A method and device for extracting scattering parameters of an ultra-small-size coaxial calibration piece

Abstract

The application relates to an extraction method and device for scattering parameters of ultra-small-size coaxial calibration pieces. The method comprises the following steps: obtaining a plurality of large-size air transmission line standard pieces and a plurality of sets of ultra-small-size coaxial calibration pieces; each set of coaxial calibration pieces comprises a plurality of offset short circuits, open circuits, loads and straight-throughs; the key geometric parameters of each offset short circuit and open circuit are measured, including the outer diameter of the inner conductor, the inner diameter / circularity of the outer conductor and the air line length; based on the measured scattering parameters of each air transmission line standard piece, the uncertain parameters required for electromagnetic simulation are determined; based on the uncertain parameters and the key geometric parameters, the theoretical reflection coefficients of each offset short circuit and open circuit at each set frequency point are simulated, and the single-port error coefficient of the vector network analyzer is calculated based on the theoretical reflection coefficients and the measured reflection coefficients; based on the single-port error coefficient, the theoretical reflection coefficient of the load and the theoretical scattering parameter matrix of the straight-through are determined; the uncertainty of each theoretical parameter at each set frequency point is determined, and is packaged into a file in a set format. The application can improve the extraction precision of the scattering parameters of the ultra-small-size coaxial calibration pieces.

Description

Technical Field

[0001] This invention relates to the field of precision calibration technology for vector network analyzers, and in particular to a method and apparatus for extracting scattering parameters of an ultra-small coaxial calibration component. Background Technology

[0002] In the field of precision calibration technology for vector network analyzers (VNAs), the accuracy of the scattering parameters of the calibration components directly determines the accuracy and traceability of VNA measurement results. With the rapid penetration of millimeter-wave and terahertz technologies into fields such as 6G communications, spaceborne remote sensing, millimeter-wave radar, and high-end chip testing, coaxial calibration components with interface sizes of 1.0 mm (110 GHz), 0.8 mm (145 GHz), and 0.5 mm (250 GHz) have become indispensable metrological standards in these frequency bands. Therefore, accurately extracting the scattering parameters of these ultra-small coaxial calibration components (bias short circuit, bias open circuit, load, and through) is not only a prerequisite for achieving high-precision VNA calibration but also a core link in constructing a complete millimeter-wave metrological traceability chain.

[0003] Currently, existing technologies mainly employ three methods to extract scattering parameters from coaxial standard parts: the first is a parameter assignment method based on the nominal values ​​of mechanical design; the second is a parameter extraction method based on electromagnetic simulation; and the third is a method suitable for direct measurement and extraction via the multi-line through-reflection-transmission line (MTRL) method. However, in the first method, geometric quantities such as air line length rely solely on the nominal dimensions of the machining drawings and CMM (Coordinate Measuring Machine) sampling (typical metrological-grade joint tolerance ±2.5µm). For a 1.0mm coaxial part, a 2.5µm length error introduces a theoretical phase error of approximately ±0.33° at 110GHz. In practice, due to factors such as batch-to-batch tool wear, assembly stress, and temperature variations, individual deviations may exceed ±10µm, and phase errors can reach over ±1.3°. More importantly, the CMM measures the contact mechanical profile, while the electromagnetic effective length required for calibration is affected by edge field effects, resulting in a systematic offset from the mechanical length. This offset is not calibrated, therefore, the extraction results are inaccurate. The second method, while employing simulation, still relies on drawings or averages for its input geometry, failing to perform individualized measurements for each calibration component. Therefore, it cannot eliminate errors introduced by individual differences. The third approach, while avoiding reliance on simulation or nominal values ​​and directly obtaining the scattering parameters of the calibration component through measurement, requires the fabrication of a set of transmission line standards with precisely known length differences and good transmission characteristics. Therefore, this approach is only suitable for coaxial connector calibration components of 1.85mm and larger dimensions (such as 2.92mm, 2.4mm, and N-type). It is evident that existing methods cannot accurately extract the scattering parameters of ultra-small coaxial calibration components (such as 1.0mm, 0.8mm, and 0.5mm). Summary of the Invention

[0004] This invention provides a method and apparatus for extracting scattering parameters of an ultra-small coaxial calibration component, which can improve the extraction accuracy of scattering parameters of an ultra-small coaxial calibration component.

[0005] In a first aspect, embodiments of the present invention provide a method for extracting scattering parameters of an ultra-small coaxial calibration component, comprising: Obtain multiple standard air transmission line components suitable for large-size coaxial connectors and multiple sets of ultra-small coaxial calibration components to be calibrated, all manufactured based on the same manufacturing standard. The interface size of each standard air transmission line component is not less than 1.85 mm, and the interface size of each set of coaxial calibration components is not more than 1.0 mm. Each set of coaxial calibration components includes multiple bias short circuits, open circuits, load circuits, and through circuits. The key geometric parameters for each bias short circuit and open circuit are measured using laser technology; these key geometric parameters include the outer diameter of the inner conductor, the inner diameter / roundness of the outer conductor, and the length of the air wire. Based on the measured scattering parameters of each of the aforementioned air transmission line standard components, the uncertain parameters required for electromagnetic simulation are determined. The uncertain parameters include at least the gold plating thickness of the inner / outer conductor, the equivalent conductivity, the surface roughness coefficient, and the convergence criterion for adaptive mesh generation. Based on the aforementioned uncertain parameters and the key geometric parameters of each bias short circuit and open circuit, the theoretical reflection coefficients of each bias short circuit and open circuit at each set frequency point are obtained through simulation. The single-port error coefficient of the vector network analyzer is calculated based on the theoretical and measured reflection coefficients for each bias short circuit and open circuit. Based on the single-port error coefficient, the measured reflection coefficient of the load is de-embedded to obtain the theoretical reflection coefficient of the load; Based on the error coefficient of each port, the theoretical scattering parameter matrix of the through is calculated; The uncertainties of each theoretical reflection coefficient and theoretical scattering parameter matrix at each set frequency point are determined based on Monte Carlo methods. The theoretical reflection coefficient, theoretical scattering parameter matrix and corresponding uncertainties are then packaged into a file with a set format for use by the vector network analyzer.

