Method for measuring high-frequency characteristic of radio frequency coaxial probe

Abstract

The invention relates to the technical field of radio frequency measurement, and discloses a method for measuring the high-frequency characteristic of a radio frequency coaxial probe. The method comprises the following steps: acquiring high-frequency response data of a radio frequency coaxial probe, segmenting a full frequency band based on a predefined frequency band division strategy, and identifying a key frequency band region; according to the response amplitude and phase distribution of the key frequency band region, screening a reference frequency band and extracting an impedance reference value, optimizing impedance matching parameters of a non-reference frequency band based on the reference value, and generating a frequency band impedance optimization parameter set; recombining a full-band impedance distribution sequence according to the parameter set to generate an initial impedance matching scheme; and finally, monitoring the high-frequency transmission deviation under the initial scheme in real time, counting the impedance fluctuation quantity and the phase offset, and generating an impedance correction instruction. The method effectively improves the stability and reliability of the measurement of the high-frequency characteristic of the radio frequency coaxial probe by accurately identifying the key frequency band in a segmented manner, guiding the impedance parameter optimization by the reference value and combining a dynamic correction mechanism.

Description

Technical Field

[0001] This invention relates to the field of radio frequency measurement technology, specifically to a method for measuring the high-frequency characteristics of a radio frequency coaxial probe. Background Technology

[0002] In the fields of microwave communication, radar systems, and radio frequency integrated circuits, radio frequency coaxial probes serve as key components connecting the device under test (DUT) to the measurement system. Their high-frequency characteristics directly affect the accuracy and reliability of measurement results. With the rapid development of high-frequency technology and the continuous increase in signal transmission frequency, the requirements for the high-frequency performance of radio frequency coaxial probes are becoming increasingly stringent. Accurate measurement of their high-frequency characteristics has become an important prerequisite for ensuring the normal operation of related systems.

[0003] Existing methods for measuring the high-frequency characteristics of RF coaxial probes generally employ a uniform approach across the entire frequency band, lacking precise identification of the characteristic differences between different regions within the band. During full-band measurements, due to significant differences in signal transmission characteristics across different frequency bands, some bands may experience signal attenuation or distortion due to impedance mismatch, phase shift, or other issues. Traditional methods struggle to accurately locate these critical problem bands. Furthermore, existing methods often rely on empirical values ​​or fixed algorithms for impedance parameter optimization, failing to fully consider the correlation between the characteristics of different frequency bands. This results in a lack of specificity in the optimization process, making it difficult to achieve balanced matching across the entire frequency band.

[0004] In the initial impedance matching scheme generation stage, existing technologies often directly set parameters based on the overall characteristics of the entire frequency band, without effectively integrating the optimized parameters for each frequency band. This makes the scheme prone to poor matching in local frequency bands during practical applications. Furthermore, in the real-time monitoring and correction stage, traditional methods are not timely enough in responding to transmission deviations, and their statistical analysis of impedance fluctuations and phase shifts is not detailed enough, making it difficult to generate accurate correction commands. This results in insufficient signal transmission stability during measurement, thus affecting the overall accuracy of high-frequency characteristic measurements. These problems limit the applicability of existing measurement methods in high-frequency scenarios, failing to meet the requirements of high-precision measurements. Therefore, there is an urgent need for a measurement method that can accurately identify key frequency bands, optimize impedance parameters, and achieve dynamic correction. Summary of the Invention

[0005] The purpose of this invention is to provide a method for measuring the high-frequency characteristics of an RF coaxial probe, so as to solve the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides a method for measuring the high-frequency characteristics of an RF coaxial probe, the method comprising:

[0007] Collect high-frequency response data from the RF coaxial probe, segment the entire frequency band based on a predefined frequency band division strategy, and identify key frequency band regions;

[0008] Based on the response amplitude and phase distribution of the key frequency band region, a reference frequency band is selected and an impedance reference value is extracted; based on the impedance reference value, the impedance matching parameters of non-reference frequency bands are optimized to generate a set of frequency band impedance optimization parameters.

[0009] Based on the frequency band impedance optimization parameter set, the full-frequency band impedance distribution sequence is reconstructed to generate an initial impedance matching scheme;

[0010] The high-frequency transmission deviation under the initial impedance matching scheme is monitored in real time, and the impedance fluctuation and phase offset are statistically analyzed to generate impedance correction commands.

[0011] Preferably, the segmentation of the entire frequency band based on a predefined frequency band partitioning strategy specifically includes:

[0012] Set the number of frequency band segments and bandwidth threshold, and scan the full frequency band response curve; divide the boundaries of adjacent frequency bands based on the amplitude abrupt change points and phase transition points in the scanning results; calculate the center frequency and bandwidth ratio of each segment, and generate the frequency band division results.

[0013] Preferably, the identification of key frequency band regions specifically includes:

[0014] Analyze the amplitude slope and phase change rate of each frequency band in the frequency band division results, and calibrate the frequency bands that exceed the preset change threshold; statistically analyze the distribution density and adjacent intervals of the calibrated frequency bands, merge the continuously distributed high-density frequency bands, and generate key frequency band feature data.

