A method and system for calibrating the frequency response of a spectrum analyzer

Abstract

The present invention proposes a method and system for calibrating the frequency response of a spectrum analyzer. The method includes: step S1, intercepting the frequency response data to be calibrated from the radio frequency signal output by the spectrum analyzer, and obtaining the standard error threshold of the spectrum analyzer, determining the calibration threshold based on the standard error threshold, and the calibration threshold is less than the standard error threshold; step S2, marking N data points contained in the frequency response data to be calibrated in a two-dimensional coordinate system, selecting M characterization data points from the N data points based on the calibration threshold, and the M characterization data points are used to characterize the calibration amount of N-M data points other than the M characterization data points; step S3, calibrating the M characterization data points by amplitude compensation, and determining the calibration amount of N-M data points based on the calibration amount of the M characterization data points, and calibrating the N-M data points with the calibration amount of the N-M data points.

Description

Technical Field

[0001] The invention belongs to the technical field of digital signal processing, and in particular relates to a method and a system for calibrating the frequency response of a spectrum analyzer. Background Art

[0002] When calibrating the frequency response of a spectrum analyzer, there are two variables: frequency and attenuation. Usually, an appropriate step frequency should be selected within the measured frequency band to test and calibrate each attenuation point by point. Although this method is feasible, due to the large number of calibration points, for example: 10M to 3800M, 10M step, a total of 380 points, a total of 25 attenuators, the time for each point is about 0.2s, and it takes 38025*0.6=1.58 hours. If the frequency range is to 50G, the calibration time will take about 21 hours. Calibration will consume a lot of time and have low production efficiency. Summary of the invention

[0003] In order to solve the above technical problems, the present invention proposes a solution for calibrating the frequency response of a spectrum analyzer, so as to effectively reduce the number of calibration points, save calibration time, and improve production efficiency.

[0004] Specifically, for each attenuation, calibration is unavoidable. The solution adopted by the present invention is to reduce the frequency points, that is, to analyze the original data and find that there are many invalid points, which can be replaced by adjacent points or obtained by the linear difference between two adjacent points. In addition, it is also found that the change trend of each attenuation is the same, and the frequency point can be found by one attenuation, and the same frequency point can be used for other attenuations; usually, an attenuation with the worst standing wave in a channel is selected, and the default is usually 0dB when the standing wave is the worst. The purpose of the present invention is to improve production efficiency while also taking into account the performance indicators of the entire machine.

[0005] The first aspect of the present invention discloses a method for calibrating the frequency response of a spectrum analyzer. The method comprises:

[0006] Step S1, intercepting frequency response data to be calibrated from a radio frequency signal output by a spectrum analyzer, and obtaining a standard error threshold of the spectrum analyzer, and determining a calibration threshold based on the standard error threshold, wherein the calibration threshold is less than the standard error threshold;

[0007] Step S2, marking N data points included in the frequency response data to be calibrated in a two-dimensional coordinate system, and selecting M characterization data points from the N data points based on the calibration threshold value, wherein the M characterization data points are used to characterize the calibration amounts of NM data points other than the M characterization data points;

[0008] The horizontal axis of the two-dimensional coordinate system represents frequency, and the vertical axis represents amplitude. The horizontal axis of each data point in the N data points is the frequency value of the data point, and the vertical axis is the amplitude value of the data point.

[0009] Step S3, calibrating the M characterization data points by means of amplitude compensation, determining the calibration amounts of the NM data points based on the calibration amounts of the M characterization data points, and calibrating the NM data points with the calibration amounts of the NM data points.

[0010] According to the method of the first aspect of the present invention, in the step S1, intercepting the frequency response data to be calibrated from the radio frequency signal output by the spectrum analyzer includes: performing amplitude attenuation detection on the radio frequency signal output by the spectrum analyzer, and when continuous amplitude attenuation is detected within a specified time period and the attenuation amplitude exceeds an attenuation threshold, intercepting a discrete signal exceeding the attenuation threshold within the specified time period as the frequency response data to be calibrated.

[0011] According to the method of the first aspect of the present invention, in step S1, the standard error threshold is the factory configuration data of the spectrum analyzer, and the calibration threshold is 0.3-0.7 times the standard error threshold.

[0012] According to the method of the first aspect of the present invention, in the step S2, selecting the M characterization data points from the N data points based on the calibration threshold value specifically includes:

[0013] Step S2-1:

[0014] Taking the first data point as the starting point and the Nth data point as the end point, constructing a first connecting line, determining the absolute values ​​of the vertical distances between the remaining data points whose horizontal coordinate values ​​are within the range from the horizontal coordinate of the first data point to the horizontal coordinate of the Nth data point and the first connecting line, as a first vertical distance set, and when the maximum vertical distance in the first vertical distance set exceeds the calibration threshold, obtaining the point corresponding to the maximum vertical distance in the first vertical distance set as the first characterization data point;

[0015] Step S2-2:

[0016] Taking the first characterizing data point as a starting point and the first data point as an end point, constructing a second connecting line, determining the absolute values ​​of the vertical distances between the remaining data points whose abscissa values ​​are within the range from the abscissa of the first characterizing data point to the abscissa of the first data point and the second connecting line, as a second vertical distance set, and when the maximum vertical distance in the second vertical distance set exceeds the calibration threshold, obtaining a point corresponding to the maximum vertical distance in the second vertical distance set as a second characterizing data point;

[0017] Taking the first characterizing data point as a starting point and the Nth data point as an end point, constructing a third connecting line, determining the absolute values ​​of the vertical distances between the remaining data points whose abscissa values ​​are within the range from the abscissa of the first characterizing data point to the abscissa of the Nth data point and the third connecting line, as a third vertical distance set, and when the maximum vertical distance in the third vertical distance set exceeds the calibration threshold, obtaining a point corresponding to the maximum vertical distance in the third vertical distance set as a third characterizing data point;

[0018] Step S2-3:

