CN109239634A - The method of Two-port netwerk vector network analyzer calibration based on ridge regression - Google Patents
The method of Two-port netwerk vector network analyzer calibration based on ridge regression Download PDFInfo
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Abstract
The present invention provides a kind of method of Two-port netwerk vector network analyzer calibration based on ridge regression, include the following steps: S1,12 error models are established, the first analytic expression between the true value of the scattering parameter of Two-port netwerk vector network analyzer and 12 errors and the measured value of scattering parameter is obtained；S2, establish single port error model, the second analytic expression between the true value of the scattering parameter of Two-port netwerk vector network analyzer and 12 errors and the measured value of scattering parameter is obtained, ridge regression algorithm is respectively adopted to two ports and is calibrated, obtains the value of all 12 errors；S3, the measured value of the value of obtain 12 errors and scattering parameter is substituted into first analytic expression, obtain the true value of scattering parameter, 12 errors refer to effective directivity forward and backward error, isolation forward and backward error, equivalent source mismatch forward and backward error, equivalent matched load mismatch forward and backward error, transmission tracking forward and backward error, reflection tracking forward and backward error.
Description
Technical field
The present invention relates to the sides that vector network analyzer field more particularly to a kind of Two-port netwerk vector network analyzer are calibrated
Method.
Background technique
Vector network analyzer is a kind of for measuring the instrument of microwave network parameters comprehensively, is widely used in element system
It makes, aerospace, the fields such as microwave communication and experimental teaching, the multimeter on the frequency microwave field circle that is known as.But by
In vector network analyzer self structure and measurement characteristic the reason of, in measurement process generate error be inevitable,
If expecting really and accurately measurement data, it is necessary to which its error is analyzed and calibrated.
Presently, there are be the SOLT based on 12 errors for the mainstream calibration method of dual-port vector network analyzer
Classical calibration method, but this method can still be led to the problem of in the actual measurement of two-port network, be joined particularly with reflection
Several measurement errors is larger, by measured value after the SOLT calibration method of 12 errors with calibrated by Electronic Calibration part after it is right
There is certain difference in the measured value of same part to be measured, effect is unsatisfactory.More complicated Microwave Net mould is introduced by bringing into
Although type can promote calibration effect, algorithm is complicated, and time-consuming for calculating, is unfavorable for practical application.
Summary of the invention
In order to overcome at least one aspect of the above problem, the embodiment of the present invention provides a kind of Two-port netwerk based on ridge regression
The method of vector network analyzer calibration, includes the following steps: S1, establishes 12 error models, obtain Two-port netwerk vector network
The first analytic expression between the true value of the scattering parameter of analyzer and 12 errors and the measured value of scattering parameter；S2 is established
Single port error model obtains true value and 12 errors and the scattering of the scattering parameter of Two-port netwerk vector network analyzer
The second analytic expression between the measured value of parameter is respectively adopted ridge regression algorithm to two ports and calibrates, and obtains whole 12
The value of item error；The measured value of the value of obtain 12 errors and scattering parameter is substituted into first analytic expression, is obtained by S3
The true value of scattering parameter, wherein 12 errors refer to effective directivity forward error, effective directivity backward error,
Isolation forward error, isolation backward error, equivalent source mismatch forward error, equivalent source mismatch backward error, equivalent matched
Load mismatch forward error, equivalent matched load mismatch backward error, transmission tracking forward error, transmission tracking backward error,
Reflection tracking forward error and reflection tracking backward error.
According to some embodiments, first analytic expression is as follows:
Wherein,S11X、S22X、
S21X、S12XRespectively indicate scattering parameter S11、S22、S21、S12True value, S11M、S22M、S21M、S12MRespectively indicate scattering parameter
S11、S22、S21、S12Measured value, EDFIndicate effective directivity forward error, EDRIndicate effective directivity backward error, EXFTable
Show isolation forward error, EXRIndicate isolation backward error, ESFIndicate equivalent source mismatch forward error, ESRIndicate equivalent source
Mismatch backward error, ELFIndicate equivalent matched load mismatch forward error, ELRExpression equivalent matched load mismatch backward error,
ETFIndicate transmission tracking forward error, ETRIndicate transmission tracking backward error, ERFIndicate reflection tracking forward error and ERRTable
Show reflection tracking backward error.