[0015] Preferably, the step of screening the reference frequency band and extracting the impedance reference value specifically includes:

[0016] Based on the amplitude stability and phase consistency in the key frequency band feature data, the frequency band priorities are sorted; the highest priority frequency band is selected as the reference frequency band, and the average of its real and imaginary impedance parts is extracted to generate the impedance reference value.

[0017] Preferably, the optimized impedance matching parameters for the non-reference frequency band specifically include:

[0018] The difference between the center frequency of the non-reference frequency band and the center frequency of the reference frequency band is calculated; based on the frequency difference weight and the impedance reference value, the real part gradient and imaginary part offset of the impedance are corrected segment by segment; and a set of frequency band impedance optimization parameters is generated.

[0019] Preferably, the reconstructed full-band impedance distribution sequence specifically includes:

[0020] Based on the correction gradient and offset in the frequency band impedance optimization parameter set, adjust the original full-band impedance sequence; redistribute impedance values ​​according to the frequency band boundaries to generate a continuously distributed full-band impedance distribution sequence.

[0021] Preferably, the generation of the initial impedance matching scheme specifically includes:

[0022] The full-band impedance distribution sequence is converted into Smith chart coordinate points; the coordinate points are fitted to generate an impedance matching trajectory, and the offset nodes between the trajectory and the standard circle are calibrated; the matching network parameters are adjusted based on the offset node positions to generate an initial impedance matching scheme.

[0023] Preferably, the real-time monitoring of high-frequency transmission deviation under the initial impedance matching scheme specifically includes:

[0024] Inject test signals and acquire the reflection coefficient and transmission coefficient of the actual transmission; calculate the amplitude difference of the reflection coefficient and the phase difference of the transmission coefficient to generate high-frequency transmission deviation data.

[0025] Preferably, the statistical impedance fluctuation and phase offset specifically include:

[0026] The real part fluctuation and the imaginary part offset in the high-frequency transmission deviation data are decomposed; the fluctuation range and the offset mean within adjacent time windows are accumulated to generate impedance fluctuation and phase offset.

[0027] Preferably, the generated impedance correction command specifically includes:

[0028] The impedance fluctuation is compared with a preset fluctuation threshold, and the phase offset is compared with a preset offset threshold; the position of the over-limit frequency band is calibrated, and an impedance compensation parameter set for the calibrated frequency band is generated as an impedance correction instruction.

[0029] Compared with the prior art, the beneficial effects of the present invention are:

[0030] This RF coaxial probe high-frequency characteristic measurement method, by segmenting and identifying key frequency bands, departs from the traditional uniform processing approach across the entire frequency band, enabling precise capture of the characteristic differences between different frequency bands. In full-band measurements, segmentation based on a predefined frequency band division strategy effectively focuses on regions with significant changes in signal transmission characteristics, preventing critical issues from being masked by mixed frequency band characteristics, thus making the measurement process more targeted. Identifying key frequency band regions provides clear target guidance for subsequent impedance parameter optimization and matching scheme design, ensuring the entire measurement process is based on accurate frequency band characteristic understanding from the data acquisition stage.

[0031] In the impedance parameter optimization stage, this method provides a reliable reference for optimizing non-reference frequency bands by selecting a reference frequency band and extracting a reference impedance value. The selection of the reference frequency band is based on the response amplitude and phase distribution of the key frequency band, ensuring the representativeness and rationality of the reference value. This allows the optimization of impedance matching parameters in non-reference frequency bands to move away from relying on experience or fixed patterns and instead make targeted adjustments based on the reference value. This reference-guided optimization method effectively reduces impedance differences between different frequency bands, minimizes signal transmission loss caused by unreasonable parameter settings, and makes the impedance distribution across the entire frequency band more balanced.

[0032] After generating the frequency band impedance optimization parameter set, an initial impedance matching scheme is generated by recombining the full-band impedance distribution sequence, thus achieving the organic integration of optimization parameters for each frequency band. Compared to the dispersed parameter settings in traditional methods, this recombining approach can incorporate optimization parameters from different frequency bands into a unified impedance distribution system, ensuring smoother characteristic transitions between frequency bands, reducing signal reflection and interference at frequency band boundaries, and improving the stability of the initial scheme across the entire frequency band.

[0033] The introduction of a real-time monitoring and correction mechanism further enhances the dynamic adaptability of the measurement process. By monitoring the high-frequency transmission deviation under the initial matching scheme in real time, statistically analyzing impedance fluctuations and phase shifts, and generating correction commands, it can promptly address characteristic drift caused by environmental changes, device aging, and other factors during the measurement process. This dynamic correction capability avoids performance degradation of fixed schemes under long-term or complex environments, enabling the measurement system to maintain a good signal transmission state continuously, thereby improving the overall consistency and uniformity of high-frequency characteristic measurements. Attached Figure Description

[0034] Figure 1 This is a schematic diagram illustrating the working principle of the radio frequency coaxial probe high-frequency characteristic measurement method described in this invention.