[0019] Taking the second characterizing data point as a starting point and the first data point as an end point, constructing a fourth connecting line, determining the absolute values ​​of the vertical distances between the remaining data points whose abscissa values ​​are within the range from the abscissa of the second characterizing data point to the abscissa of the first data point and the fourth connecting line, as a fourth vertical distance set, and when the maximum vertical distance in the fourth vertical distance set exceeds the calibration threshold, obtaining a point corresponding to the maximum vertical distance in the fourth vertical distance set as the fourth characterizing data point;

[0020] Taking the second characterization data point as a starting point and the first characterization data point as an end point, constructing a fifth connecting line, determining the absolute values ​​of the vertical distances between the remaining data points whose abscissa values ​​are within the range from the abscissa of the first characterization data point to the abscissa of the second characterization data point and the fifth connecting line, as a fifth vertical distance set, and when the maximum vertical distance in the fifth vertical distance set exceeds the calibration threshold, obtaining a point corresponding to the maximum vertical distance in the fifth vertical distance set as the fifth characterization data point;

[0021] Taking the third characterizing data point as a starting point and the Nth data point as an end point, constructing a sixth connecting line, determining the absolute values ​​of the vertical distances between the remaining data points whose abscissa values ​​are within the range from the abscissa of the third characterizing data point to the abscissa of the Nth data point and the sixth connecting line, as a sixth vertical distance set, and when the maximum vertical distance in the sixth vertical distance set exceeds the calibration threshold, obtaining a point corresponding to the maximum vertical distance in the sixth vertical distance set as the sixth characterizing data point;

[0022] Taking the third characterization data point as a starting point and the first characterization data point as an end point, constructing a seventh connecting line, determining the absolute values ​​of the vertical distances between the remaining data points whose abscissa values ​​are within the range from the abscissa of the third characterization data point to the abscissa of the first characterization data point and the seventh connecting line, as a seventh vertical distance set, and when the maximum vertical distance in the seventh vertical distance set exceeds the calibration threshold, obtaining a point corresponding to the maximum vertical distance in the seventh vertical distance set as the seventh characterization data point;

[0023] Step S2-4:

[0024] All characterizing data points are selected by continuously constructing connecting lines, calculating the vertical distances between data points and the connecting lines, determining the data points corresponding to the maximum vertical distances and making the maximum vertical distances exceed the calibration threshold value, until the vertical distances between all data points and the constructed connecting lines are no greater than the calibration threshold value.

[0025] According to the method of the first aspect of the present invention, in the step S3, calibrating the M characterization data points by means of amplitude compensation specifically includes: respectively calculating the absolute values ​​of the amplitudes of the M characterization data points to the zero point as the calibration amounts of the M characterization data points, and calibrating the M characterization data points to the zero point based on the calibration amounts of the M characterization data points, so that the amplitudes of the M characterization data points after amplitude compensation are attenuated to zero.

[0026] According to the method of the first aspect of the present invention, in step S3, determining the calibration amounts of the NM data points based on the calibration amounts of the M characterization data points specifically includes:

[0027] The first data point, the M characterization data points, and the Nth data point in the two-dimensional coordinate system are obtained as M+2 calibration points, and the average values ​​of the calibration amounts of two adjacent calibration points are calculated in order of the horizontal coordinates from small to large, and the absolute value from the average value to the zero point is used as the calibration amount of other data points between the two adjacent calibration points, thereby obtaining the calibration amounts of the NM data points.

[0028] According to the method of the first aspect of the present invention, in the step S3, calibrating the NM data points with the calibration amounts of the NM data points specifically includes: compensating the vertical coordinates of the NM data points based on the calibration amounts of the NM data points, so that the vertical distance of the NM data points from the zero point after amplitude compensation is not greater than the calibration threshold.

[0029] A second aspect of the present invention discloses a system for calibrating the frequency response of a spectrum analyzer. The system comprises:

[0030] A first processing unit is configured to intercept frequency response data to be calibrated from a radio frequency signal output by a spectrum analyzer, obtain a standard error threshold of the spectrum analyzer, and determine a calibration threshold based on the standard error threshold, wherein the calibration threshold is less than the standard error threshold;

[0031] A second processing unit is configured to mark N data points included in the frequency response data to be calibrated in a two-dimensional coordinate system, and select M characterization data points from the N data points based on the calibration threshold value, wherein the M characterization data points are used to characterize calibration amounts of NM data points other than the M characterization data points;

[0032] The horizontal axis of the two-dimensional coordinate system represents frequency, and the vertical axis represents amplitude. The horizontal axis of each data point in the N data points is the frequency value of the data point, and the vertical axis is the amplitude value of the data point.

[0033] The third processing unit is configured to calibrate the M characterization data points by means of amplitude compensation, determine the calibration amounts of the NM data points based on the calibration amounts of the M characterization data points, and calibrate the NM data points with the calibration amounts of the NM data points.

[0034] According to the system of the second aspect of the present invention, the first processing unit is specifically configured to intercept the frequency response data to be calibrated from the radio frequency signal output by the spectrum analyzer in the following manner: perform amplitude attenuation detection on the radio frequency signal output by the spectrum analyzer, and when continuous amplitude attenuation is detected within a specified time period and the attenuation amplitude exceeds an attenuation threshold, intercept a discrete signal exceeding the attenuation threshold within the specified time period as the frequency response data to be calibrated.

[0035] According to the system of the second aspect of the present invention, the standard error threshold is the factory configuration data of the spectrum analyzer, and the calibration threshold is 0.3-0.7 times the standard error threshold.