[0006] Secondly, embodiments of the present invention also provide a device for extracting scattering parameters of an ultra-small coaxial calibration component, comprising: The acquisition unit is used to acquire multiple air transmission line standard parts suitable for large-size coaxial connectors and multiple sets of ultra-small-size coaxial calibration parts to be calibrated, all manufactured based on the same manufacturing standard. The interface size of each air transmission line standard part is not less than 1.85mm, and the interface size of each set of coaxial calibration parts is not more than 1.0mm. Each set of coaxial calibration parts includes multiple bias short circuits, open circuits, load circuits, and through circuits. A measurement unit is used to measure the key geometric parameters of each bias short circuit and open circuit based on laser; the key geometric parameters include the outer diameter of the inner conductor, the inner diameter / roundness of the outer conductor, and the length of the air wire. The first determining unit is used to determine the uncertain parameters required for electromagnetic simulation based on the measured scattering parameters of each of the air transmission line standard components. The uncertain parameters include at least the gold plating thickness of the inner / outer conductor, the equivalent conductivity, the surface roughness coefficient, and the convergence criterion of the adaptive mesh generation. The simulation unit is used to simulate the theoretical reflection coefficient of each bias short circuit and open circuit at each set frequency point based on the uncertain parameters and the key geometric parameters of each bias short circuit and open circuit. The first calculation unit is used to calculate the single-port error coefficient of the vector network analyzer based on the theoretical and measured reflection coefficients for each bias short circuit and open circuit. The second determining unit is used to perform de-embedding processing on the measured reflection coefficient of the load based on the single-port error coefficient, and obtain the theoretical reflection coefficient of the load. The second calculation unit is used to calculate the theoretical scattering parameter matrix of the through-pass based on the error coefficient of each port; The encapsulation unit is used to determine the uncertainty of each theoretical reflection coefficient and theoretical scattering parameter matrix at each set frequency point based on Monte Carlo, and encapsulate each theoretical reflection coefficient, theoretical scattering parameter matrix and corresponding uncertainty into a file of a set format for use by the vector network analyzer.

[0007] Thirdly, embodiments of the present invention also provide an electronic device, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, it implements the method described in any embodiment of this specification.

[0008] Fourthly, embodiments of the present invention also provide a computer-readable storage medium having a computer program stored thereon, which, when executed in a computer, causes the computer to perform the methods described in any embodiment of this specification.

[0009] Fifthly, embodiments of the present invention also provide a computer program product, including a computer program that, when executed by a processor, implements the steps of the method described above.

[0010] This invention provides a method and apparatus for extracting scattering parameters of ultra-small coaxial calibration components. For the first time, a non-contact laser measurement method is introduced to the individualized measurement of the airline length of coaxial calibration components. By tracing the wavelength of the frequency-stabilized laser back to the SI unit "meter," it differs from existing technologies that rely on nominal design values ​​or batch sampling mechanical tolerances, fundamentally eliminating systematic deviations in length parameters. Using the measured scattering parameters of a large-size airline standard component as a golden reference value, uncertain parameters such as plating thickness, conductivity, roughness, and dielectric constant, which cannot be directly obtained in electromagnetic simulations, are calibrated in reverse. Then, these uncertain parameters are directly extrapolated to ultra-small coaxial components. During simulation calculations, only the individualized key geometric parameters measured by laser need to be replaced, thus ensuring that the simulation accuracy of ultra-small calibration components has traceable experimental evidence, breaking through the credibility bottleneck of traditional simulations that lack physical verification. By using a single-port error coefficient to determine the theoretical reflection coefficient of the load, the true value of the load scattering parameters is obtained instead of the nominal value. Finally, the uncertainties of the extraction results for each standard component are calculated using Monte Carlo simulation and then packaged for easy access by a vector network analyzer. Therefore, this application can improve the extraction accuracy of scattering parameters for ultra-small coaxial calibration components. Attached Figure Description

[0011] To more clearly illustrate the technical solutions in the embodiments of the present invention 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 some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0012] Figure 1 This is a schematic diagram of the structure of a method for extracting scattering parameters of an ultra-small coaxial calibration component according to an embodiment of the present invention; Figure 2 This is a schematic diagram showing the reflection coefficient obtained by simulating a 2.1mm long 1.0mm bias short circuit according to an embodiment of the present invention; Figure 3 This is an embodiment of the present invention that provides S obtained by simulating a 2.1mm long 1.0mm air line. 11 (Reflection coefficient of port 1) Result diagram; Figure 4 This is an embodiment of the present invention that provides S obtained by simulating a 2.1mm long 1.0mm air line. 12 (Reflection coefficient of port 2) Result Diagram; Figure 5 This is an embodiment of the present invention that provides S obtained by simulating a 2.1mm long 1.0mm air line. 21(Forward transmission coefficient) Result Diagram; Figure 6 This is an embodiment of the present invention that provides S obtained by simulating a 2.1mm long 1.0mm air line. 22 (Reverse transmission coefficient) Result Diagram; Figure 7 This is a schematic diagram of the signal flow of a single-port error model provided in an embodiment of the present invention; Figure 8 This is a hardware architecture diagram of an electronic device provided in an embodiment of the present invention; Figure 9 This is a structural diagram of a device for extracting scattering parameters of an ultra-small coaxial calibration component according to an embodiment of the present invention. Detailed Implementation

[0013] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are some embodiments of the present invention, but not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0014] As mentioned earlier, existing technologies mainly employ three methods to extract scattering parameters from coaxial standard parts: the first is a parameter assignment method based on the nominal values ​​of mechanical design; the second is a parameter extraction method based on electromagnetic simulation; and the third is a method suitable for direct measurement and extraction via the multi-line through-reflection transmission line (MTRL) method. In the first method, the manufacturer performs ultra-precision machining according to the mechanical dimensions (such as inner conductor diameter, outer conductor diameter, air line length, and dielectric support position) specified in IEEE Std 287-2021, "Precision Coaxial Connector Standard". After machining, a small number of samples are randomly inspected for dimensions using a coordinate measuring machine (CMM). If the dimensions are within tolerance, the parameters of all calibration parts of that model are set to the theoretical nominal values. However, for ultra-small coaxial calibration parts, in the millimeter-wave bands such as 1.0 mm and 0.5 mm, the wavelengths are extremely short. Even micron-level differences in machining and inner conductor surface roughness between calibration parts within the same batch can cause significant phase deviations in the reflection coefficient. Using the "average value of the sampling" to represent "each individual" makes it impossible to extract the true individual S-parameters of each calibration piece.