[0035] Figure 2 Flowchart for identifying key frequency band regions;

[0036] Figure 3 This is a flowchart for reference frequency band selection and impedance reference value extraction.

[0037] Figure 4 A flowchart generated for the initial impedance matching scheme. Detailed Implementation

[0038] 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 only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0039] Please see Figure 1 This invention provides a method for measuring the high-frequency characteristics of an RF coaxial probe, the method comprising:

[0040] A high-frequency characteristic measurement method for RF coaxial probes achieves high-precision impedance matching across the entire frequency band by optimizing impedance matching parameters in stages. This method acquires high-frequency response data from the RF coaxial probe, segments the entire frequency band based on a predefined frequency band division strategy, and identifies key frequency band regions. A reference frequency band is selected based on the response amplitude and phase distribution of the key frequency band regions, and an impedance reference value is extracted. Impedance matching parameters for non-reference frequency bands are then optimized based on this reference value, generating a set of optimized frequency band impedance parameters. The entire frequency band impedance distribution sequence is further reconstructed to generate an initial impedance matching scheme. By real-time monitoring of high-frequency transmission deviations under the initial impedance matching scheme, impedance fluctuations and phase shifts are statistically analyzed to generate impedance correction commands, achieving dynamic adjustment.

[0041] Example 1: See Figure 2 The execution of the frequency band division strategy begins with setting two key parameters: the number of frequency band segments and the bandwidth threshold. The number of frequency band segments is determined based on the total frequency band covered by the probe design, combined with the statistical characteristics of signal distribution in typical application scenarios. The bandwidth threshold is not a fixed value; its magnitude needs to be dynamically adjusted with reference to the overall trend of the high-frequency response curve in the amplitude and phase dimensions to adapt to the needs of different probe models or measurement environments. The scanning operation of the full-band response curve is completed by automated measurement equipment, using a sliding window algorithm as the core detection mechanism. This algorithm moves the analysis window along the frequency axis with a preset step size, simultaneously analyzing amplitude and phase data at each window position. The identification criterion for amplitude abrupt changes is defined as the absolute value of the amplitude difference between adjacent sampling points exceeding a preset dynamic threshold value, which is set according to the probe's sensitivity index. The detection of phase transition points relies on the calculation of the phase derivative; when the phase change rate exceeds an independently set threshold, a phase transition is determined to exist at that location. The delineation of adjacent frequency band boundaries is strictly based on the spatial distribution of detected amplitude abrupt changes and phase transition points. Locations where the two types of feature points coincide or are adjacent are preferentially selected as boundary points to ensure that amplitude and phase changes within each divided frequency band remain relatively continuous, avoiding drastic jumps within a single band. After frequency band delineation, the center frequency and bandwidth percentage of each independent segment need to be calculated. The center frequency is calculated using an amplitude-weighted average method, that is, the amplitude value of each frequency point within the band is assigned a weight, and the weighted average frequency value is used as the center frequency of that band. The bandwidth percentage is calculated by dividing the frequency span of the band itself by the total bandwidth of the probe's entire frequency band, representing the relative width of the band in the entire frequency band as a percentage. The final frequency band delineation result includes the start frequency, end frequency, center frequency, and bandwidth percentage data of all segmented frequency bands, forming the basic structure for subsequent processing.

[0042] The identification process for key frequency band regions is based on the aforementioned frequency band division results. The core task of this step is to screen out regions with significant characteristics and drastic changes from all the divided frequency bands. In specific implementation, quantitative analysis of amplitude slope and phase change rate needs to be performed on each independent frequency band. The amplitude slope is calculated by linearly fitting the discrete points of amplitude change with frequency within the frequency band using the least squares method. The slope of the resulting fitted line is the quantized value of the amplitude change rate of that frequency band. The phase change rate is calculated using the difference method, that is, calculating the phase difference between the start and end points of the frequency band and then dividing it by the frequency band bandwidth to obtain the average phase change per unit frequency. The preset change threshold is pre-set according to the specific type of probe and the typical signal characteristics of its target application scenario. This threshold distinguishes between normal changes and drastic changes. The calibration operation involves comparing the absolute value of the amplitude slope and the absolute value of the phase change rate calculated for each frequency band with the preset threshold. Frequency bands with any index exceeding the threshold are marked as candidate key frequency bands. When calculating the distribution density of calibration frequency bands, the number of calibrated frequency bands per unit bandwidth needs to be calculated. This density value reflects the degree of clustering of key features in the spectrum. Adjacent interval statistics calculate the difference between the center frequencies of two adjacent calibrated frequency bands, reflecting the dispersion of key feature distribution. Merging continuously distributed high-density frequency bands is a crucial step in identifying the final key region. The triggering condition for the merging operation is based on a comparison between the interval distance of adjacent calibrated frequency bands and a preset merging threshold. If the interval between adjacent calibrated frequency bands is less than the merging threshold, these frequency bands are considered to be continuously and densely distributed in the spectrum and should be merged into a larger key frequency band region. The merging threshold is not fixed but dynamically adjusted based on the average bandwidth of the merged frequency bands, typically taking a multiple of the average bandwidth. The boundary of the new key frequency band after merging is taken as the leftmost start frequency and rightmost end frequency of the merged frequency bands, and the key feature data within it is integrated. The final generated key frequency band feature data includes boundary information, center frequency, number of original calibration frequency bands before merging, and statistical values ​​of amplitude and phase change characteristics after merging for all identified key frequency band regions, providing clear regional indications for subsequent reference frequency band selection. The entire process relies on precise quantitative analysis of high-frequency response curve characteristics and a merging strategy based on statistical laws, aiming to accurately capture frequency regions where the probe exhibits abnormal behavior or requires special attention across the entire frequency range.