[0036] According to the system of the second aspect of the present invention, the second processing unit is specifically configured to select the M characterization data points from the N data points in the following manner:

[0037] Step S2-1:

[0038] Taking the first data point as the starting point and the Nth data point as the end point, constructing a first connecting line, determining the absolute values ​​of the vertical distances between the remaining data points whose horizontal coordinate values ​​are within the range from the horizontal coordinate of the first data point to the horizontal coordinate of the Nth data point and the first connecting line, as a first vertical distance set, and when the maximum vertical distance in the first vertical distance set exceeds the calibration threshold, obtaining the point corresponding to the maximum vertical distance in the first vertical distance set as the first characterization data point;

[0039] Step S2-2:

[0040] Taking the first characterizing data point as a starting point and the first data point as an end point, constructing a second connecting line, determining the absolute values ​​of the vertical distances between the remaining data points whose abscissa values ​​are within the range from the abscissa of the first characterizing data point to the abscissa of the first data point and the second connecting line, as a second vertical distance set, and when the maximum vertical distance in the second vertical distance set exceeds the calibration threshold, obtaining a point corresponding to the maximum vertical distance in the second vertical distance set as a second characterizing data point;

[0041] Taking the first characterizing data point as a starting point and the Nth data point as an end point, constructing a third connecting line, determining the absolute values ​​of the vertical distances between the remaining data points whose abscissa values ​​are within the range from the abscissa of the first characterizing data point to the abscissa of the Nth data point and the third connecting line, as a third vertical distance set, and when the maximum vertical distance in the third vertical distance set exceeds the calibration threshold, obtaining a point corresponding to the maximum vertical distance in the third vertical distance set as a third characterizing data point;

[0042] Step S2-3:

[0043] Taking the second characterizing data point as a starting point and the first data point as an end point, constructing a fourth connecting line, determining the absolute values ​​of the vertical distances between the remaining data points whose abscissa values ​​are within the range from the abscissa of the second characterizing data point to the abscissa of the first data point and the fourth connecting line, as a fourth vertical distance set, and when the maximum vertical distance in the fourth vertical distance set exceeds the calibration threshold, obtaining a point corresponding to the maximum vertical distance in the fourth vertical distance set as the fourth characterizing data point;

[0044] Taking the second characterization data point as a starting point and the first characterization data point as an end point, constructing a fifth connecting line, determining the absolute values ​​of the vertical distances between the remaining data points whose abscissa values ​​are within the range from the abscissa of the first characterization data point to the abscissa of the second characterization data point and the fifth connecting line, as a fifth vertical distance set, and when the maximum vertical distance in the fifth vertical distance set exceeds the calibration threshold, obtaining a point corresponding to the maximum vertical distance in the fifth vertical distance set as the fifth characterization data point;

[0045] Taking the third characterizing data point as a starting point and the Nth data point as an end point, constructing a sixth connecting line, determining the absolute values ​​of the vertical distances between the remaining data points whose abscissa values ​​are within the range from the abscissa of the third characterizing data point to the abscissa of the Nth data point and the sixth connecting line, as a sixth vertical distance set, and when the maximum vertical distance in the sixth vertical distance set exceeds the calibration threshold, obtaining a point corresponding to the maximum vertical distance in the sixth vertical distance set as the sixth characterizing data point;

[0046] Taking the third characterization data point as a starting point and the first characterization data point as an end point, constructing a seventh connecting line, determining the absolute values ​​of the vertical distances between the remaining data points whose abscissa values ​​are within the range from the abscissa of the third characterization data point to the abscissa of the first characterization data point and the seventh connecting line, as a seventh vertical distance set, and when the maximum vertical distance in the seventh vertical distance set exceeds the calibration threshold, obtaining a point corresponding to the maximum vertical distance in the seventh vertical distance set as the seventh characterization data point;

[0047] Step S2-4:

[0048] All characterizing data points are selected by continuously constructing connecting lines, calculating the vertical distances between data points and the connecting lines, determining the data points corresponding to the maximum vertical distances and making the maximum vertical distances exceed the calibration threshold value, until the vertical distances between all data points and the constructed connecting lines are no greater than the calibration threshold value.

[0049] According to the system of the second aspect of the present invention, the third processing unit is specifically configured to calibrate the M characterization data points by amplitude compensation in the following manner: respectively calculate the absolute values ​​of the amplitudes of the M characterization data points to the zero point as the calibration amounts of the M characterization data points, and calibrate the M characterization data points to the zero point based on the calibration amounts of the M characterization data points, so that the amplitude of the M characterization data points after amplitude compensation decays to zero.

[0050] According to the system of the second aspect of the present invention, the third processing unit is specifically configured to determine the calibration amounts of the NM data points in the following manner: obtain the first data point, the M characterization data points, and the Nth data point in the two-dimensional coordinate system as M+2 calibration points, and calculate the average values ​​of the calibration amounts of two adjacent calibration points in order of the horizontal coordinates from small to large, and use the absolute value from the average value to zero as the calibration amount of other data points between the two adjacent calibration points, thereby obtaining the calibration amounts of the NM data points.

[0051] According to the system of the second aspect of the present invention, the third processing unit is specifically configured to calibrate the NM data points in the following manner: calibrating the NM data points with the calibration amount of the NM data points specifically includes: compensating the vertical coordinates of the NM data points based on the calibration amount of the NM data points, so that the vertical distance of the NM data points from the zero point after amplitude compensation is not greater than the calibration threshold value.

[0052] The third aspect of the present invention discloses an electronic device, which includes a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the steps in the method for calibrating the frequency response of a spectrum analyzer described in the first aspect of the present invention are implemented.

[0053] The fourth aspect of the present invention discloses a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method for calibrating the frequency response of a spectrum analyzer described in the first aspect of the present invention.

[0054] The technical solution provided by the present invention significantly improves the efficiency of calibrating the spectrum analyzer and saves a lot of calculation cost and time cost. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0056] Figure 1 is a flow chart of a method for calibrating a frequency response of a spectrum analyzer according to an embodiment of the present invention;

[0057] Figure 2 A schematic diagram of selecting characterization data points according to an embodiment of the present invention;

[0058] Figure 3 is a structural diagram of a system for calibrating the frequency response of a spectrum analyzer according to an embodiment of the present invention;

[0059] Figure 4 The figure is a structural diagram of an electronic device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0060] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0061] A first aspect of the present invention discloses a method for calibrating the frequency response of a spectrum analyzer. Figure 1 FIG. 4 is a flow chart of a method for calibrating the frequency response of a spectrum analyzer according to an embodiment of the present invention; Figure 1 As shown, the method includes:

[0062] Step S1, intercepting frequency response data to be calibrated from a radio frequency signal output by a spectrum analyzer, and obtaining a standard error threshold of the spectrum analyzer, and determining a calibration threshold based on the standard error threshold, wherein the calibration threshold is less than the standard error threshold;

[0063] Step S2, marking N data points included in the frequency response data to be calibrated in a two-dimensional coordinate system, and selecting M characterization data points from the N data points based on the calibration threshold value, wherein the M characterization data points are used to characterize the calibration amounts of NM data points other than the M characterization data points;

[0064] The horizontal axis of the two-dimensional coordinate system represents frequency, and the vertical axis represents amplitude. The horizontal axis of each data point in the N data points is the frequency value of the data point, and the vertical axis is the amplitude value of the data point.