According to some embodiments, step S2 includes S21, establishes single port error model, obtains Two-port netwerk vector network point
The second analytic expression between the true value of the scattering parameter of analyzer and 12 errors and the measured value of scattering parameter；S22, to first
Port is respectively connected to open circuit calibration component, short-circuit calibration component and load calibration part, three groups of data is obtained, to three groups of data applications
Ridge regression algorithm is fitted；S23 repeats step S22 to second port, obtains the value of reflection error in 12 errors；
S24, by measuring transmission and isolation parameters between the first port and the second port, in conjunction with the reflection error
Value determines the value that error is transmitted in 12 errors.
According to some embodiments, step S24 includes S241, removes low-pass filter, connects matched load and surveys configured transmission S21
And S12, respectively obtain measured value M1 and M4；S242, the first port are connected to the second port, survey configured transmission respectively
S21、S12With reflection parameters S11、S22, respectively obtain measured value M2, M5 and M3, M6；S243, in conjunction with the measured value and described 12
Reflection error in item error obtains the value of residual error in 12 errors.
According to some embodiments, ridge regression algorithm is fitted with following formula:
Wherein, λ is slightly over 0.1 constant, SX1、SX2And SX3It is true value, SM1、SM2And SM3Respectively access open circuit
The measured value of calibration component, short-circuit calibration component and matched load calibration component, S when accessing open circuit calibration componentX1=1, access short circuit calibration
S when partX2=-1, S when accessing matched load calibration componentX3=0, EDFIndicate effective directivity forward error, ESFIndicate that equivalent source is lost
With forward error, ERFIndicate reflection tracking forward error, i is imaginary unit.
Compared with prior art, the invention has the following advantages that ridge regression algorithm is introduced into calibration process by the present invention, and
It is not apparent from increase algorithm complexity, has reached more accurate calibration effect compared to 12 ERROR ALGORITHMs of tradition.The present invention with draw
Enter complicated network algorithm to compare, there is comparable accuracy, but more simplify practical.
Detailed description of the invention
By the description made for the present invention of below with reference to attached drawing, other objects and advantages of the present invention will be aobvious and easy
See, and can help that complete understanding of the invention will be obtained.
Fig. 1 is the work flow diagram of one embodiment of the invention；
Fig. 2 is 12 error model schematic diagrames of dual-port of one embodiment of the invention；
Fig. 3 is the single port error model schematic diagram of one embodiment of the invention；
Fig. 4 A is the scattering parameter S of the embodiment of the present invention and Electronic Calibration part for 1 port transmitting in Fig. 211Calibration effect
Fruit comparison diagram；
Fig. 4 B is the scattering parameter S of the embodiment of the present invention and Electronic Calibration part for 1 port transmitting in Fig. 221Calibration effect
Fruit comparison diagram；
Fig. 4 C is the scattering parameter S of the embodiment of the present invention and Electronic Calibration part for 1 port transmitting in Fig. 212Calibration effect
Fruit comparison diagram；
Fig. 4 D is the scattering parameter S of the embodiment of the present invention and Electronic Calibration part for 1 port transmitting in Fig. 222Calibration effect
Fruit comparison diagram.
Specific embodiment
In order to make the object, technical scheme and advantages of the embodiment of the invention clearer, below in conjunction with the embodiment of the present invention
In attached drawing, technical scheme in the embodiment of the invention is clearly and completely described, it is clear that described embodiment is
A part of the embodiment of the present invention, instead of all the embodiments.Based on the embodiments of the present invention, those of ordinary skill in the art
Every other embodiment obtained without making creative work, shall fall within the protection scope of the present invention.
The term used in embodiments of the present invention is only to be not intended to be limiting merely for for the purpose of describing particular embodiments
The present invention.Unless otherwise defined, the technical term or scientific term that the present invention uses should be tool in fields of the present invention
The ordinary meaning for thering is the personage of general technical ability to be understood.
The present invention provides a kind of method of Two-port netwerk vector network analyzer calibration based on ridge regression, and this method passes through ridge
The least square method of recurrence combines the SOLT calibration method of 12 traditional errors, is being not apparent from the case where increasing algorithm complexity
Under, substantially increase the accuracy of calibration.
Fig. 1 is work flow diagram according to an embodiment of the invention.As shown in Figure 1, the embodiment of the present invention includes as follows
Step:
S1 establishes 12 error models, obtain the scattering parameter of Two-port netwerk vector network analyzer true value and 12
The first analytic expression between error and the measured value of scattering parameter.