[0043] Example 2: See Figure 3The selection of reference frequency bands begins with in-depth analysis of the characteristic data of the identified key frequency bands. The core basis is the stability and consistency of each key frequency band in the amplitude dimension. Amplitude stability is quantitatively assessed by calculating the dispersion of amplitude values ​​corresponding to all frequency sampling points within a specific frequency band. Specifically, it calculates the average of the sum of squares of the deviations of all amplitude values ​​within the band from their arithmetic mean. This value directly reflects the severity of amplitude fluctuations within the band; a smaller value indicates greater amplitude stability. Phase consistency is assessed by focusing on the range of phase value changes within the band. This is done by identifying the maximum and minimum values ​​among all phase sampling points within the band and calculating the difference between them. The magnitude of this difference characterizes the level of phase consistency within the band; a smaller difference indicates smoother phase changes and higher consistency. When prioritizing key frequency bands, both amplitude stability and phase consistency must be considered. Therefore, weighting coefficients are assigned to the amplitude stability and phase consistency indicators, with the specific values ​​of these coefficients pre-set based on the probe's design objectives and the focus of high-frequency measurements. The priority score for each critical frequency band is calculated by multiplying its amplitude stability assessment value by the corresponding weighting coefficient, and then adding its phase consistency assessment value multiplied by the corresponding weighting coefficient. After the score calculation, all critical frequency bands are sorted from highest to lowest score, and the critical frequency band with the highest score is selected as the reference frequency band. Once the reference frequency band is determined, representative impedance reference values ​​need to be extracted from it. The extraction process involves calculating the arithmetic mean of the real part of the impedance corresponding to all frequency sampling points within the reference frequency band, which serves as the reference value for the real part of the impedance. Simultaneously, the arithmetic mean of the imaginary part of the impedance corresponding to all frequency sampling points within the reference frequency band is calculated, which serves as the reference value for the imaginary part of the impedance. The final generated impedance reference value contains both the real and imaginary reference values, which together constitute the reference benchmark for subsequent impedance optimization of non-reference frequency bands.

[0044] The optimization process of impedance matching parameters in non-reference frequency bands closely depends on the aforementioned impedance reference values ​​and the frequency relationship between the non-reference and reference frequency bands. The first step in the optimization operation is to calculate the absolute difference between the center frequency of each non-reference band and the center frequency of the reference band. This frequency difference is a crucial parameter determining the optimization weight. The calculation rule for the frequency difference weight is that the frequency difference is inversely proportional to the weight; that is, the larger the frequency difference, the lower the corresponding weight. This weight allocation method reflects that the optimization process of frequency bands farther from the reference band should be less affected by the reference value. Correction of the real part gradient of impedance is one of the core aspects of optimization. The goal of the correction is to smoothly adjust the trend of the real part change of the non-reference band based on the reference value and its frequency distance from the reference band. During correction, the trend of the original real part of the non-reference band changing with frequency is first analyzed, and then the slope or amplitude of this trend is adjusted proportionally according to the calculated frequency difference weight. The direction and degree of adjustment aim to make the real part distribution of the entire frequency band present a more coherent transition, reducing abrupt changes that may be caused by frequency band division. The correction of the imaginary offset directly applies the imaginary reference value in the impedance reference value. During correction, the difference between the arithmetic mean of the original imaginary values ​​of the non-reference frequency band and the imaginary reference value is calculated. Then, based on the frequency difference weight corresponding to the non-reference frequency band, this difference is adjusted proportionally. The adjusted difference is the required imaginary offset correction value for the non-reference frequency band. In practical application, this correction value is superimposed on the original imaginary value of each frequency sampling point within the non-reference frequency band, thus completing the imaginary optimization of that frequency band. After the above real part gradient correction and imaginary offset correction, each non-reference frequency band obtains a set of optimized parameters, including the corrected real part change gradient description and the imaginary offset value. These optimized parameters for all non-reference frequency bands are summarized and organized to form a structured set of frequency band impedance optimization parameters. This parameter set records in detail the identification information of each non-reference frequency band, the corresponding frequency difference weight, the corrected real part gradient parameters, and the corrected imaginary offset parameters, providing a precise adjustment basis for the next step of reconstructing the full-band impedance distribution sequence. The entire process embodies a strategy of using the reference frequency band as an anchor point and dynamically adjusting the optimization intensity based on the spectral distance, aiming to achieve coordination and optimization of impedance characteristics across the entire frequency band.