[0065] Step S3, calibrating the M characterization data points by means of amplitude compensation, determining the calibration amounts of the NM data points based on the calibration amounts of the M characterization data points, and calibrating the NM data points with the calibration amounts of the NM data points.

[0066] In step S1, frequency response data to be calibrated is intercepted from a radio frequency signal output by a spectrum analyzer, and a standard error threshold of the spectrum analyzer is obtained. A calibration threshold is determined based on the standard error threshold, and the calibration threshold is smaller than the standard error threshold.

[0067] Specifically, take the standard error threshold as 0.5 and the calibration threshold as 0.3*0.5, that is, 0.15, as an example.

[0068] In some embodiments, in step S1, intercepting the frequency response data to be calibrated from the RF signal output by the spectrum analyzer includes: performing amplitude attenuation detection on the RF signal output by the spectrum analyzer, and when continuous amplitude attenuation is detected within a specified time period and the attenuation amplitude exceeds an attenuation threshold, intercepting a discrete signal exceeding the attenuation threshold within the specified time period as the frequency response data to be calibrated.

[0069] Specifically, within the selected range of 20MHz-3800MHz, the signal source is set to have a frequency of F0=20M, and the spectrum analyzer will display the reading P0. Then the signal source and the spectrum analyzer are set in a 10MHz step cycle, and all frequencies and corresponding amplitude values ​​are recorded. The frequency value is recorded as Fn, and the amplitude value is recorded as Pn. Then, the original data of frequency vs amplitude at 378 points are obtained; this data is used as the standard input of step S2.

[0070] In step S2, N data points included in the frequency response data to be calibrated are marked in a two-dimensional coordinate system, and M characterization data points are selected from the N data points based on the calibration threshold value, and the M characterization data points are used to characterize the calibration amounts of NM data points other than the M characterization data points; wherein the horizontal axis of the two-dimensional coordinate system represents frequency, and the vertical axis represents amplitude, and the horizontal coordinate of each data point among the N data points is the frequency value of the data point, and the vertical coordinate is the amplitude value of the data point.

[0071] In some embodiments, in step S2, selecting the M characterization data points from the N data points based on the calibration threshold value specifically includes:

[0072] Step S2-1:

[0073] Taking the first data point as the starting point and the Nth data point as the end point, constructing a first connecting line, determining the absolute values ​​of the vertical distances between the remaining data points whose horizontal coordinate values ​​are within the range from the horizontal coordinate of the first data point to the horizontal coordinate of the Nth data point and the first connecting line, as a first vertical distance set, and when the maximum vertical distance in the first vertical distance set exceeds the calibration threshold, obtaining the point corresponding to the maximum vertical distance in the first vertical distance set as the first characterization data point;

[0074] Step S2-2:

[0075] Taking the first characterizing data point as a starting point and the first data point as an end point, constructing a second connecting line, determining the absolute values ​​of the vertical distances between the remaining data points whose abscissa values ​​are within the range from the abscissa of the first characterizing data point to the abscissa of the first data point and the second connecting line, as a second vertical distance set, and when the maximum vertical distance in the second vertical distance set exceeds the calibration threshold, obtaining a point corresponding to the maximum vertical distance in the second vertical distance set as a second characterizing data point;

[0076] Taking the first characterizing data point as a starting point and the Nth data point as an end point, constructing a third connecting line, determining the absolute values ​​of the vertical distances between the remaining data points whose abscissa values ​​are within the range from the abscissa of the first characterizing data point to the abscissa of the Nth data point and the third connecting line, as a third vertical distance set, and when the maximum vertical distance in the third vertical distance set exceeds the calibration threshold, obtaining a point corresponding to the maximum vertical distance in the third vertical distance set as a third characterizing data point;

[0077] Step S2-3:

[0078] Taking the second characterizing data point as a starting point and the first data point as an end point, constructing a fourth connecting line, determining the absolute values ​​of the vertical distances between the remaining data points whose abscissa values ​​are within the range from the abscissa of the second characterizing data point to the abscissa of the first data point and the fourth connecting line, as a fourth vertical distance set, and when the maximum vertical distance in the fourth vertical distance set exceeds the calibration threshold, obtaining a point corresponding to the maximum vertical distance in the fourth vertical distance set as the fourth characterizing data point;

[0079] Taking the second characterization data point as a starting point and the first characterization data point as an end point, constructing a fifth connecting line, determining the absolute values ​​of the vertical distances between the remaining data points whose abscissa values ​​are within the range from the abscissa of the first characterization data point to the abscissa of the second characterization data point and the fifth connecting line, as a fifth vertical distance set, and when the maximum vertical distance in the fifth vertical distance set exceeds the calibration threshold, obtaining a point corresponding to the maximum vertical distance in the fifth vertical distance set as the fifth characterization data point;

[0080] Taking the third characterizing data point as a starting point and the Nth data point as an end point, constructing a sixth connecting line, determining the absolute values ​​of the vertical distances between the remaining data points whose abscissa values ​​are within the range from the abscissa of the third characterizing data point to the abscissa of the Nth data point and the sixth connecting line, as a sixth vertical distance set, and when the maximum vertical distance in the sixth vertical distance set exceeds the calibration threshold, obtaining a point corresponding to the maximum vertical distance in the sixth vertical distance set as the sixth characterizing data point;

[0081] Taking the third characterization data point as a starting point and the first characterization data point as an end point, constructing a seventh connecting line, determining the absolute values ​​of the vertical distances between the remaining data points whose abscissa values ​​are within the range from the abscissa of the third characterization data point to the abscissa of the first characterization data point and the seventh connecting line, as a seventh vertical distance set, and when the maximum vertical distance in the seventh vertical distance set exceeds the calibration threshold, obtaining a point corresponding to the maximum vertical distance in the seventh vertical distance set as the seventh characterization data point;

[0082] Step S2-4:

[0083] All characterizing data points are selected by continuously constructing connecting lines, calculating the vertical distances between data points and the connecting lines, determining the data points corresponding to the maximum vertical distances and making the maximum vertical distances exceed the calibration threshold value, until the vertical distances between all data points and the constructed connecting lines are no greater than the calibration threshold value.

