A radio frequency (RF) matching method, system, device, and storage medium for online calibration

Abstract

This application provides an online calibration method, system, device, and storage medium for radio frequency (RF) matching devices, addressing the problem that existing RF calibration technologies cannot directly measure specific electrical parameters online. The method synchronously acquires the true values ​​of RF electrical parameters (such as voltage, current, phase, and impedance) from NIST-traceable calibration components and the measured values ​​from the internal sensors of the device under test (DUT). It then uses a gradient descent algorithm to iteratively optimize a multi-factor calibration function model (such as a composite function with temperature compensation or aging compensation), dynamically adjusting the function parameters until the error between the true and measured values ​​converges within a threshold. The optimized function model is then embedded into the DUT in real time, reconstructing the mapping relationship between its internal sensor signals and output RF parameters, forming a closed-loop calibration process.

Description

Technical Field

[0001] This application relates to the field of radio frequency technology, and more specifically, to an online calibration method, system, device, and storage medium for radio frequency matching devices. Background Technology

[0002] Radio frequency (RF) calibration is a core component in ensuring the performance of wireless communication equipment, directly impacting signal transmission quality, device compatibility, and system reliability. In high-frequency communication scenarios such as 5G / 6G and the Internet of Things (IoT), the accuracy of RF electrical parameters (voltage, current, phase, impedance, etc.) directly determines whether the equipment can meet stringent industry standards (such as 3GPP and FCC). However, existing calibration technologies suffer from inherent limitations and implementation bottlenecks, making it difficult to simultaneously achieve real-time performance and accuracy in online calibration.

[0003] Existing online RF calibration technologies mainly employ indirect measurement methods, such as calculating the actual transmission power of non-50-ohm devices under test based on the conjugate matching principle. However, this method cannot directly measure and calibrate specific RF electrical parameters (such as voltage, current, phase, and impedance) of the device under test online, leading to system error accumulation. Summary of the Invention

[0004] The purpose of this application is to provide an online calibration method, system, device, and storage medium for radio frequency matching devices, so as to solve the above-mentioned problems existing in the prior art and realize direct online measurement and calibration.

[0005] Firstly, an online calibration method for a radio frequency matching device is provided, the method including:

[0006] The true values ​​of the RF electrical parameters of the RF matching unit under test are measured under operating conditions using a calibration kit.

[0007] Simultaneously acquire the true values ​​of the RF electrical parameters measured by the calibrator and the measured values ​​of the RF electrical parameters of the RF matching device under test based on the internal sensor, with the same sampling interval;

[0008] The true value and the measured value are used as the dependent variable and the variable, respectively. A preliminary calibration function model reflecting the mapping relationship between the true value and the measured value is fitted according to the preset calibration function model type until the fitting process reaches the set conditions.

[0009] The RF matching unit adjusts the mapping relationship between the acquired signals of the internal sensors and the corresponding output RF electrical parameters based on the preliminary calibration function model.

[0010] Again, using the same sampling interval, the true values ​​of the RF electrical parameters measured by the calibrator and the measured values ​​of the RF electrical parameters of the RF matching device under test based on the internal sensor are obtained simultaneously to verify whether the difference is less than the set threshold.

[0011] If the value is less than the set threshold, the RF matching unit calibration is completed; if the value is greater than the set threshold, the calibration function model is further fitted and the RF matching unit is calibrated based on the resampled data.

[0012] Furthermore, the fitting method for the function model includes:

[0013] Define the loss function and calculate the output value F(V) of the functional model. t ;θ) and the truth value V r The error between them

[0014]

[0015] Where F represents the calibration function model, V t Let θ be the set of measured values, θ represent the adjustable parameters in the calibration function model, and Vr be the set of true values. ti V represents the i-th truth value. ri Let N be the i-th measurement value, and N be the total number of samples.

[0016] Assign an initial value to θ, iterate θ using the gradient descent algorithm, and stop iterating when the set conditions are met, and obtain the current value of θ.

[0017] Furthermore, the gradient descent algorithm includes:

[0018] The gradient descent algorithm includes:

[0019] For the current parameter θ k Calculate the gradient of the loss function.

[0020]

[0021] Where θ=[θ1,θ2,…,θ m ] T , where each θ j (j = 1, 2, ..., m) is an independent optimizable parameter of the calibration function model, m is the total number of independent optimizable parameters, and k represents the number of iterations. Represents partial derivatives,

[0022] The parameters are updated along the negative gradient direction using a learning rate η, where η controls the step size.

[0023]

[0024] The number of iterations k starts from 0 and continues until convergence.