[0045] Example 3: See Figure 4The core task of this step is to reintegrate the optimized impedance parameters of each frequency band into a continuous full-band impedance distribution, and based on this, generate a preliminary impedance matching scheme. The operation of reconstructing the full-band impedance distribution sequence begins with the analytical processing of the optimized frequency band impedance parameter set. This parameter set contains the optimized real gradient parameters and imaginary offset parameters for each non-reference frequency band, as well as the boundary frequency information for each band. During implementation, it is first necessary to establish a mapping framework between the frequency axis and impedance values ​​for the entire frequency band. This framework uses frequency as the independent variable and impedance value as the dependent variable, covering the entire frequency range of the probe's operation.

[0046] The key to impedance sequence reconstruction lies in achieving a smooth transition between adjacent frequency bands. For any two adjacent frequency bands, the impedance values ​​at their boundary are processed using a weighted average method:

[0047]

[0048] Among them: Z boundary This represents the final impedance value at the boundary. This represents the impedance value at the end of the nth frequency band. Let w1 and w2 be the starting impedance values ​​for the (n+1)th frequency band, and w1 and w2 be weighting coefficients dynamically adjusted according to the frequency band characteristics, satisfying w1 + w2 = 1. The specific values ​​of the weighting coefficients depend on the center frequency distance between two adjacent frequency bands and their respective optimized parameter characteristics. This approach effectively avoids impedance abrupt changes caused by frequency band division, ensuring the continuity of impedance distribution across the entire frequency band.

[0049] After boundary processing, the impedance distribution within each independent frequency band is reconstructed. The impedance value distribution within a frequency band is generated using an interpolation method based on optimized parameters. For the reconstruction of the real part, the real part value corresponding to each frequency point within the band is calculated based on the optimized real part gradient parameters of that frequency band. In practice, the center frequency of the frequency band is used as a reference point, and linear expansion is performed to both sides according to the optimized gradient parameters. The reconstruction of the imaginary part directly applies the optimized imaginary part offset parameters to systematically adjust the original imaginary part values. After the internal reconstruction of each frequency band is completed, it is connected with adjacent frequency bands using the aforementioned boundary processing method, ultimately forming a complete full-band impedance distribution sequence.

[0050] The initial impedance matching scheme generation process uses the reconstructed full-band impedance distribution sequence as input. This process first discretizes the continuous impedance distribution sequence into a set of coordinate points recognizable by the Smith chart. During discretization, characteristic frequency points are uniformly selected across the entire frequency band according to a preset sampling density, and the normalized impedance value corresponding to each point is calculated. Normalization is performed using a standard reference impedance value.

[0051]

[0052] Where Γ is the reflection coefficient, Z is the measured impedance value, and Z0 is the system reference impedance value. This transformation maps the impedance value to coordinate points on the Smith chart, facilitating subsequent visualization analysis and processing.

[0053] After the coordinate point set is generated, an impedance change trajectory is constructed using a curve fitting algorithm. The fitting process considers the characteristic differences of each frequency band, assigning different fitting weights to different bands. The reference frequency band and its adjacent bands are typically given higher weights to ensure impedance matching accuracy in these critical areas. The fitted trajectory curve reflects the impedance change pattern of the probe across the entire frequency range. This trajectory is compared and analyzed with the ideal matching circle to identify feature nodes with significant deviations. These nodes are usually distributed at locations where the trajectory curvature changes significantly, or in sections where the distance from the ideal circle exceeds a preset threshold.

[0054] Based on the identified deviation nodes, a preliminary design of the matching network parameters is performed. The matching network adopts a classic LC topology. The required inductor and capacitor parameters are calculated according to the frequency position and degree of deviation of the nodes. For deviations in the low-frequency range, priority is given to adjusting the series inductors; for deviations in the high-frequency range, the optimization of the parallel capacitors is emphasized. The parameter values ​​of each component are determined through iterative calculations, ensuring that the impedance trajectory in the corresponding frequency band approaches the ideal circle. After multiple rounds of parameter adjustments, a preliminary LC matching network design scheme, i.e., the initial impedance matching scheme, is formed.

[0055] The entire implementation process emphasizes the coherence of data processing and the systematic nature of parameter adjustment. The reassembly of the impedance distribution sequence not only considers the characteristic optimization within each frequency band but also focuses on the smoothness of transitions between frequency bands. The generation of the initial matching scheme is based on accurate impedance distribution characterization and is achieved through a combination of visualization analysis and parameterized adjustment. This method avoids the limitations of traditional matching design's over-reliance on local optimization and achieves coordinated matching across the entire frequency band.