When excitation port difference, error model is divided into forward error model and backward error model.Therefore, 12 errors point
It Wei not effective directivity forward error EDF, effective directivity backward error EDR, isolation forward error EXF, after isolation to accidentally
Poor EXR, equivalent source mismatch forward error ESF, equivalent source mismatch backward error ESR, equivalent matched load mismatch forward error ELF, etc.
Imitate matched load mismatch backward error ELR, transmission tracking forward error ETF, transmission tracking backward error ETR, before reflection tracking to
Error ERFWith reflection tracking backward error ERR.12 errors are further divided into reflection error and transmission error.Reflection error can be with
It is effective directivity error, equivalent source mismatch error and reflection tracking error；Transmission error can be isolation error, equivalent
With load mismatch error and transmission tracking error.
Scattering parameter includes S11、S22、S12And S21, S11For input reflection coefficient, i.e. input return loss；S22It is anti-to export
Coefficient is penetrated, i.e. output return loss；S12For reverse transfer coefficient, that is, it is isolated；S21For positive transmission coefficient, i.e. gain.S11X、
S22X、S12XAnd S21XFor the true value of scattering parameter, S11M、S22M、S12MAnd S21MFor the not calibrated direct measurement of scattering parameter
Value.
Fig. 2 is 12 error model schematic diagrames of dual-port according to an embodiment of the invention.According to Fig.2, and
In conjunction with Mason rule, it can be deduced that the true value of the scattering parameter of Two-port netwerk vector network analyzer and 12 errors and scattering
The first analytic expression between the measured value of parameter, the first analytic expression are as follows:
Wherein,
S2 establishes single port error model, obtains true value and the institute of the scattering parameter of Two-port netwerk vector network analyzer
The second analytic expression between 12 errors and the measured value of scattering parameter is stated, ridge regression algorithm is respectively adopted to two ports and is carried out
Calibration obtains the value of all 12 errors.
Fig. 3 is single port error model schematic diagram according to an embodiment of the invention.As shown in figure 3, with first port
For propagated forward, EDFor effective directivity error, ESFor equivalent source mismatch error, ERFor reflection tracking error.According to Fig. 3 and
Mason formula can determine true value and 12 errors and the scattering of the scattering parameter of Two-port netwerk vector network analyzer
The second analytic expression between the measured value of parameter, directional error is denoted as E hereDF, reflection tracking error is denoted as ERF, source mismatch
Error is denoted as ESF.One of them in second analytic expression is as follows:
For the ease of calculating later, following formula can be deformed into:
S11M=EDF-(EDFESF-ERF)S11X+ESFS11MS11X
Similar, available S22M、S12MAnd S21MAnalytic expression.
Then, the reflection error of single port is calibrated, is respectively connected to open circuit calibration component, short-circuit calibration component and load school
Quasi- part, available three groups of data are fitted this three groups of data using ridge regression algorithm.In some embodiments it is possible to
Using following formula three groups of data are carried out with the fitting of ridge regression:
Wherein, λ is the constant greater than 0.1, and λ is slightly larger than 0.1 under normal circumstances, and the specific value of different instruments may not
Together, such as λ=0.101 can be taken；SX1、SX2And SX3It is true value, SM1、SM2And SM3Respectively access open circuit calibration component, short
The measured value of road calibration component and matched load calibration component, S when accessing open circuit calibration componentX1=1, S when accessing short-circuit calibration componentX2=-
1, S when accessing matched load calibration componentX3=0, EDF、ESFAnd ERF12 errors are belonged to, i is imaginary unit, i2=-1.
First port and second port are operated respectively, according to two groups of fittings as a result, useful direction can be solved
Property forward error EDF, effective directivity backward error EDR, equivalent source mismatch forward error ESF, equivalent source mismatch backward error ESR、
Reflection tracking forward error ERFWith reflection tracking backward error ERR。
It is then possible to be calibrated to transmission error, it that is to say and the error in transmission process is calibrated.Pass through measurement
Transmission determines the error in transmission process with isolation parameters between first port and second port, and detailed process is as follows:
(1) low-pass filter is removed, matched load is connect and surveys configured transmission S21And S12, respectively obtain measured value M1 and M4.This
Low-pass filter in embodiment can be 575M low-pass filter (DUT), certainly, in other examples, low-pass filtering
Device can be other models.