[0015] When using the second method, some high-end calibration component suppliers employ three-dimensional full-wave electromagnetic simulation to extract calibration parameters. The specific steps are as follows: a parametric three-dimensional model of the coaxial connector is created in electromagnetic simulation software (such as ANSYS HFSS or CST Studio Suite), including the outer conductor, inner conductor, dielectric gaskets such as polyetherimide (PEI) or quartz, air gap, and short-circuit piston or open-circuit structure. The geometric dimensions in the model are derived from design drawings or batch sampling averages. The simulation obtains the amplitude and phase response of the reflection coefficient S11 as a function of frequency, which is then converted into time delay or equivalent circuit parameters through polynomial fitting and written into the calibration component definition file. It is evident that existing simulations are based on ideal boundary conditions and perfect material properties (such as a fixed dielectric constant). However, in actual manufacturing, conductor edges have chamfers, dielectric gaskets have assembly stress, and air gaps have eccentric tolerances. These actual physical states cannot be accurately reproduced by the simulation model; therefore, there is a non-negligible model error between the simulation-extracted S-parameters and the actual S-parameters of the real physical calibration component at the port.

[0016] When using the third method, for coaxial connectors of 1.85mm and above (such as 2.4mm, 2.92mm, 3.5mm, N-type, etc.), existing publicly available technologies employ a multi-line Thru-Reflect-Line (MTRL) + Line Reflect Match (LRM) calibration method. The specific process is as follows: at high frequencies, a set of transmission line standards with different electrical lengths are used. High-precision system error coefficients are obtained through MTRL self-calibration. At low frequencies, LRM is used for supplementation. Then, the single-port calibration component to be characterized is measured under this calibration reference plane, thereby directly measuring the scattering parameters (S-parameters) of these calibration components under actual physical conditions. This method can trace the calibration component parameters back to the physical length of the transmission line and does not rely on simulation models; it is called "data-based" calibration component parameter extraction. However, this method is only suitable for large-sized coaxial calibration components.

[0017] To address the shortcomings of the three methods mentioned above, the inventors proposed that the measurement values ​​of large-size coaxial calibration components can be used as a third method to help with the simulation modeling and scattering parameter extraction of ultra-small-size coaxial calibration components.

[0018] Please refer to Figure 1 This invention provides a method for extracting scattering parameters of an ultra-small coaxial calibration component, the method comprising: Step 100: Obtain multiple air transmission line standard parts suitable for large-size coaxial connectors and multiple sets of ultra-small-size coaxial calibration parts to be calibrated, all manufactured based on the same manufacturing standard. The interface size of each air transmission line standard part is not less than 1.85mm, and the interface size of each set of coaxial calibration parts is not more than 1.0mm. Each set of coaxial calibration parts includes multiple bias short circuits, open circuits, load circuits, and through circuits. Step 102: Measure the key geometric parameters for each bias short circuit and open circuit using laser measurement; the key geometric parameters include the outer diameter of the inner conductor, the inner diameter / roundness of the outer conductor, and the length of the air line. Step 104: Based on the measured scattering parameters of each air transmission line standard, determine the uncertain parameters required for electromagnetic simulation. The uncertain parameters include at least the gold plating thickness of the inner / outer conductor, the equivalent conductivity, the surface roughness coefficient, and the convergence criterion for adaptive mesh generation. Step 106: Based on the uncertain parameters and the key geometric parameters of each bias short circuit and open circuit, the theoretical reflection coefficient of each bias short circuit and open circuit at each set frequency point is obtained by simulation. Step 108: Calculate the single-port error coefficient of the vector network analyzer based on the theoretical and measured reflection coefficients for each bias short circuit and open circuit. Step 110: Based on the single-port error coefficient, the measured reflection coefficient of the load is de-embedded to obtain the theoretical reflection coefficient of the load; Step 112: Calculate the theoretical scattering parameter matrix of the through-pass based on the error coefficient of each port; Step 114: Determine the uncertainty of each theoretical reflection coefficient and theoretical scattering parameter matrix at each set frequency point based on Monte Carlo, and encapsulate each theoretical reflection coefficient, theoretical scattering parameter matrix and corresponding uncertainty into a file of a set format for use by the vector network analyzer.

[0019] In this embodiment, a non-contact laser measurement method is introduced for the first time to the individualized measurement of the air line length of a coaxial calibration component. By tracing the wavelength of the frequency-stabilized laser back to the SI unit "meter," it fundamentally eliminates the systematic deviation of the length parameter, unlike existing technologies that rely on nominal design values ​​or batch sampling mechanical tolerances. Using the measured scattering parameters of a large-size air transmission line standard component as a golden reference value, uncertain parameters such as plating thickness, conductivity, roughness, and dielectric constant, which cannot be directly obtained in electromagnetic simulations, are calibrated in reverse. Then, these uncertain parameters are directly extrapolated to ultra-small coaxial components. During simulation calculations, only the individualized key geometric parameters measured by the laser need to be replaced, thus ensuring that the simulation accuracy of ultra-small calibration components has traceable experimental basis, breaking through the credibility bottleneck of traditional simulations that lack physical verification. By using a single-port error coefficient to determine the theoretical reflection coefficient of the load, the true value of the load scattering parameters is obtained instead of the nominal value. Finally, the uncertainty of the extracted results for each standard component is calculated using Monte Carlo methods and encapsulated for easy access by a vector network analyzer. Therefore, this application can improve the extraction accuracy of scattering parameters of ultra-small coaxial calibration components.

[0020] The following description Figure 1 The execution method of each step is shown.

[0021] First, for step 100, obtain multiple standard air transmission line parts for large-size coaxial connectors and multiple sets of ultra-small-size coaxial calibration parts to be calibrated, which are manufactured based on the same manufacturing standard.

[0022] In this step, to ensure the applicability of uncertain parameters in electromagnetic simulation between large-size and ultra-small-size coaxial calibration components, both types of coaxial calibration components should be manufactured using the same standard. Furthermore, the interface dimensions of the large-size coaxial connector are preferably 1.85 mm and 2.92 mm, and the interface dimensions of the ultra-small-size coaxial calibration component are preferably 1.0 mm, 0.8 mm, and 0.5 mm. Of course, users can also use coaxial calibration components of other sizes; this application does not impose specific limitations.

[0023] For step 102, the key geometric parameters for each bias short circuit and open circuit are measured using laser measurement. The specific process is as follows: (1) The outer diameter of the inner conductor of each bias short circuit and open circuit is measured based on the laser diameter measuring instrument method.