[0056] Example 4: The main task of this step is to monitor the performance of the initial impedance matching scheme under actual operating conditions in real time and to quantitatively analyze its transmission characteristic deviation. The implementation process begins with the injection of a test signal, using a swept-frequency signal as the excitation source, whose frequency range covers the entire operating frequency band of the probe. The output power of the signal source is set according to the rated operating conditions of the probe to avoid overdrive or underdrive. After signal injection, the incident wave and reflected wave are separated by a directional coupler, and the output signal of the transmission channel is acquired simultaneously.

[0057] The reflection coefficient and transmission coefficient were measured using a vector network analyzer. The measurement system required rigorous pre-calibration to eliminate the influence of systematic errors. During calibration, standard calibration components were used to perform open-circuit, short-circuit, load, and through-circuit calibrations sequentially to ensure impedance matching at the measurement ports and the accuracy of the signal transmission path. During measurement, the vector network analyzer scanned the entire frequency band at discrete frequency points, recording the amplitude and phase information of the reflection coefficient and transmission coefficient at each frequency point. These raw measurement data form the basis for subsequent deviation analysis.

[0058] The generation of high-frequency transmission deviation data is based on a comparative analysis of measured and ideal values. For the reflection coefficient, the algebraic difference between the measured amplitude and the ideal amplitude at each frequency point is calculated; for the transmission coefficient, the algebraic difference between the measured phase and the ideal phase is calculated. The ideal values ​​are determined based on the probe design specifications and the theoretical calculation results of the initial impedance matching scheme. The deviation data is recorded with timestamps to facilitate subsequent analysis of trends over time. In a typical implementation, the measurement system performs a full-band scan at a rate of 10 times per second, and the continuous monitoring time is set according to application requirements, typically no less than 30 minutes.

[0059] The statistical processing of impedance fluctuations and phase offsets employs a sliding time window method. The window length is dynamically adjusted according to signal stability requirements; a longer window is used in regions with gentle signal changes to improve statistical stability, while the window length is shortened in regions with rapid signal changes to capture fast-changing characteristics. Within each window, the range of the real part fluctuation is statistically analyzed, i.e., the difference between the maximum and minimum real part deviations within the window is calculated; for the imaginary part offset, the arithmetic mean of all sampling points within the window is calculated. The statistical results are categorized and summarized by frequency band to form structured analytical data.

[0060] Table 1: Statistical examples of impedance fluctuations and phase shifts in typical frequency bands.

[0061]

[0062] Refer to Table 1 for the statistical results of the four typical frequency bands within a 30-minute monitoring period. The data shows that different frequency bands exhibit different fluctuation characteristics. The real part fluctuation in the low-frequency band (1.0-1.5 GHz) is relatively small, while the high-frequency band (2.5-3.0 GHz) shows a larger phase shift. This frequency domain difference reflects the difference in the probe's response characteristics in different frequency ranges, providing a basis for subsequent targeted adjustments.

[0063] The key step in the implementation process is the real-time analysis and feature extraction of deviation data. The analysis algorithm first performs noise filtering on the raw measurement data, using digital filters to eliminate high-frequency noise and power frequency interference introduced by the measurement system. The filtered data is then segmented by frequency band, and characteristic parameters for each band are calculated. For reflection coefficient amplitude data, its local maxima and minima are extracted as fluctuation feature points; for transmission coefficient phase data, its rate of change is calculated as a stability index. These characteristic parameters are correlated with time information to form a multi-dimensional monitoring dataset.

[0064] Impedance fluctuations are calculated using a layered approach. First, hotspot regions with significant fluctuations are identified across the entire frequency band, followed by detailed analysis within these regions. Hotspot identification is based on the spatial distribution of the rate of change of the reflection coefficient amplitude; continuous frequency intervals with rates of change exceeding a threshold are marked as hotspots. Within these hotspot regions, the time-varying characteristics of the real and imaginary parts of the impedance are further analyzed, and their statistical distribution parameters are calculated. The calculation of phase offset focuses on the group delay characteristics of the transmission channel, analyzing the temporal consistency of signal transmission through the phase-frequency derivative relationship.

[0065] The monitoring system adopts a modular architecture, comprising a signal acquisition module, a data processing module, and a results display module. The signal acquisition module controls the measuring instruments to complete signal excitation and response acquisition; the data processing module executes deviation calculation and statistical analysis algorithms; and the results display module provides a graphical interface to intuitively display the fluctuation trends and offset characteristics of each frequency band. During system operation, the modules exchange data through standard interface protocols to ensure the continuity of the processing flow and the integrity of the data.