Because of S11x=S22X=S12X=S21X=0, so M1=EXF；M4=EXR。
(2) first port is connected to the second port, surveys configured transmission S respectively21、S12With reflection parameters S11、
S22, respectively obtain measured value M2, M5 and M3, M6.
Because of S11X=S22X=0, S12X=S21X=1；So
The above analytic expression of simultaneous, available:
EXF=M1
ETF=(M2-M1)(1-ESFELF)
EXR=M4
ETR=(M5-M4)(1-ESRELR)
6 measured values M1, M2, M3, M4, M5 and M6 and effective directivity forward error EDF, effective directivity backward error
EDR, equivalent source mismatch forward error ESF, equivalent source mismatch backward error ESR, reflection tracking forward error ERFAfter reflection tracking
To error ERRIt is it is known that so far, all 12 errors can be acquired.
The measured value of the value of obtain 12 errors and scattering parameter is substituted into first analytic expression, is dissipated by S3
Penetrate the true value of parameter.
The E that will be obtained by above formulaXF、ELF、ETF、EXR、ELRAnd ETRAnd the E obtained beforeDF、EDR、ESF、ESR、ERFWith
ERRAll for such as entering in the first analytic expression, the true value by calibration can be obtained.With 575M low-pass filter in the present embodiment
For, Fig. 4 A, Fig. 4 B, Fig. 4 C and Fig. 4 D respectively show the embodiment of the present invention and Electronic Calibration part and emit for 1 port in Fig. 2
Scattering parameter S11、S21、S12And S22Calibration Contrast on effect, the E-cal accurate calibration in figure is the calibration of Electronic Calibration part.
Fig. 4 A, Fig. 4 B, abscissa all indicates frequency in Fig. 4 C and Fig. 4 D, and ordinate respectively indicates scattering parameter S11、S21、S12And S22's
Value, scattering parameter S11、S21、S12And S22Value between [- 1,1].It can be seen from the figure that the present embodiment and accurately electricity
The result of sub- calibration component calibration is almost consistent, illustrates that the present embodiment can achieve calibration effect well.
Least square method based on ridge regression is introduced into calibration process by the present invention, increases algorithm complexity being not apparent from
In the case of, substantially increase the calibration result of the scattering parameter of Two-port netwerk vector network analyzer.
Finally, it should be noted that the above embodiments are merely illustrative of the technical solutions of the present invention, rather than its limitations；Although
Present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that: it still may be used
To modify the technical solutions described in the foregoing embodiments or equivalent replacement of some of the technical features；
And these are modified or replaceed, technical solution of various embodiments of the present invention that it does not separate the essence of the corresponding technical solution spirit and
Range.
Claims (5)
1. a kind of method of the Two-port netwerk vector network analyzer calibration based on ridge regression, which comprises the steps of:
S1 establishes 12 error models, obtains the true value and 12 errors of the scattering parameter of Two-port netwerk vector network analyzer
The first analytic expression between the measured value of scattering parameter；
S2 establishes single port error model, obtains the true value and described 12 of the scattering parameter of Two-port netwerk vector network analyzer
Two ports are respectively adopted ridge regression algorithm and carry out school by the second analytic expression between item error and the measured value of scattering parameter
Standard obtains the value of all 12 errors；
S3 substitutes into the measured value of the value of obtain 12 errors and scattering parameter in first analytic expression, obtains scattering ginseng
Several true values,
Wherein, 12 errors refer to before effective directivity forward error, effective directivity backward error, isolation to accidentally
Before difference, isolation backward error, equivalent source mismatch forward error, equivalent source mismatch backward error, equivalent matched load mismatch to
Error, equivalent matched load mismatch backward error, transmission tracking forward error, transmission tracking backward error, before reflection tracking to
Error and reflection tracking backward error.
2. the method according to claim 1, wherein first analytic expression is as follows:
Wherein,S11X、S22X、S21X、
S12XRespectively indicate scattering parameter S11、S22、S21、S12True value, S11M、S22M、S21M、S12MRespectively indicate scattering parameter S11、
S22、S21、S12Measured value, EDFIndicate effective directivity forward error, EDRIndicate effective directivity backward error, EXFIndicate every
From degree forward error, EXRIndicate isolation backward error, ESFIndicate equivalent source mismatch forward error, ESRIndicate equivalent source mismatch
Backward error, ELFIndicate equivalent matched load mismatch forward error, ELRIndicate equivalent matched load mismatch backward error, ETFTable
Show transmission tracking forward error, ETRIndicate transmission tracking backward error, ERFIndicate reflection tracking forward error and ERRIndicate anti-
Penetrate tracking backward error.