[0024] A laser diameter gauge conforming to JJF 1250-2010 "Calibration Specification for Laser Diameter Gauges" (under the jurisdiction of the National Technical Committee on Geometric Engineering Parameter Metrology) is used. The principle is as follows: the inner conductor is placed perpendicular to the laser beam axis. A rotating multifaceted prism causes the laser beam to form a high-speed linear scan on the outer diameter surface of the inner conductor. A photoelectric receiver records the time window of obstruction. The outer diameter of the inner conductor is inferred from the product of the scanning speed and the obstruction time. During measurement, at least five cross-sections are uniformly selected along the air line axis. Each cross-section is rotated around the circumference and measured at least four positions (90° intervals). The arithmetic mean of all measurement points is taken as the equivalent outer diameter of the inner conductor. Before measurement, a traceable standard pin gauge (diameter uncertainty ≤ 0.2µm, k=2) is used for on-site calibration to eliminate system offset. The measurement repeatability of this method is better than ±0.2µm, and the expanded uncertainty U ≤ 1.0µm (k=2).

[0025] (2) The inner diameter and roundness of the outer conductors for each bias short circuit and open circuit are measured based on the laser confocal method.

[0026] For ultra-small coaxial connectors such as 1.0mm / 0.8mm / 0.5mm, a high-precision laser confocal microscope is used to measure the inner diameter and roundness of the outer conductor. The high-precision laser confocal microscope acquires the three-dimensional topographic point cloud data of the inner wall surface of the outer conductor's inner diameter through confocal optics. After reconstruction and fitting, the inner diameter value and roundness error are output simultaneously. Its lateral resolution can reach 0.12μm, its Z-axis resolution can reach 0.01μm, and its XY direction measurement repeatability (3σ) is better than 0.02μm. Referring to relevant research results in the field of laser confocal microscopy, the deviation of the inner diameter measurement results obtained by this method from higher-order reference measurement methods can be controlled within 0.2μm. Before measurement, calibration was performed according to JJF 2160-2024 "Calibration Specification for Laser Confocal Microscope" (issued by the State Administration for Market Regulation, under the jurisdiction of the National Technical Committee on Geometric Length Metrology, and drafted by the National Institute of Metrology of China). Verification was performed using a standard ring gauge calibrated by the National Institute of Metrology of China to ensure the accuracy and reliability of the measurement value. The measurement expanded uncertainty U ≤ 1.0µm (k=2).

[0027] (3) Measure the axial length of the air line based on the laser interferometer method.

[0028] This measurement method is a direct means of achieving SI traceability. A frequency-stabilized He-Ne laser interferometer conforming to JJG 739-2005 "Verification Procedure for Laser Interferometers" or JJF 1913-2021 "Calibration Specification for Laser Interferometer Length Comparator" is used. Its wavelength is traced back to the iodine frequency stabilization standard conforming to JJG 353-2006 "Verification Procedure for 633nm Frequency-Stabilized Lasers," with a frequency uncertainty ≤ 2.5 × 10⁻⁶. -¹¹. The calibration piece under test is fixed on a precision air-bearing slide in a constant temperature (25±1°C) and constant humidity (40~60% RH) environment. The measurement optical path is split into a reference beam and a measurement beam by a beam splitter. The measurement beam is incident perpendicularly to the connector reference end face through a specially designed optical focusing system, and the first interference count is read. Then, the slide is moved or the optical path is switched to focus the measurement beam on the short-circuit end face or open-circuit end face of the air line, and the second interference count is read. The difference between the two counts is converted into the physical length of the air line after correcting the air refractive index according to the Ciddor formula based on the temperature, air pressure and humidity data collected in real time by the environmental sensor. The same air line is measured 10 times, and the arithmetic mean is taken as the final length value of the air line. L Air According to JJF1059.1-2012 "Evaluation and Expression of Measurement Uncertainty", its expanded uncertainty U ≤ 0.6µm (k=2). This length value is directly traced back to the frequency-stabilized laser wavelength, that is, to the SI basic unit of length "meter / m". Table 1 shows the comparison results of geometric dimension measurement methods: Table 1 Comparison of Geometric Dimension Measurement Methods Measurement object Outer diameter of the inner conductor (filament) Outer conductor inner diameter + roundness (micro-hole) Axial length of air line Measurement Dimensions One-dimensional (diameter) 3D (topographic point cloud) One dimension (length) Core accuracy ≤1.0µm ≤1.0µm (inner diameter), roundness acquired simultaneously ≤0.6µm Standard basis JJF 1250-2010 JJF 2160-2024 JJG 739-2005 / JJF 1913-2021 SI Origin Indirect traceability through standard needle gauges Indirect source tracing through standard environmental gauges Directly traced to the frequency-stabilized laser wavelength speed Fast (milliseconds) Slowly (several minutes) Medium (seconds) Core advantages Non-contact, rapid outer diameter measurement The only one that can measure inner diameter and roundness The only direct SI traceability Applicable size filaments larger than 0.2mm Micropores larger than 0.2mm Arbitrary length As shown in Table 1, lasers can achieve non-contact measurements of biased short-circuit and open-circuit air line lengths in the µm range, and establish a direct traceability chain down to the SI length unit, resulting in high measurement accuracy and thus compensating for the inability to perform direct measurements using MTRLs. Furthermore, by using measured geometric dimensions as the sole input, full-wave electromagnetic simulation is driven to obtain individualized calibration standard reflection coefficients, avoiding reliance on nominal values ​​or infeasible transmission line standards.

[0029] For step 104, the measured scattering parameters of the air transmission line standard were obtained directly through MTRL calibration, and the physical length of the air transmission line standard was precisely calibrated using a laser interferometer. A vector network analyzer was used to perform MTRL+LRM self-calibration within the corresponding frequency band to directly extract the measured S-parameters of the air transmission line standard. Since the error coefficients of the MTRL calibration depend only on the difference in physical length of the transmission line and the reciprocity assumption, the results are generally recognized as having metrological-grade accuracy and can serve as an absolute reference for subsequent simulation verification.

[0030] Based on the measured scattering parameters of each air transmission line standard component, the uncertain parameters required for electromagnetic simulation are determined, including: Full-wave electromagnetic simulation models were constructed for each standard air transmission line component, and initial values ​​were set for each uncertain parameter in the model. The uncertain parameters are as follows: (1) The initial value of the gold plating thickness of the inner / outer conductor is set to 1µm for the inner conductor and 1µm for the outer conductor; (2) The equivalent conductivity σ of the inner / outer conductor is initially set to 4.1 × 10⁻⁶.7 S / m, beryllium copper is 2.8×10 7 S / m, the actual coating conductivity may deviate from the theoretical value due to process deviations, and needs to be used as one of the soft parameters for reverse calibration; (3) Surface roughness coefficient R q The initial range is set to 0.1~0.4µm based on the processing technology; (4) The relative permittivity ε of the dielectric support gasket r and the loss tangent tanδ; (5) The convergence criterion for adaptive mesh generation is initially set to S-parameter change < 0.1%.