[0084] Figure 2 Schematic diagram of selecting characterization data points according to an embodiment of the present invention, as shown in Figure 2As shown, first, draw a two-point straight line between the first point and the last point of the frequency response data, set the threshold to 0.15, find the point P1 with the largest vertical distance, if it does not exceed the threshold range, the first point and the last point are used as the final two calibration points; if it exceeds the threshold range, then draw a connecting line between the first point and P1 of the original data, set the calibration point threshold to 0.15, find the point P2 with the largest vertical distance, draw a two-point straight line between P1 and the last point, set the calibration point threshold to 0.15, find the point P3 with the largest vertical distance; and repeat this cycle to find all calibration points (i.e., M characterization data points).

[0085] Figure 2 middle,

[0086] The dotted line (………) represents the original data;

[0087] Straight line (-) means to draw a straight line between the starting point and the end point, and find the point 1 that deviates the most from the straight line;

[0088] The short straight line (-----) means to draw a straight line between the starting point and point 1, find point 2 with the largest deviation from the straight line, draw a straight line between point 1 and the end point, find point 3 with the largest deviation from the straight line, and so on; the black dots represent: all calibration frequency points.

[0089] In step S3, the M characterization data points are calibrated by amplitude compensation, and the calibration amounts of the NM data points are determined based on the calibration amounts of the M characterization data points, and the NM data points are calibrated with the calibration amounts of the NM data points.

[0090] In some embodiments, in the step S3, calibrating the M characterization data points by means of amplitude compensation specifically includes: respectively calculating the absolute values ​​of the amplitudes of the M characterization data points to the zero point as the calibration amounts of the M characterization data points, and calibrating the M characterization data points to the zero point based on the calibration amounts of the M characterization data points, so that the amplitudes of the M characterization data points after amplitude compensation decay to zero.

[0091] In some embodiments, the calibration amounts of the NM data points are determined based on the calibration amounts of the M characterization data points, specifically including: obtaining the first data point, the M characterization data points, and the Nth data point in the two-dimensional coordinate system as M+2 calibration points, and calculating the average values ​​of the calibration amounts of two adjacent calibration points in order of the horizontal coordinates from small to large, and taking the absolute value from the average value to zero as the calibration amount of other data points between the two adjacent calibration points, thereby obtaining the calibration amounts of the NM data points.

[0092] In some embodiments, in the step S3, calibrating the NM data points with the calibration amounts of the NM data points specifically includes: compensating the vertical coordinates of the NM data points based on the calibration amounts of the NM data points, so that the vertical distance of the NM data points from the zero point after amplitude compensation is not greater than the calibration threshold.

[0093] Specifically, usually 20MHz-3800MHz, 10M steps are selected for calibration, there are 378 points (10 minutes), and after processing in step S3, there are only 45 points (1.2 minutes), and the calibration time is shortened to about 1 / 8 of the original time. Then, amplitude compensation processing is performed. For these 45 points, they are directly compensated to zero point. For other data points, the amplitudes of two adjacent calibration points are taken for calibration. After calibration, the vertical distances are all within 0.15 when tested with 10M steps. The calibration result meets expectations.

[0094] The improved effects of the method for calibrating the frequency response of a spectrum analyzer according to the first aspect of the present invention are described from the following four aspects:

[0095] 1. Comparison of calibration frequency points

[0096] Frequency range Original points Inflection point 20MHz-3800MHz 378 45

[0097] Table 1: Calibration points 2. Efficiency comparison

[0098] Frequency range Original calibration time Inflection point calibration time 20MHz-3800MHz 95 minutes(378) 12 minutes (45)

[0099] Table 2: Calibration time

[0100] 3. Production efficiency comparison

[0101] By comparing the time, the calibration time was reduced from 95 minutes to 12 minutes, and was shortened to about 1 / 8 of the original time.

[0102] 4. Performance index comparison

[0103] With 45 inflection points, after calibration, the test was performed with a step of 10M, all within 0.15, and the test results met the design and index requirements.

[0104] A second aspect of the present invention discloses a system for calibrating the frequency response of a spectrum analyzer. Figure 3 FIG. 4 is a structural diagram of a system for calibrating the frequency response of a spectrum analyzer according to an embodiment of the present invention; Figure 3 As shown, the system 300 includes:

[0105] The first processing unit 301 is configured to intercept frequency response data to be calibrated from the radio frequency signal output by the spectrum analyzer, and obtain a standard error threshold of the spectrum analyzer, and determine a calibration threshold based on the standard error threshold, wherein the calibration threshold is less than the standard error threshold;

[0106] The second processing unit 302 is configured to mark N data points included in the frequency response data to be calibrated in a two-dimensional coordinate system, and select M characterization data points from the N data points based on the calibration threshold value, wherein the M characterization data points are used to characterize calibration amounts of NM data points other than the M characterization data points;

[0107] The horizontal axis of the two-dimensional coordinate system represents frequency, and the vertical axis represents amplitude. The horizontal axis of each data point in the N data points is the frequency value of the data point, and the vertical axis is the amplitude value of the data point.

[0108] The third processing unit 303 is configured to calibrate the M characterization data points by amplitude compensation, determine the calibration amounts of the NM data points based on the calibration amounts of the M characterization data points, and calibrate the NM data points with the calibration amounts of the NM data points.