[0066] The entire implementation process emphasizes real-time monitoring and comprehensive analysis. Real-time monitoring is reflected in the pipeline operation mode of data acquisition and processing, ensuring timely capture of transient anomalies; comprehensive analysis is manifested in the integrated monitoring of the entire frequency band and multiple parameters, avoiding the limitations of traditional methods that only focus on individual frequencies or single parameters. Through this implementation method, the performance characteristics of the initial impedance matching scheme under actual working conditions can be fully grasped, providing reliable data support for subsequent precise adjustments. The structured storage and visualization of monitoring data also facilitate historical comparison and trend analysis, helping to identify potential problem patterns and optimization directions.

[0067] Example 5: The core task of this step is to generate targeted impedance parameter adjustment commands based on the impedance fluctuation and phase offset data obtained from real-time monitoring. The implementation process begins with setting preset fluctuation and offset thresholds. These thresholds are not fixed values, but are dynamically configured according to the specific probe model, operating frequency range, and accuracy requirements of the application scenario. The threshold settings consider the theoretical performance boundaries of the probe under ideal matching conditions and are appropriately relaxed in combination with the typical noise level in the actual measurement environment. The fluctuation threshold mainly constrains the allowable range of impedance real part variation, while the offset threshold limits the acceptable level of phase deviation.

[0068] The comparison of impedance fluctuation with preset fluctuation thresholds is performed independently by frequency band. For each frequency band, the statistically obtained real-part fluctuation range within the monitoring period is compared with the corresponding fluctuation threshold. The comparison result yields three states: fluctuation range is below the lower threshold limit, within the threshold range, or exceeds the upper threshold limit. The comparison of phase offset with preset offset thresholds uses the same logic, comparing the statistically obtained imaginary-part offset mean or phase offset mean with the corresponding threshold. The comparison operation is performed periodically at set time intervals to ensure continuous tracking of the probe's operating status.

[0069] The calibration of out-of-limit frequency bands is triggered based on the comparison results mentioned above. When the impedance fluctuation of a frequency band exceeds its fluctuation threshold or its phase offset exceeds its offset threshold, that frequency band is marked as an out-of-limit band. The calibration process considers the adjacency of frequency bands; if multiple adjacent frequency bands exceed the limit simultaneously, these bands are merged into a single out-of-limit region for processing, avoiding fragmented adjustments. The calibration results record the start frequency, end frequency, out-of-limit type (fluctuation out-of-limit or offset out-of-limit), and severity level of the out-of-limit frequency band. The severity level is determined based on the proportion of the out-of-limit value exceeding the threshold; the higher the proportion, the higher the severity level.

[0070] Generating the impedance compensation parameter set for the calibration frequency band is the core step. The compensation parameters are divided into two categories: real-part compensation and imaginary-part compensation, corresponding to different over-limit types. For frequency bands with fluctuation exceeding the limit, primarily real-part compensation is generated. This compensation is calculated based on the value of the fluctuation range exceeding the fluctuation threshold, combined with historical fluctuation characteristics of the frequency band, to determine a proportional coefficient. The final real-part compensation is the product of the excess value and this proportional coefficient, and its effect is aimed at suppressing real-part fluctuations. For frequency bands with offset exceeding the limit, primarily imaginary-part compensation is generated. The imaginary-part compensation is calculated based on the value of the offset mean exceeding the offset threshold, also combined with historical offset data to determine a proportional coefficient. The final compensation is the product of the excess value and the proportional coefficient, and its effect is aimed at correcting phase offset. For frequency bands with both types of over-limits, both types of compensation are generated in parallel.

[0071] The generated impedance compensation parameter set is organized in a structured data format. This dataset contains multiple entries, each corresponding to a calibrated out-of-limit frequency band or out-of-limit region. Each entry records the following information in detail: frequency band identifier (start and end frequencies), out-of-limit type identifier, severity level, calculated real part compensation (if applicable), and calculated imaginary part compensation (if applicable). This parameter set constitutes the final impedance correction instruction.

[0072] The impedance correction command output and application process is as follows: The command output uses a standardized, machine-readable format for easy parsing and execution by the automatic control system. The application process involves transmitting the compensation parameters from the command to the probe's impedance matching network adjustment unit. The adjustment unit locates the circuit module requiring adjustment based on the frequency band identifier in the command, and then adjusts the parameters of the corresponding adjustable components (such as variable capacitors, variable inductors, or resistor arrays) according to the compensation amount and type. The adjustment amount directly corresponds to the compensation value specified in the command. For example, for real part compensation, the resistance or inductance value in the matching network may be adjusted; for imaginary part compensation, the capacitance value may be adjusted. The adjustment operation is completed within milliseconds, ensuring rapid response to changes in the probe's operating state.

[0073] The entire implementation process emphasizes the targeted and timely generation of instructions. Targetedness is reflected in the fact that compensation parameters are strictly tailored to the specific exceedance conditions of each frequency band, rather than being adjusted globally. Timeliness is achieved through a rapid monitoring-analysis-decision-execution closed loop, ensuring that probe performance deviations are corrected in the shortest possible time. The calculation logic of the compensation parameters takes historical data into account, giving the adjustment strategy a certain degree of adaptability and avoiding over-compensation or under-compensation. The standardized design of the instruction data structure also ensures efficient integration with downstream control systems, achieving seamless connection from monitoring and analysis to execution and adjustment. This implementation enables the probe to maintain stable high-frequency transmission characteristics in complex operating environments.