[0031] The uncertain parameters are used as optimization variables, and the transmission coefficient in the measured scattering parameters of each air transmission line standard is used as the objective function. Parameter scanning and iterative optimization are performed on each air transmission line standard across the entire frequency band until the phase deviation between the simulated transmission coefficient output by the full-wave electromagnetic simulation model and the measured transmission coefficient is no greater than a phase deviation threshold and the amplitude deviation is no greater than an amplitude deviation threshold across the entire frequency band, thus obtaining the final uncertain parameters. The phase deviation threshold is ±0.2°, and the amplitude deviation threshold is ±0.01dB. Of course, users can set the thresholds themselves as needed; this application is not limited to the above.

[0032] For step 106, based on the uncertain parameters and the key geometric parameters of each bias short circuit and open circuit, the theoretical reflection coefficients of each bias short circuit and open circuit at each set frequency point are simulated, including: For each bias short-circuit calibrator and open-circuit calibrator, perform the following operations: Construct an electromagnetic simulation model of the calibration component; The key geometric parameters and uncertain parameters of the calibration component are used as simulation parameters for the electromagnetic simulation model, and the simulation frequency sweep range is set to a continuous frequency band from 0 Hz to the upper limit of the calibration component's use. The calibration component was simulated and calculated under simulation parameters and simulation frequency bands to obtain the theoretical reflection coefficient of the calibration component at each set frequency point.

[0033] This step leverages the ability to fabricate MTRL standard parts in large sizes (e.g., 2.92mm and 1.85mm) and uses measured MTRL scattering parameters as a golden reference value to reverse-calibrate "soft parameters" in the electromagnetic simulation software model, such as conductivity, roughness, and dielectric constant, which are not directly observable. This physically verified simulation protocol directly extrapolates to smaller sizes (e.g., 1.0mm, 0.8mm, and 0.5mm) where MTRL cannot be implemented, replacing only the individualized geometric dimensions measured by laser. This ensures that the simulation accuracy of small-sized calibration parts has traceable experimental evidence, overcoming the credibility bottleneck of traditional simulations lacking physical verification. Unlike conventional simulations that use design drawings or batch-average geometry, this step uses the individualized diameter and length data of each calibration part obtained from laser measurement as a forced input to the electromagnetic simulation model, creating a one-to-one correspondence after calibration. This ensures a precise correspondence between the simulated object and the physical state of the actual object, eliminating geometric deviations between the model and the physical object, resulting in a high accuracy of the theoretical reflection coefficient obtained from the simulation.

[0034] Furthermore, since the electromagnetic simulation is based on the principles of Maxwell's equations, and Maxwell's equations satisfy the geometric scaling law (i.e., when all geometric dimensions are scaled synchronously with the frequency at the same ratio, the scattering parameters remain unchanged), and the simulation mesh is automatically adapted to wavelength changes, this recursive method ensures that the phase accuracy of the simulated scattering parameters of small-sized calibration components and the measured recursive uncertainty remain within the same confidence interval (typical value <0.5°@110GHz, k=2).

[0035] like Figures 2-6 The figures show the simulation results of scattering parameters for a 2.1 mm long 1.0 mm bias short circuit and a 2.1 mm long 1.0 mm air line using the method of this application. As can be seen from the figures, the simulation structure has high accuracy.

[0036] For step 108, the single-port error coefficient includes a directivity term, a reflection tracking term, and a source matching term; based on the theoretical and measured reflection coefficients for each bias short-circuit and open-circuit, the single-port error coefficient of the vector network analyzer is calculated, including: (1) Based on the signal flow graph of the single-port error model, determine each network error term from the instrument port to the test end face of the vector network analyzer.

[0037] like Figure 7 The diagram shown is the signal flow graph of a single-port error model. In the diagram, a M and b M These represent the incident wave and the reflected wave, respectively. E 00 ~ E 11e represents the network error term from the instrument port to the test surface of the vector network analyzer. -γl The transmission coefficient of the air line is represented by e, the natural constant, and γ is the transmission constant of the air line obtained from simulation. l This represents the physical length of the air wire, where O represents an open circuit and S represents a short circuit. L Represents load.

[0038] (2) Based on the signal flow graph and Mason's gain formula, the theoretical reflection coefficient and measured reflection coefficient for each bias short circuit and open circuit, as well as the matrix relationship between each network error term, are determined as follows: In the above matrix relation, let: This constitutes an overdetermined system of equations. Ax = b。

[0039] In the formula, , These represent the theoretical and measured reflection coefficients for an open circuit, respectively. , They represent the first n Theoretical and measured reflection coefficients for a bias short circuit; n ≥3.

[0040] (3) Solve the matrix relation based on the singular value decomposition method to obtain the error value of each network error term, that is, solve for the error value of each network error term. E 00 ~ E 11 .

[0041] (4) Determine the value of the single-port error coefficient based on the relationship between each network error term and the single-port error coefficient.

[0042] In this step, the single-port error coefficients include: the directionality term EDF, the reflection tracking term ERF, and the source matching term ESF. The relationship between the three error coefficients and the error network term is shown in the following equation: Based on the above method, the error coefficient for each port can be obtained.

[0043] This step employs a robust solution using redundant standard components and singular value decomposition (SVD). For example, at 110GHz, at least four short circuits with different offset lengths and at least one open circuit with different offset lengths are used to construct an overdetermined equation system, totaling at least five redundant standard components. At 250GHz, at least six short circuits with different offset lengths and at least one open circuit with different offset lengths are used to construct an overdetermined equation system, totaling at least seven redundant standard components. By truncating small singular values ​​through SVD, the influence of measurement noise and outliers of individual standard components on the error coefficient solution is significantly suppressed, overcoming the excessive reliance on the perfection of standard components in traditional three-standard-component deterministic calibration.

[0044] For step 110, based on the single-port error coefficient, the measured reflection coefficient of the load is de-embedded to obtain the theoretical reflection coefficient of the load.

[0045] In this step, the electrical performance of the load is determined by its internal precision resistive network. Its reflection coefficient is dominated by the impedance characteristics of the resistive elements and is independent of the airline geometry. That is, the theoretical reflection coefficient of the load does not depend on geometric measurements of the load. Therefore, no geometric measurements of the load are required here; only electrical parameters need to be measured. After the single-port error calibration is completed by the vector network analyzer, this step only requires measuring the load's scattering parameters and the reflection coefficient using the vector network analyzer. Then, by substituting these measurements into the matrix relation, the theoretical reflection coefficient of the load can be solved.