[0109] According to the system of the second aspect of the present invention, the first processing unit 301 is specifically configured to intercept the frequency response data to be calibrated from the radio frequency signal output by the spectrum analyzer in the following manner: perform amplitude attenuation detection on the radio frequency signal output by the spectrum analyzer, and when continuous amplitude attenuation is detected within a specified time period and the attenuation amplitude exceeds an attenuation threshold, intercept a discrete signal exceeding the attenuation threshold within the specified time period as the frequency response data to be calibrated.

[0110] According to the system of the second aspect of the present invention, the standard error threshold is the factory configuration data of the spectrum analyzer, and the calibration threshold is 0.3-0.7 times the standard error threshold.

[0111] According to the system of the second aspect of the present invention, the second processing unit 302 is specifically configured to select the M representative data points from the N data points in the following manner:

[0112] Step S2-1:

[0113] Taking the first data point as the starting point and the Nth data point as the end point, constructing a first connecting line, determining the absolute values ​​of the vertical distances between the remaining data points whose horizontal coordinate values ​​are within the range from the horizontal coordinate of the first data point to the horizontal coordinate of the Nth data point and the first connecting line, as a first vertical distance set, and when the maximum vertical distance in the first vertical distance set exceeds the calibration threshold, obtaining the point corresponding to the maximum vertical distance in the first vertical distance set as the first characterization data point;

[0114] Step S2-2:

[0115] Taking the first characterizing data point as a starting point and the first data point as an end point, constructing a second connecting line, determining the absolute values ​​of the vertical distances between the remaining data points whose abscissa values ​​are within the range from the abscissa of the first characterizing data point to the abscissa of the first data point and the second connecting line, as a second vertical distance set, and when the maximum vertical distance in the second vertical distance set exceeds the calibration threshold, obtaining a point corresponding to the maximum vertical distance in the second vertical distance set as a second characterizing data point;

[0116] Taking the first characterizing data point as a starting point and the Nth data point as an end point, constructing a third connecting line, determining the absolute values ​​of the vertical distances between the remaining data points whose abscissa values ​​are within the range from the abscissa of the first characterizing data point to the abscissa of the Nth data point and the third connecting line, as a third vertical distance set, and when the maximum vertical distance in the third vertical distance set exceeds the calibration threshold, obtaining a point corresponding to the maximum vertical distance in the third vertical distance set as a third characterizing data point;

[0117] Step S2-3:

[0118] Taking the second characterizing data point as a starting point and the first data point as an end point, constructing a fourth connecting line, determining the absolute values ​​of the vertical distances between the remaining data points whose abscissa values ​​are within the range from the abscissa of the second characterizing data point to the abscissa of the first data point and the fourth connecting line, as a fourth vertical distance set, and when the maximum vertical distance in the fourth vertical distance set exceeds the calibration threshold, obtaining a point corresponding to the maximum vertical distance in the fourth vertical distance set as the fourth characterizing data point;

[0119] Taking the second characterization data point as a starting point and the first characterization data point as an end point, constructing a fifth connecting line, determining the absolute values ​​of the vertical distances between the remaining data points whose abscissa values ​​are within the range from the abscissa of the first characterization data point to the abscissa of the second characterization data point and the fifth connecting line, as a fifth vertical distance set, and when the maximum vertical distance in the fifth vertical distance set exceeds the calibration threshold, obtaining a point corresponding to the maximum vertical distance in the fifth vertical distance set as the fifth characterization data point;

[0120] Taking the third characterizing data point as a starting point and the Nth data point as an end point, constructing a sixth connecting line, determining the absolute values ​​of the vertical distances between the remaining data points whose abscissa values ​​are within the range from the abscissa of the third characterizing data point to the abscissa of the Nth data point and the sixth connecting line, as a sixth vertical distance set, and when the maximum vertical distance in the sixth vertical distance set exceeds the calibration threshold, obtaining a point corresponding to the maximum vertical distance in the sixth vertical distance set as the sixth characterizing data point;

[0121] Taking the third characterization data point as a starting point and the first characterization data point as an end point, constructing a seventh connecting line, determining the absolute values ​​of the vertical distances between the remaining data points whose abscissa values ​​are within the range from the abscissa of the third characterization data point to the abscissa of the first characterization data point and the seventh connecting line, as a seventh vertical distance set, and when the maximum vertical distance in the seventh vertical distance set exceeds the calibration threshold, obtaining a point corresponding to the maximum vertical distance in the seventh vertical distance set as the seventh characterization data point;

[0122] Step S2-4:

[0123] All characterizing data points are selected by continuously constructing connecting lines, calculating the vertical distances between data points and the connecting lines, determining the data points corresponding to the maximum vertical distances and making the maximum vertical distances exceed the calibration threshold value, until the vertical distances between all data points and the constructed connecting lines are no greater than the calibration threshold value.

[0124] According to the system of the second aspect of the present invention, the third processing unit 303 is specifically configured to calibrate the M characterization data points by amplitude compensation in the following manner: respectively calculate the absolute values ​​of the amplitudes of the M characterization data points to the zero point as the calibration amounts of the M characterization data points, and calibrate the M characterization data points to the zero point based on the calibration amounts of the M characterization data points, so that the amplitudes of the M characterization data points after amplitude compensation are attenuated to zero.

[0125] According to the system of the second aspect of the present invention, the third processing unit 303 is specifically configured to determine the calibration amounts of the NM data points in the following manner: obtain the first data point, the M characterization data points, and the Nth data point in the two-dimensional coordinate system as M+2 calibration points, and calculate the average values ​​of the calibration amounts of two adjacent calibration points in order of the horizontal coordinates from small to large, and use the absolute value from the average value to zero as the calibration amount of other data points between the two adjacent calibration points, thereby obtaining the calibration amounts of the NM data points.

[0126] According to the system of the second aspect of the present invention, the third processing unit 303 is specifically configured to calibrate the NM data points in the following manner: calibrating the NM data points with the calibration amount of the NM data points specifically includes: compensating the vertical coordinates of the NM data points based on the calibration amount of the NM data points, so that the vertical distance of the NM data points from the zero point after amplitude compensation is not greater than the calibration threshold.