[0074] 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 process, method, article, or apparatus.

[0075] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for measuring the high-frequency characteristics of an RF coaxial probe, characterized in that, include: Collect high-frequency response data from the RF coaxial probe, segment the entire frequency band based on a predefined frequency band division strategy, and identify key frequency band regions; Based on the response amplitude and phase distribution of the key frequency band region, a reference frequency band is selected and an impedance reference value is extracted; based on the impedance reference value, the impedance matching parameters of non-reference frequency bands are optimized to generate a set of frequency band impedance optimization parameters. Based on the frequency band impedance optimization parameter set, the full-frequency band impedance distribution sequence is reconstructed to generate an initial impedance matching scheme; The high-frequency transmission deviation under the initial impedance matching scheme is monitored in real time, and the impedance fluctuation and phase offset are statistically analyzed to generate impedance correction commands.

2. The method for measuring the high-frequency characteristics of an RF coaxial probe according to claim 1, characterized in that, The segmentation of the entire frequency band based on a predefined frequency band partitioning strategy specifically includes: Set the number of frequency band segments and bandwidth threshold, and scan the full frequency band response curve; divide the boundaries of adjacent frequency bands based on the amplitude abrupt change points and phase transition points in the scanning results; calculate the center frequency and bandwidth ratio of each segment, and generate the frequency band division results.

3. The method for measuring the high-frequency characteristics of an RF coaxial probe according to claim 2, characterized in that, The identification of key frequency band regions specifically includes: Analyze the amplitude slope and phase change rate of each frequency band in the frequency band division results, and calibrate the frequency bands that exceed the preset change threshold; statistically analyze the distribution density and adjacent intervals of the calibrated frequency bands, merge the continuously distributed high-density frequency bands, and generate key frequency band feature data.

4. The method for measuring the high-frequency characteristics of an RF coaxial probe according to claim 3, characterized in that, The process of selecting the reference frequency band and extracting the impedance reference value specifically includes: Based on the amplitude stability and phase consistency in the key frequency band feature data, the frequency band priorities are sorted; the highest priority frequency band is selected as the reference frequency band, and the average of its real and imaginary impedance parts is extracted to generate the impedance reference value.

5. The method for measuring the high-frequency characteristics of an RF coaxial probe according to claim 4, characterized in that, The optimized impedance matching parameters for non-reference frequency bands specifically include: The difference between the center frequency of the non-reference frequency band and the center frequency of the reference frequency band is calculated; based on the frequency difference weight and the impedance reference value, the real part gradient and imaginary part offset of the impedance are corrected segment by segment; and a set of frequency band impedance optimization parameters is generated.

6. The method for measuring the high-frequency characteristics of an RF coaxial probe according to claim 5, characterized in that, The reconstructed full-band impedance distribution sequence specifically includes: Based on the correction gradient and offset in the frequency band impedance optimization parameter set, adjust the original full-band impedance sequence; redistribute impedance values ​​according to the frequency band boundaries to generate a continuously distributed full-band impedance distribution sequence.

7. The method for measuring the high-frequency characteristics of an RF coaxial probe according to claim 6, characterized in that, The method for generating the initial impedance matching scheme specifically includes: The full-band impedance distribution sequence is converted into Smith chart coordinate points; the coordinate points are fitted to generate an impedance matching trajectory, and the offset nodes between the trajectory and the standard circle are calibrated; the matching network parameters are adjusted based on the offset node positions to generate an initial impedance matching scheme.

8. The method for measuring the high-frequency characteristics of an RF coaxial probe according to claim 7, characterized in that, The real-time monitoring of high-frequency transmission deviation under the initial impedance matching scheme specifically includes: Inject test signals and acquire the reflection coefficient and transmission coefficient of the actual transmission; calculate the amplitude difference of the reflection coefficient and the phase difference of the transmission coefficient to generate high-frequency transmission deviation data.

9. The method for measuring the high-frequency characteristics of an RF coaxial probe according to claim 8, characterized in that, The statistical impedance fluctuation and phase offset specifically include: The real part fluctuation and the imaginary part offset in the high-frequency transmission deviation data are decomposed; the fluctuation range and the offset mean within adjacent time windows are accumulated to generate impedance fluctuation and phase offset.

10. The method for measuring the high-frequency characteristics of an RF coaxial probe according to claim 9, characterized in that, The generated impedance correction command specifically includes: The impedance fluctuation is compared with a preset fluctuation threshold, and the phase offset is compared with a preset offset threshold; the position of the over-limit frequency band is calibrated, and an impedance compensation parameter set for the calibrated frequency band is generated as an impedance correction instruction.

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