[0046] This step differs from traditional methods that directly assume an ideal 50Ω load match. Instead, it employs a de-embedding logic that first solves for system errors and then measures the true load value: First, it uses geometric tracing and simulation to precisely known short-circuit / open-circuit standard components to solve for the single-port error coefficient. Then, it uses this error model to de-embedding the measured load value and deduce the true reflection coefficient of the load. This achieves the acquisition of the true value of the load S-parameters instead of the nominal value, avoiding the uncertainty of load parameters depending on the design nominal value in traditional methods.

[0047] For step 112, the through path satisfies the reciprocity condition; based on the error coefficients of each port, the theoretical scattering parameter matrix of the through path is calculated, including: A straight-through connection was used to link the two ports, and the measurement scattering parameter matrix S of the straight-through network was measured using a vector network analyzer. M ; Based on the single-port error terms and measured scattering parameter matrix of the two ports, the theoretical scattering parameter matrix of the through network is derived by using the SOLR multi-port calibration method.

[0048] In this step, the through-pass satisfies the reciprocity condition (i.e., the transmission coefficient from port 1 to port 2 is equal to the transmission coefficient from port 2 to port 1) and the ports are well matched (return loss ≥ 20dB). Using the SOLR multiport calibration method to deduce the theoretical scattering parameter matrix of the through-pass network is a common technique in this field and will not be elaborated here. This step combines the actual reflection coefficients of short circuits, open circuits, and loads, and then performs multiport calibration using the SOLR method. It only requires unknown through-passes that satisfy the reciprocity condition, eliminating the need for precise zero-length or precisely known electrical length through-pass standards. Commercial metrology-grade coaxial adapters can be used back-to-back, significantly reducing the manufacturing cost and engineering difficulty of calibration kits. Furthermore, for multiports, a similar approach to dual-port systems can be used for arbitrary port expansion. The advantage of this method is that the through-pass does not require a known electrical length or a precise 50Ω impedance, greatly reducing the dependence on ultra-precise zero-length through-passes.

[0049] Finally, for step 114, the uncertainties of the theoretical reflection coefficient and theoretical scattering parameter matrix at each set frequency point are determined in the following manner: (1) The axial length of the air line and the inner diameter of the conductor for each bias short circuit and open circuit are determined. D In and the outer diameter of the inner conductor D Out And the uncertain parameters in the electromagnetic simulation are set as probability distributions, specifically: axial length of the air line L Air Assuming a normal distribution, the mean length is taken as the measured value obtained from laser measurement, and the standard deviation is σ( L Air ); inner diameter of the outer conductor D In and the outer diameter of the inner conductor D Out Assuming a normal distribution, the mean is taken as the measured value obtained from laser measurement, and the standard deviations are σ( D In ) and σ ( D Out ).

[0050] Set the uncertain parameters (conductivity, dielectric constant, etc.) of the electromagnetic simulation to a normal or uniform distribution, based on the range given in the material certificate.

[0051] (2) After setting the probability distribution of each input parameter, Latin Hypercube Sampling (LHS) is used to generate multiple sets (e.g., M=10000) of input parameter vectors. For each set of input parameters, the theoretical reflection coefficients of the corresponding calibration components (biased short circuit and open circuit) at different frequency points are calculated using a trained electromagnetic simulation model (the predicted phase error of the electromagnetic simulation model is <0.1°). The calculated theoretical reflection coefficients are substituted into the matrix relation to obtain the single-port error coefficients. The theoretical reflection coefficients of the load are determined based on the single-port error coefficients. The theoretical scattering parameter matrix of the through circuit is calculated based on the error coefficients of each port.

[0052] (3) Calculate the mean, standard deviation and 95% coverage interval of each error coefficient, theoretical reflection coefficient and theoretical scattering parameter matrix in each result (e.g., 10,000 times), and output the expanded uncertainty (k=2) of the calibration coefficient (i.e. the theoretical reflection coefficient of each bias short circuit and open circuit, the theoretical reflection coefficient of the load and the theoretical scattering parameter matrix of the through circuit) at each frequency point.

[0053] Finally, the numbers of each calibration component, the theoretical reflection coefficients and uncertainties of each bias short circuit and open circuit at each frequency point, the theoretical reflection coefficients and uncertainties of the load, and the theoretical scattering parameter matrix and uncertainties of the through circuit are all packaged into a file with a set format for use by the vector network analyzer.

[0054] It should be noted that when using a vector network analyzer to test actual targets, if the test frequency is inconsistent with the frequency point in the package file, ring interpolation or vector fitting interpolation method is used for data interpolation and scaling, and the interpolated data is used to calibrate the measurement results.

[0055] like Figure 8 , Figure 9 As shown, this embodiment of the invention provides a device for extracting scattering parameters of an ultra-small coaxial calibration component. The device embodiment can be implemented through software, hardware, or a combination of both. From a hardware perspective, as... Figure 8 The diagram shown is a hardware architecture diagram of an electronic device for extracting scattering parameters of an ultra-small coaxial calibration component, as provided in an embodiment of the present invention. (Except for...) Figure 8 In addition to the processor, memory, network interface, and non-volatile memory shown, the electronic device in the embodiment may also include other hardware, such as a forwarding chip responsible for processing packets. Taking software implementation as an example, such as... Figure 9 As shown, a device in a logical sense is formed by the CPU of the electronic device in which it is located reading the corresponding computer program from the non-volatile memory into the memory for execution.

[0056] This embodiment provides a device for extracting scattering parameters of an ultra-small coaxial calibration component, comprising: The acquisition unit 900 is used to acquire multiple air transmission line standard parts suitable for large-size coaxial connectors and multiple sets of ultra-small-size coaxial calibration parts to be calibrated, all manufactured based on the same manufacturing standard. The interface size of each air transmission line standard part is not less than 1.85mm, and the interface size of each set of coaxial calibration parts is not more than 1.0mm. Each set of coaxial calibration parts includes multiple bias short circuits, open circuits, load circuits, and through circuits. Measurement unit 902 is used to measure the key geometric parameters of each bias short circuit and open circuit based on laser; the key geometric parameters include the outer diameter of the inner conductor, the inner diameter / roundness of the outer conductor, and the length of the air wire. The first determining unit 904 is used to determine the uncertain parameters required for electromagnetic simulation based on the measured scattering parameters of each air transmission line standard. The uncertain parameters include at least the gold plating thickness of the inner / outer conductor, the equivalent conductivity, the surface roughness coefficient, and the convergence criterion of the adaptive mesh generation. Simulation unit 906 is used to simulate the theoretical reflection coefficient of each bias short circuit and open circuit at each set frequency point based on uncertain parameters and key geometric parameters of each bias short circuit and open circuit. The first calculation unit 908 is used to calculate the single-port error coefficient of the vector network analyzer based on the theoretical and measured reflection coefficients for each bias short circuit and open circuit. The second determining unit 910 is used to perform de-embedding processing on the measured reflection coefficient of the load based on the single-port error coefficient to obtain the theoretical reflection coefficient of the load. The second calculation unit 912 is used to calculate the theoretical scattering parameter matrix of the through-pass based on the error coefficient of each port; The encapsulation unit 914 is used to determine the uncertainty of each theoretical reflection coefficient and theoretical scattering parameter matrix at each set frequency point based on Monte Carlo, and encapsulate each theoretical reflection coefficient, theoretical scattering parameter matrix and corresponding uncertainty into a file of a set format for use by the vector network analyzer.