[0025] Furthermore, the calibration function model type includes one or more of the following: a first-order polynomial for fitting linear shift, a polynomial with a temperature term for fitting temperature drift, or a logarithmic function with a time factor for fitting aging decay.

[0026] Furthermore, the first-order polynomial is:

[0027] V ti =θ1·V ri +θ2,

[0028] The logarithmic function is:

[0029] V ti =θ6ln(θ7t+θ8)+θ9V ri ,

[0030] The polynomial containing the temperature term is:

[0031]

[0032] Where T represents the current ambient temperature and t represents the total operating time of the equipment.

[0033] Furthermore, the radio frequency electrical parameters include at least one of voltage, current, phase, power, noise, or impedance.

[0034] Furthermore, the calibration component is a NIST traceable radio frequency matching device calibration component.

[0035] Secondly, an online calibration system for radio frequency matching devices is provided, including:

[0036] Calibration kits are used to test RF matched units and provide NIST-traceable RF electrical parameter reference values.

[0037] The data acquisition and processing system is configured to perform the method described in the first aspect.

[0038] Thirdly, an electronic device is provided, which includes a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus;

[0039] Memory, used to store computer programs;

[0040] When a processor executes a program stored in memory, it implements the steps of the method described in the first aspect above.

[0041] Fourthly, a computer-readable storage medium is provided, wherein a computer program is stored therein, and when executed by a processor, the computer program implements the steps of the method described in the first aspect above.

[0042] Beneficial Effects: The RF matching device calibration method of this application achieves dynamic closed-loop calibration of the device under test (DUT) by directly measuring the RF electrical parameters (voltage, current, phase, impedance, etc.) of the DUT and NIST traceable calibration components, combined with an optimized fitting function generated by a self-learning module. Direct measurement and truth-based traceability replace traditional indirect calculation methods, eliminating systematic errors. The function parameters are trained in real-time using a gradient descent optimization algorithm and embedded into the DUT firmware, forming a "measurement-training-programming-verification" closed loop, shortening calibration time. The calibration function model dynamically integrates environmental variables such as temperature and aging, adaptively compensating for distortion in high-frequency and plasma etching scenarios. Attached Figure Description

[0043] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments of this application will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0044] Figure 1 An online calibration method for an RF matching device is provided in this application embodiment;

[0045] Figure 2 A block diagram of an online calibration system for an RF matching device is provided in this application embodiment;

[0046] Figure 3 A flowchart illustrating the calibration function model fitting process provided in this application embodiment. Detailed Implementation

[0047] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of the embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application. Unless otherwise defined, the technical or scientific terms used in this application should have the ordinary meaning understood by those skilled in the art. The words "first," "second," and similar terms used in this application do not indicate any order, quantity, or importance, but are only used to distinguish different components. The words "comprising" or "including," etc., mean that the element or object preceding the word covers the element or object listed after the word and its equivalents, but do not exclude other elements or objects. The words "connected," "coupled," or "connected," etc., are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. "Up," "down," "left," "right," etc., are only used to indicate relative positional relationships. When the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0048] The online calibration method for radio frequency matching devices provided in this application embodiment, such as Figure 1 As shown, it includes:

[0049] The true values ​​of the RF electrical parameters of the RF matching device under test are measured using a calibration kit. The calibration kit is a NIST traceable RF matching device calibration kit, covering impedance, power, and noise standards. NIST traceable RF matching device calibration kits include the following types:

[0050]

[0051] The data acquisition module simultaneously acquires the true values ​​V of the RF electrical parameters measured by the calibration piece at the same sampling interval. r and the measured RF electrical parameters V of the RF matching unit under test based on its internal sensors. t Radio frequency electrical parameters include at least one of voltage, current, phase, power, noise, or impedance.

[0052] The truth value V r With the measured value V t Using these as the dependent and variable values ​​respectively, a preliminary calibration function model reflecting the mapping relationship between the true and measured values ​​is fitted according to a preset calibration function model type until the fitting process meets the set conditions. The calibration function type can be selected based on test environment factors and potential measurement biases, including first-order polynomials for fitting linear offsets.

[0053] Vti =θ1·V ri +θ2,

[0054] Fitting a polynomial containing a temperature term to the temperature drift, such as:

[0055] V ti =θ6ln(θ7t+θ8)+θ9V ri ,

[0056] When considering aging, we can combine the logarithmic function of aging decay with a time factor. A typical logarithmic function is:

[0057]

[0058] Where T represents the current ambient temperature, and t represents the total operating time of the device. If computing power allows, the three types can be superimposed. This allows for a more accurate simulation of the calibration function.

