing device, characterized in that, include: The acquisition module is used to control the antenna under test to rotate according to a predefined motion curve and to acquire the first antenna pattern of the antenna under test. The filtering module is used to perform SG filtering on the first antenna pattern to convert the first antenna pattern into a second antenna pattern that tends to be smooth and continuous. The decomposition module is used to decompose the second antenna pattern into approximation coefficients and detail coefficients; The denoising module is used to perform wavelet threshold denoising on the detail coefficients and reconstruct the approximation coefficients and the wavelet threshold denoised detail coefficients into a third antenna pattern to preserve the main lobe and side lobe structure and suppress high-frequency noise. The extraction module is used to extract antenna feature parameters from the third antenna pattern.

8. A computer device comprising a memory, a processor, and a computer program stored in the memory, characterized in that, When the computer program is run by the processor, it executes the instructions of the method according to any one of claims 1-6.

9. A computer storage medium having a computer program stored thereon, characterized in that, When the computer program is run by the processor of the computer device, it executes the instructions of the method according to any one of claims 1-6.

10. A computer program product, characterized in that, The computer program product includes a computer program that, when run by the processor of a computer device, executes instructions according to any one of claims 1-6.

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