[0057] In some implementations, the measurement unit 902 is used to perform the following operations: The outer diameter of the inner conductor for each biased short circuit and open circuit is measured using a laser diameter gauge method. The inner diameter and roundness of the outer conductor for each bias short circuit and open circuit are measured using the laser confocal method. The axial length of an air line is measured using a laser interferometer method.

[0058] In some implementations, the measured scattering parameters of the air transmission line standard are obtained directly through MTRL calibration; The first determining unit 904 is used to perform the following operations: A full-wave electromagnetic simulation model for each standard air transmission line component was constructed, and initial values ​​for each uncertain parameter in the model were set. The uncertain parameters are used as optimization variables, and the transmission coefficient in the measured scattering parameters of each air transmission line standard is used as the objective function. The parameters of each air transmission line standard are scanned and iteratively optimized in the whole frequency band until the phase deviation between the simulated transmission coefficient and the measured transmission coefficient output by the full-wave electromagnetic simulation model is no greater than the phase deviation threshold and the amplitude deviation is no greater than the amplitude deviation threshold in the whole frequency band, thus obtaining the final uncertain parameters.

[0059] In some implementations, the simulation unit 906 is used to perform the following operations: For each bias short-circuit calibrator and open-circuit calibrator, perform the following operations: Construct an electromagnetic simulation model of the calibration component; The key geometric parameters and uncertain parameters of the calibration component are used as simulation parameters for the electromagnetic simulation model, and the simulation frequency sweep range is set to a continuous frequency band from 0 Hz to the upper limit of the calibration component's use. The calibration component was simulated and calculated under simulation parameters and simulation frequency bands to obtain the theoretical reflection coefficient of the calibration component at each set frequency point.

[0060] In some implementations, the first computing unit 908 is used to perform the following operations: The signal flow graph based on the single-port error model determines each network error term from the instrument port to the test end face of the vector network analyzer. Based on the signal flow graph and Mason's gain formula, the theoretical reflection coefficient and measured reflection coefficient for each bias short circuit and open circuit are determined, as well as the matrix relationship between each network error term. The matrix relations are solved using the singular value decomposition method to obtain the error values ​​of each network error term; The value of the single-port error coefficient is determined based on the relationship between each network error term and the single-port error coefficient.

[0061] In some implementations, the second computing unit 912 is used to perform the following operations: Two ports are connected by a through-through, and the measurement scattering parameter matrix of the through-through network is measured using a vector network analyzer. Based on the single-port error terms and measured scattering parameter matrix of the two ports, the theoretical scattering parameter matrix of the through network is derived by using the SOLR multi-port calibration method.

[0062] It is understood that the structures illustrated in the embodiments of the present invention do not constitute a specific limitation on the device for extracting scattering parameters of an ultra-small coaxial calibration component. In other embodiments of the present invention, a device for extracting scattering parameters of an ultra-small coaxial calibration component may include more or fewer components than illustrated, or combine some components, or split some components, or arrange the components differently. The illustrated components may be implemented in hardware, software, or a combination of software and hardware.

[0063] The information interaction and execution process between the modules in the above-mentioned device are based on the same concept as the method embodiment of the present invention, and the specific details can be found in the description of the method embodiment of the present invention, and will not be repeated here.

[0064] This invention also provides an electronic device, including a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, it implements a method for extracting scattering parameters of an ultra-small coaxial calibration device according to any embodiment of this invention.

[0065] This invention also provides a computer-readable storage medium storing a computer program. When executed by a processor, the computer program causes the processor to perform a method for extracting scattering parameters of an ultra-small coaxial calibration device according to any embodiment of this invention.

[0066] Specifically, a system or apparatus equipped with a storage medium may be provided, on which software program code implementing the functions of any of the embodiments described above is stored, and the computer (or CPU or MPU) of the system or apparatus may read and execute the program code stored in the storage medium.

[0067] In this case, the program code read from the storage medium can itself implement the function of any of the above embodiments, and therefore the program code and the storage medium storing the program code constitute part of the present invention.

[0068] Storage media embodiments for providing program code include floppy disks, hard disks, magneto-optical disks, optical disks (such as CD-ROM, CD-R, CD-RW, DVD-ROM, DVD-RAM, DVD-RW, DVD+RW), magnetic tapes, non-volatile memory cards, and ROMs. Alternatively, program code can be downloaded from a server computer via a communication network.

[0069] Furthermore, it should be clear that not only can the program code read by the computer be executed, but also the operating system or other components operating on the computer can be instructed based on the program code to perform some or all of the actual operations, thereby realizing the function of any of the embodiments described above.

[0070] Furthermore, it is understood that the program code read from the storage medium is written to the memory set in the expansion board inserted into the computer or to the memory set in the expansion module connected to the computer. Then, based on the instructions of the program code, the CPU or other components installed on the expansion board or expansion module execute some and all of the actual operations, thereby realizing the function of any of the above embodiments.