[0059] The RF matching unit adjusts the mapping relationship between the acquired signals of its internal sensors and the corresponding output RF electrical parameters based on a preliminary calibration function model. Specifically, the core mechanism by which the RF matching unit adjusts the mapping relationship between internal sensor signals and output RF electrical parameters based on the preliminary calibration function model is to embed a complete mathematical function as an independent module into the signal processing link, directly reconstructing the conversion process from the original signal to a physical quantity. Specifically, the original signals acquired by the sensors (such as voltage, current, and phase) are input to the calibration function module. This function calculates the correction value in real time using a preset mathematical expression (such as a first-order polynomial or a composite function containing temperature / time factors) and outputs the calibrated RF parameters. For example, if the calibration function is an expression with temperature compensation:

[0060] θ3=0.95, θ4=0.2, θ5=-0.02

[0061] When the sensor measures an initial voltage of 1.3V and the ambient temperature T = 85℃, the system automatically calculates and outputs a correction value of 1.24V, significantly suppressing sensor drift errors caused by high temperatures. This embedded approach implements function operations through hardware (such as FPGA logic circuits) or firmware (such as MCU interrupt service routines), achieving dynamic environmental adaptability and improved accuracy.

[0062] When the calibration function model is embedded in the RF matching unit, further verification of the matching degree is required. The true values ​​of the RF electrical parameters measured by the calibration device and the measured values ​​of the RF electrical parameters of the RF matching unit based on its internal sensors are obtained simultaneously at the same sampling interval to verify whether the difference is less than the set threshold.

[0063] When the value is below the set threshold, the RF matching unit calibration is completed; when the value is above the set threshold, the calibration function model is further fitted based on the resampled data, and the RF matching unit is calibrated. This iterative fitting and verification process continues until the value is below the set threshold.

[0064] Fitting methods for calibration function models are as follows Figure 2 As shown, the details are as follows:

[0065] Define the loss function and calculate the output value F(V) of the functional model. t ;θ) and the truth value V r The error between them

[0066]

[0067] Where F represents the calibration function model, V t Let θ be the set of measured values, θ represent the adjustable parameters in the calibration function model, and Vr be the set of true values. ti V represents the i-th truth value. ri Let N be the i-th measurement value, and N be the total number of samples.

[0068] Assign an initial value to θ, iterate θ using the gradient descent algorithm, and stop iterating when the set conditions are met, and obtain the current value of θ.

[0069] Gradient descent algorithms include:

[0070] For the current parameter θ k Calculate the gradient of the loss function.

[0071]

[0072] Where θ=[θ1,θ2,…,θ m ] T , where each θ j (j = 1, 2, ..., m) is an independent optimizable parameter of the calibration function model, m is the total number of independent optimizable parameters, and k represents the number of iterations. This represents the partial derivative. The parameters are updated along the negative gradient direction using the learning rate η, where η controls the step size.

[0073]

[0074] The number of iterations k starts from 0 and continues until convergence.

[0075] The RF matching device calibration method of this application achieves dynamic closed-loop calibration of the device under test by directly measuring the RF electrical parameters (voltage, current, phase, impedance, etc.) of the device under test and the NIST traceable calibration component, combined with the optimized fitting function generated by the self-learning module. Its core beneficial effects include: (1) replacing the traditional indirect calculation method with direct measurement and truth traceability to eliminate system errors. (2) training the function parameters in real time through the gradient descent optimization algorithm and embedding them into the firmware of the device under test to form a "measurement-training-burning-verification" closed loop, shortening the calibration time. (3) dynamically integrating environmental variables such as temperature and aging into the calibration function model to adaptively compensate for distortion in scenarios such as 5G high frequency (28GHz) and plasma etching.

[0076] Based on the same inventive concept, this application also provides an online calibration system for radio frequency matching devices, such as... Figure 2 As shown, it includes:

[0077] Calibration kits are used to test RF matched units and provide NIST-traceable RF electrical parameter reference values.

[0078] The data acquisition and processing system is configured to perform the above-described online calibration method for the radio frequency matching device.

[0079] Based on the same inventive concept, this application also provides an electronic device, which includes a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus;

[0080] Memory, used to store computer programs;

[0081] The processor, when executing the program stored in the memory, implements the above-described online calibration method for the radio frequency matching device.

[0082] The communication bus mentioned above can be a peripheral component interconnection standard bus or an Extended Industry Standard Architecture (EISA) bus, etc. This communication bus can be divided into address bus, data bus, control bus, etc. For ease of illustration, only one thick line is used to represent it in the diagram, but this does not mean that there is only one bus or one type of bus.

[0083] The communication interface is used for communication between the aforementioned electronic devices and other devices.

[0084] The memory may include random access memory (RAM) or non-volatile memory (NVM), such as at least one disk storage device. Optionally, the memory may also be at least one storage device located remotely from the aforementioned processor.