[0127] The third aspect of the present invention discloses an electronic device, which includes a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the steps in the method for calibrating the frequency response of a spectrum analyzer described in the first aspect of the present invention are implemented.

[0128] Figure 4 is a structural diagram of an electronic device according to an embodiment of the present invention; Figure 4 As shown, the electronic device includes a processor, a memory, a communication interface, a display screen and an input device connected via a system bus. Among them, the processor of the electronic device is used to provide computing and control capabilities. The memory of the electronic device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the electronic device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, an operator network, near field communication (NFC) or other technologies. The display screen of the electronic device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the electronic device can be a touch layer covered on the display screen, or a button, a trackball or a touch pad set on the housing of the electronic device, or an external keyboard, touch pad or mouse, etc.

[0129] Those skilled in the art will understand that Figure 4The structure shown in the figure is only a structural diagram of the part related to the technical solution of the present disclosure, and does not constitute a limitation on the electronic device to which the technical solution of the present application is applied. The specific electronic device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0130] The fourth aspect of the present invention discloses a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method for calibrating the frequency response of a spectrum analyzer described in the first aspect of the present invention.

[0131] In summary, the technical solution of the present invention has the following technical effects:

[0132] The technical solution of the invention is actually applied to the amplitude calibration compensation of the spectrum analyzer. The traditional calibration method adopts the method of taking steps to perform amplitude compensation on each frequency point obtained in the calibration frequency band in turn. In order to achieve a better calibration effect, a smaller step is usually selected to obtain the calibration frequency point, which will result in a longer calibration time and extremely low efficiency. The technical solution of the present invention has great advantages in improving efficiency. Through this calibration method, a large number of unnecessary calibration frequency points can be reduced, and the calibration time can be greatly shortened while maintaining the calibration effect, saving a lot of time cost. This technical solution has been applied to the actual amplitude calibration production of spectrum analyzers. The actual results prove that this solution is completely feasible and the calibration results are reliable. The technical solution of the present invention is practical and creative, and can be widely used in the amplitude calibration compensation of spectrum analyzers.

[0133] Please note that the technical features of the above embodiments can be combined arbitrarily. In order to make the description concise, all possible combinations of the technical features in the above embodiments are not described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification. The above-mentioned embodiments only express several implementation methods of the present application, and their descriptions are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that for ordinary technicians in this field, without departing from the concept of the present application, several variations and improvements can be made, which all belong to the scope of protection of the present application. Therefore, the scope of protection of the patent in this application shall be based on the attached claims.

Claims

1. A method for calibrating the frequency response of a spectrum analyzer, characterized in that: The method comprises: Step S1, intercepting frequency response data to be calibrated from a radio frequency signal output by a spectrum analyzer, and obtaining a standard error threshold of the spectrum analyzer, and determining a calibration threshold based on the standard error threshold, wherein the calibration threshold is less than the standard error threshold; Step S2, marking N data points included in the frequency response data to be calibrated in a two-dimensional coordinate system, and selecting M characterization data points from the N data points based on the calibration threshold value, wherein the M characterization data points are used to characterize the calibration amounts of NM data points other than the M characterization data points; The horizontal axis of the two-dimensional coordinate system represents frequency, and the vertical axis represents amplitude. The horizontal axis of each data point in the N data points is the frequency value of the data point, and the vertical axis is the amplitude value of the data point. Step S3, calibrating the M characterization data points by means of amplitude compensation, determining calibration amounts of the NM data points based on the calibration amounts of the M characterization data points, and calibrating the NM data points with the calibration amounts of the NM data points; In the step S3, calibrating the M characterization data points by means of amplitude compensation specifically includes: respectively calculating the absolute values ​​of the amplitudes of the M characterization data points to the zero point as the calibration amounts of the M characterization data points, and calibrating the M characterization data points to the zero point based on the calibration amounts of the M characterization data points, so that the amplitudes of the M characterization data points after amplitude compensation are attenuated to zero; In the step S3, the calibration amounts of the NM data points are determined based on the calibration amounts of the M characterization data points, specifically comprising: obtaining the first data point, the M characterization data points, and the Nth data point in the two-dimensional coordinate system as M+2 calibration points, and calculating the average values ​​of the calibration amounts of two adjacent calibration points in order of the horizontal coordinates from small to large, and taking the absolute value from the average value to the zero point as the calibration amount of other data points between the two adjacent calibration points, thereby obtaining the calibration amounts of the NM data points; In the step S3, calibrating the NM data points with the calibration amounts of the NM data points specifically includes: compensating the vertical coordinates of the NM data points based on the calibration amounts of the NM data points, so that the vertical distance of the NM data points from the zero point after amplitude compensation is not greater than the calibration threshold.

2. A method for calibrating the frequency response of a spectrum analyzer according to claim 1, characterized in that: In the step S1, intercepting the frequency response data to be calibrated from the RF signal output by the spectrum analyzer includes: performing amplitude attenuation detection on the RF signal output by the spectrum analyzer, and when continuous amplitude attenuation is detected within a specified time period and the attenuation amplitude exceeds an attenuation threshold, intercepting a discrete signal exceeding the attenuation threshold within the specified time period as the frequency response data to be calibrated.

3. A method for calibrating the frequency response of a spectrum analyzer according to claim 2, characterized in that: In the step S1, the standard error threshold is the factory configuration data of the spectrum analyzer, and the calibration threshold is 0.3-0.7 times the standard error threshold.