[0071] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0072] 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 them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for extracting scattering parameters of an ultra-small coaxial calibration component, characterized in that, include: Obtain multiple standard air transmission line components suitable for large-size coaxial connectors and multiple sets of ultra-small coaxial calibration components to be calibrated, all manufactured based on the same manufacturing standard. The interface size of each standard air transmission line component is not less than 1.85 mm, and the interface size of each set of coaxial calibration components is not more than 1.0 mm. Each set of coaxial calibration components includes multiple bias short circuits, open circuits, load circuits, and through circuits. The key geometric parameters for each bias short circuit and open circuit are measured using laser technology; these key geometric parameters include the outer diameter of the inner conductor, the inner diameter / roundness of the outer conductor, and the length of the air wire. Based on the measured scattering parameters of each of the aforementioned air transmission line standard components, the uncertain parameters required for electromagnetic simulation are determined. The uncertain parameters include at least the gold plating thickness of the inner / outer conductor, the equivalent conductivity, the surface roughness coefficient, and the convergence criterion for adaptive mesh generation. Based on the aforementioned uncertain parameters and the key geometric parameters of each bias short circuit and open circuit, the theoretical reflection coefficients of each bias short circuit and open circuit at each set frequency point are obtained through simulation. The single-port error coefficient of the vector network analyzer is calculated based on the theoretical and measured reflection coefficients for each bias short circuit and open circuit. Based on the single-port error coefficient, the measured reflection coefficient of the load is de-embedded to obtain the theoretical reflection coefficient of the load; Based on the error coefficient of each port, the theoretical scattering parameter matrix of the through is calculated; The uncertainties of each theoretical reflection coefficient and theoretical scattering parameter matrix at each set frequency point are determined based on Monte Carlo methods. The theoretical reflection coefficient, theoretical scattering parameter matrix and corresponding uncertainties are then packaged into a file with a set format for use by the vector network analyzer.

2. The method according to claim 1, characterized in that, The key geometric parameters for each bias short circuit and open circuit measured using lasers include: The outer diameter of the inner conductor for each biased short circuit and open circuit is measured using a laser diameter gauge method. The inner diameter and roundness of the outer conductor for each bias short circuit and open circuit are measured using the laser confocal method. The axial length of an air line is measured using a laser interferometer method.

3. The method according to claim 1, characterized in that, The measured scattering parameters of the air transmission line standard were obtained directly through MTRL calibration; The determination of uncertain parameters required for electromagnetic simulation based on the measured scattering parameters of each of the air transmission line standard components includes: A full-wave electromagnetic simulation model for each of the aforementioned air transmission line standard components was constructed, and initial values ​​for each uncertain parameter in the model were set. The uncertain parameters are used as optimization variables, and the transmission coefficient in the measured scattering parameters of each air transmission line standard is used as the objective function. Parameter scanning and iterative optimization are performed on each air transmission line standard in the full frequency band until the phase deviation between the simulated transmission coefficient and the measured transmission coefficient output by the full-wave electromagnetic simulation model is no greater than the phase deviation threshold and the amplitude deviation is no greater than the amplitude deviation threshold in the full frequency band, thus obtaining the final uncertain parameters.

4. The method according to claim 1, characterized in that, Based on the uncertain parameters and the key geometric parameters of each bias short circuit and open circuit, the theoretical reflection coefficients of each bias short circuit and open circuit at each set frequency point are simulated, including: For each bias short-circuit calibrator and open-circuit calibrator, perform the following operations: Construct an electromagnetic simulation model of the calibration component; The key geometric parameters of the calibrator and the uncertain parameters are used as simulation parameters for the electromagnetic simulation model, and the simulation frequency sweep range is set to a continuous frequency band from 0Hz to the upper limit of the calibrator's use. The calibration component is simulated and calculated under the specified simulation parameters and frequency bands to obtain the theoretical reflection coefficient of the calibration component at each set frequency point.

5. The method according to claim 1, characterized in that, The single-port error coefficient includes a directivity term, a reflection tracking term, and a source matching term; the calculation of the single-port error coefficient of the vector network analyzer based on the theoretical and measured reflection coefficients for each bias short-circuit and open-circuit includes: The signal flow graph based on the single-port error model determines each network error term from the instrument port to the test end face of the vector network analyzer. Based on the signal flow graph and Mason's gain formula, the theoretical reflection coefficient, measured reflection coefficient, and matrix relationship between each bias short circuit and open circuit are determined. The matrix relationship is solved using the singular value decomposition method to obtain the error values ​​of each network error term; The value of the single-port error coefficient is determined based on the relationship between each network error term and the single-port error coefficient.

6. The method according to claim 1, characterized in that, The through-pass satisfies the reciprocity condition; the calculation of the theoretical scattering parameter matrix of the through-pass based on the error coefficient of each port includes: Two ports are connected by a through-through, and the measurement scattering parameter matrix of the through-through network is measured using a vector network analyzer. Based on the single-port error terms of the two ports and the measured scattering parameter matrix, the theoretical scattering parameter matrix of the through network is derived using the SOLR multi-port calibration method.

7. A device for extracting scattering parameters of an ultra-small coaxial calibration component, characterized in that, include: The acquisition unit is used to acquire multiple air transmission line standard parts suitable for large-size coaxial connectors and multiple sets of ultra-small-size coaxial calibration parts to be calibrated, all manufactured based on the same manufacturing standard. The interface size of each air transmission line standard part is not less than 1.85mm, and the interface size of each set of coaxial calibration parts is not more than 1.0mm. Each set of coaxial calibration parts includes multiple bias short circuits, open circuits, load circuits, and through circuits. A measurement unit is used to measure the key geometric parameters of each bias short circuit and open circuit based on laser; the key geometric parameters include the outer diameter of the inner conductor, the inner diameter / roundness of the outer conductor, and the length of the air wire. The first determining unit is used to determine the uncertain parameters required for electromagnetic simulation based on the measured scattering parameters of each of the air transmission line standard components. The uncertain parameters include at least the gold plating thickness of the inner / outer conductor, the equivalent conductivity, the surface roughness coefficient, and the convergence criterion of the adaptive mesh generation. The simulation unit is used to simulate the theoretical reflection coefficient of each bias short circuit and open circuit at each set frequency point based on the uncertain parameters and the key geometric parameters of each bias short circuit and open circuit. The first calculation unit is used to calculate the single-port error coefficient of the vector network analyzer based on the theoretical and measured reflection coefficients for each bias short circuit and open circuit. The second determining unit is used to perform de-embedding processing on the measured reflection coefficient of the load based on the single-port error coefficient, and obtain the theoretical reflection coefficient of the load. The second calculation unit is used to calculate the theoretical scattering parameter matrix of the through-pass based on the error coefficient of each port; The encapsulation unit is used to determine the uncertainty of each theoretical reflection coefficient and theoretical scattering parameter matrix at each set frequency point based on Monte Carlo, and encapsulate each theoretical reflection coefficient, theoretical scattering parameter matrix and corresponding uncertainty into a file of a set format for use by the vector network analyzer.

8. A computing device comprising a memory and a processor, wherein the memory stores a computer program, and the processor, when executing the computer program, implements the method as described in any one of claims 1-6.

9. A computer-readable storage medium having a computer program stored thereon, which, when executed in a computer, causes the computer to perform the method of any one of claims 1-6.

10. A computer program product, characterized in that, Includes a computer program, which, when executed by a processor, implements the steps of the method according to any one of claims 1-6.

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