3. the method according to claim 1, wherein step S2 includes:
S21 establishes single port error model, obtains the true value and 12 mistakes of the scattering parameter of Two-port netwerk vector network analyzer
The second analytic expression between difference and the measured value of scattering parameter；
S22 is respectively connected to open circuit calibration component, short-circuit calibration component and load calibration part to first port, three groups of data is obtained, to institute
Three groups of data application ridge regression algorithms are stated to be fitted；
S23 repeats step S22 to second port, obtains the value of reflection error in 12 errors；
S24 is missed by measuring transmission and isolation parameters between the first port and the second port in conjunction with the reflection
The value of difference determines the value that error is transmitted in 12 errors.
4. according to the method described in claim 3, it is characterized in that, step S24 includes:
S241 removes low-pass filter, connects matched load and surveys configured transmission S21And S12, respectively obtain measured value M1 and M4；
S242, the first port are connected to the second port, survey configured transmission S respectively21、S12With reflection parameters S11、S22,
Respectively obtain measured value M2, M5 and M3, M6；
S243 obtains residual error in 12 errors in conjunction with the reflection error in the measured value and 12 errors
Value.
5. according to the method described in claim 3, it is characterized in that, the ridge regression algorithm is fitted with following formula:
Wherein, λ is the constant greater than 0.1, SX1、SX2And SX3It is true value, SM1、SM2And SM3Respectively access open circuit calibration
The measured value of part, short-circuit calibration component and matched load calibration component, S when accessing open circuit calibration componentX1=1, when accessing short-circuit calibration component
SX2=-1, S when accessing matched load calibration componentX3=0, EDFIndicate effective directivity forward error, ESFBefore indicating equivalent source mismatch
To error, ERFIndicate reflection tracking forward error, i is imaginary unit.
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| CN111398693A (en) * | 2020-04-28 | 2020-07-10 | 江苏神州半导体科技有限公司 | Method for measuring ESR (equivalent series resistance) and Q (Q) value of vacuum capacitor based on S-parameter network analyzer |
| CN111579869A (en) * | 2020-04-21 | 2020-08-25 | 中国电子科技集团公司第十三研究所 | Reciprocal two-port network S parameter measuring method and device and terminal equipment |
| CN112564823A (en) * | 2020-12-03 | 2021-03-26 | 浙江铖昌科技股份有限公司 | Multi-port radio frequency microwave calibration method based on self-calibration algorithm |
| CN112630716A (en) * | 2020-12-11 | 2021-04-09 | 西安电子科技大学 | Two-port vector network analyzer calibration method based on weighting correction |
| CN113791285A (en) * | 2021-08-23 | 2021-12-14 | 电子科技大学 | Vector network analyzer of non-reference receiver |
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| CN111579869A (en) * | 2020-04-21 | 2020-08-25 | 中国电子科技集团公司第十三研究所 | Reciprocal two-port network S parameter measuring method and device and terminal equipment |
| CN111398693A (en) * | 2020-04-28 | 2020-07-10 | 江苏神州半导体科技有限公司 | Method for measuring ESR (equivalent series resistance) and Q (Q) value of vacuum capacitor based on S-parameter network analyzer |
| CN112564823A (en) * | 2020-12-03 | 2021-03-26 | 浙江铖昌科技股份有限公司 | Multi-port radio frequency microwave calibration method based on self-calibration algorithm |
| CN112630716A (en) * | 2020-12-11 | 2021-04-09 | 西安电子科技大学 | Two-port vector network analyzer calibration method based on weighting correction |
| CN112630716B (en) * | 2020-12-11 | 2021-09-03 | 西安电子科技大学 | Two-port vector network analyzer calibration method based on weighting correction |
| CN113791285A (en) * | 2021-08-23 | 2021-12-14 | 电子科技大学 | Vector network analyzer of non-reference receiver |
| CN113791285B (en) * | 2021-08-23 | 2022-12-27 | 电子科技大学 | Vector network analyzer of non-reference receiver |
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