4. A method for calibrating the frequency response of a spectrum analyzer according to claim 2, characterized in that: In the step S2, selecting the M characterization data points from the N data points based on the calibration threshold value specifically includes: Step S2-1: Taking the first data point as the starting point and the Nth data point as the end point, constructing a first connecting line, determining the absolute values ​​of the vertical distances between the remaining data points whose horizontal coordinate values ​​are within the range from the horizontal coordinate of the first data point to the horizontal coordinate of the Nth data point and the first connecting line, as a first vertical distance set, and when the maximum vertical distance in the first vertical distance set exceeds the calibration threshold, obtaining the point corresponding to the maximum vertical distance in the first vertical distance set as the first characterization data point; Step S2-2: Taking the first characterizing data point as a starting point and the first data point as an end point, constructing a second connecting line, determining the absolute values ​​of the vertical distances between the remaining data points whose abscissa values ​​are within the range from the abscissa of the first characterizing data point to the abscissa of the first data point and the second connecting line, as a second vertical distance set, and when the maximum vertical distance in the second vertical distance set exceeds the calibration threshold, obtaining a point corresponding to the maximum vertical distance in the second vertical distance set as a second characterizing data point; Taking the first characterizing data point as a starting point and the Nth data point as an end point, constructing a third connecting line, determining the absolute values ​​of the vertical distances between the remaining data points whose abscissa values ​​are within the range from the abscissa of the first characterizing data point to the abscissa of the Nth data point and the third connecting line, as a third vertical distance set, and when the maximum vertical distance in the third vertical distance set exceeds the calibration threshold, obtaining a point corresponding to the maximum vertical distance in the third vertical distance set as a third characterizing data point; Step S2-3: Taking the second characterizing data point as a starting point and the first data point as an end point, constructing a fourth connecting line, determining the absolute values ​​of the vertical distances between the remaining data points whose abscissa values ​​are within the range from the abscissa of the second characterizing data point to the abscissa of the first data point and the fourth connecting line, as a fourth vertical distance set, and when the maximum vertical distance in the fourth vertical distance set exceeds the calibration threshold, obtaining a point corresponding to the maximum vertical distance in the fourth vertical distance set as the fourth characterizing data point; Taking the second characterization data point as a starting point and the first characterization data point as an end point, constructing a fifth connecting line, determining the absolute values ​​of the vertical distances between the remaining data points whose abscissa values ​​are within the range from the abscissa of the first characterization data point to the abscissa of the second characterization data point and the fifth connecting line, as a fifth vertical distance set, and when the maximum vertical distance in the fifth vertical distance set exceeds the calibration threshold, obtaining a point corresponding to the maximum vertical distance in the fifth vertical distance set as the fifth characterization data point; Taking the third characterizing data point as a starting point and the Nth data point as an end point, constructing a sixth connecting line, determining the absolute values ​​of the vertical distances between the remaining data points whose abscissa values ​​are within the range from the abscissa of the third characterizing data point to the abscissa of the Nth data point and the sixth connecting line, as a sixth vertical distance set, and when the maximum vertical distance in the sixth vertical distance set exceeds the calibration threshold, obtaining a point corresponding to the maximum vertical distance in the sixth vertical distance set as the sixth characterizing data point; Taking the third characterization data point as a starting point and the first characterization data point as an end point, constructing a seventh connecting line, determining the absolute values ​​of the vertical distances between the remaining data points whose abscissa values ​​are within the range from the abscissa of the third characterization data point to the abscissa of the first characterization data point and the seventh connecting line, as a seventh vertical distance set, and when the maximum vertical distance in the seventh vertical distance set exceeds the calibration threshold, obtaining a point corresponding to the maximum vertical distance in the seventh vertical distance set as the seventh characterization data point; Step S2-4: All characterizing data points are selected by continuously constructing connecting lines, calculating the vertical distances between data points and the connecting lines, determining the data points corresponding to the maximum vertical distances and making the maximum vertical distances exceed the calibration threshold value, until the vertical distances between all data points and the constructed connecting lines are no greater than the calibration threshold value.

5. A system for calibrating the frequency response of a spectrum analyzer, characterized in that: The system comprises: A first processing unit is configured to intercept frequency response data to be calibrated from a radio frequency signal output by a spectrum analyzer, obtain a standard error threshold of the spectrum analyzer, and determine a calibration threshold based on the standard error threshold, wherein the calibration threshold is less than the standard error threshold; A second processing unit is configured to mark N data points included in the frequency response data to be calibrated in a two-dimensional coordinate system, and select M characterization data points from the N data points based on the calibration threshold value, wherein the M characterization data points are used to characterize calibration amounts of NM data points other than the M characterization data points; The horizontal axis of the two-dimensional coordinate system represents frequency, and the vertical axis represents amplitude. The horizontal axis of each data point in the N data points is the frequency value of the data point, and the vertical axis is the amplitude value of the data point. a third processing unit, configured to calibrate the M characterization data points by amplitude compensation, determine calibration amounts of the NM data points based on the calibration amounts of the M characterization data points, and calibrate the NM data points with the calibration amounts of the NM data points; Among them, calibrating the M characterization data points by means of amplitude compensation specifically includes: respectively calculating the absolute values ​​of the amplitudes of the M characterization data points to the zero point as the calibration amounts of the M characterization data points, and calibrating the M characterization data points to the zero point based on the calibration amounts of the M characterization data points, so that the amplitudes of the M characterization data points after amplitude compensation are attenuated to zero; Wherein, determining the calibration amounts of the NM data points based on the calibration amounts of the M characterization data points specifically includes: obtaining the first data point, the M characterization data points, and the Nth data point in the two-dimensional coordinate system as M+2 calibration points, and calculating the average values ​​of the calibration amounts of two adjacent calibration points in order of the horizontal coordinates from small to large, and taking the absolute value from the average value to the zero point as the calibration amount of other data points between the two adjacent calibration points, thereby obtaining the calibration amounts of the NM data points; Among them, calibrating the NM data points with the calibration amounts of the NM data points specifically includes: compensating the vertical coordinates of the NM data points based on the calibration amounts of the NM data points, so that the vertical distance of the NM data points from the zero point after amplitude compensation is not greater than the calibration threshold.

6. An electronic device, characterized in that: The electronic device comprises a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the steps in the method for calibrating the frequency response of a spectrum analyzer according to any one of claims 1 to 4 are implemented.

7. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps in the method for calibrating the frequency response of a spectrum analyzer according to any one of claims 1 to 4 are implemented.

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