[0085] The processors mentioned above can be general-purpose processors, including central processing units (CPUs), network processors (NPs), etc.; they can also be digital signal processors, application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0086] In another embodiment provided in this application, a computer-readable storage medium is also provided, which stores instructions that, when executed on a computer, cause the computer to perform any of the above-described radio frequency matching online calibration methods.

[0087] Those skilled in the art will understand that the embodiments in this application can be provided as methods, systems, or computer program products. Therefore, the embodiments in this application can take the form of entirely hardware embodiments, entirely software embodiments, or embodiments combining software and hardware aspects. Furthermore, the embodiments in 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.

[0088] This application describes embodiments of methods, apparatus (systems), and computer program products according to embodiments of this application with reference to flowchart illustrations and / or block diagrams. 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. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0089] 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 1The function specified in one or more boxes.

[0090] 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.

[0091] Although preferred embodiments have been described in this application, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of the embodiments of this application.

[0092] Obviously, those skilled in the art can make various modifications and variations to the embodiments of this application without departing from the spirit and scope of the embodiments of this application. Therefore, if these modifications and variations to the embodiments of this application fall within the scope of the claims in this application and their equivalents, then this application also intends to include these modifications and variations.

Claims

1. An online calibration method for an RF matching device, characterized in that, include: The true values ​​of the RF electrical parameters of the RF matching unit under test are measured under operating conditions using a calibration kit. Simultaneously acquire the true values ​​of the RF electrical parameters measured by the calibrator and the measured values ​​of the RF electrical parameters of the RF matching device under test based on the internal sensor, with the same sampling interval; The true value and the measured value are used as the dependent variable and the variable, respectively. A preliminary calibration function model reflecting the mapping relationship between the true value and the measured value is fitted according to the preset calibration function model type until the fitting process reaches the set conditions. The RF matching unit adjusts the mapping relationship between the acquired signals of the internal sensors and the corresponding output RF electrical parameters based on the preliminary calibration function model. Again, using the same sampling interval, the true values ​​of the RF electrical parameters measured by the calibrator and the measured values ​​of the RF electrical parameters of the RF matching device under test based on the internal sensor are obtained simultaneously to verify whether the difference is less than the set threshold. When the value is less than the set threshold, the RF matching circuit calibration is complete. If the value exceeds the set threshold, the calibration function model is further fitted and the RF matching circuit is calibrated based on the resampled data. The fitting method for the function model includes: Define the loss function and calculate the output value F(V) of the functional model. t ;θ) and the truth value V r The error between them ， Where F represents the calibration function model, V t Let θ be the set of measured values, θ represent the adjustable parameters in the calibration function model, and Vr be the set of true values. ti V represents the i-th truth value. ri Let N be the i-th measurement value, and N be the total number of samples. Assign an initial value to θ, iterate θ using the gradient descent algorithm, and stop iterating when the set conditions are met, and obtain the current value of θ. The calibration kit is a NIST traceable radio frequency matching kit.

2. The online calibration method for the radio frequency matching device according to claim 1, characterized in that: The gradient descent algorithm includes: For the current parameter θ k Calculate the gradient of the loss function. ， Where θ=[θ1,θ2,…,θ m ] T , where each θ j (j=1,2,…,m) is an independent optimizable parameter of the calibration function model, m is the total number of independent optimizable parameters, and k represents the number of iterations. Represents partial derivatives, The parameters are updated along the negative gradient direction using a learning rate η, where η controls the step size. ， The number of iterations k starts from 0 and continues until convergence.

3. The online calibration method for the radio frequency matching device according to claim 2, characterized in that: The calibration function model type includes one or more of the following: a first-order polynomial for fitting linear shift, a polynomial with a temperature term for fitting temperature drift, or a logarithmic function with a time factor for fitting aging decay.

4. The online calibration method for the radio frequency matching device according to claim 3, characterized in that: The first-order polynomial is: , The logarithmic function is: ， The polynomial containing the temperature term is: ， Where T represents the current ambient temperature and t represents the total operating time of the equipment.

5. The online calibration method for an RF matching device according to claim 1, characterized in that: The radio frequency electrical parameters include at least one of voltage, current, phase, power, noise, or impedance.

6. An online calibration system for radio frequency matching devices, characterized in that, include: Calibration kits are used to test RF matched units and provide NIST-traceable RF electrical parameter reference values. A data acquisition and processing system is configured to perform the method as described in any one of claims 1-5.

7. An electronic device, characterized in that, The electronic device includes a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus; Memory, used to store computer programs; A processor, when executing a program stored in memory, implements the method of any one of claims 1-5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the method described in any one of claims 1-5.

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