CN113745789A - Debugging method and system for filter debugging intermediate stage - Google Patents

Debugging method and system for filter debugging intermediate stage Download PDF

Info

Publication number
CN113745789A
CN113745789A CN202010459872.XA CN202010459872A CN113745789A CN 113745789 A CN113745789 A CN 113745789A CN 202010459872 A CN202010459872 A CN 202010459872A CN 113745789 A CN113745789 A CN 113745789A
Authority
CN
China
Prior art keywords
filter
matrix
debugging
return loss
follows
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN202010459872.XA
Other languages
Chinese (zh)
Inventor
肖如吾
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Suzhou Changheng Communication Technology Co ltd
Original Assignee
Shanghai Teprui Communication Technology Co ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Shanghai Teprui Communication Technology Co ltd filed Critical Shanghai Teprui Communication Technology Co ltd
Priority to CN202010459872.XA priority Critical patent/CN113745789A/en
Publication of CN113745789A publication Critical patent/CN113745789A/en
Pending legal-status Critical Current

Links

Images

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10—Complex mathematical operations
    • G06F17/16—Matrix or vector computation, e.g. matrix-matrix or matrix-vector multiplication, matrix factorization
    • H—ELECTRICITY
    • H01—ELECTRIC ELEMENTS
    • H01P—WAVEGUIDES; RESONATORS, LINES, OR OTHER DEVICES OF THE WAVEGUIDE TYPE
    • H01P11/00—Apparatus or processes specially adapted for manufacturing waveguides or resonators, lines, or other devices of the waveguide type
    • H01P11/007—Manufacturing frequency-selective devices

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Mathematical Physics (AREA)
  • Data Mining & Analysis (AREA)
  • Theoretical Computer Science (AREA)
  • Computational Mathematics (AREA)
  • Mathematical Analysis (AREA)
  • Mathematical Optimization (AREA)
  • Pure & Applied Mathematics (AREA)
  • Computing Systems (AREA)
  • Algebra (AREA)
  • Databases & Information Systems (AREA)
  • Software Systems (AREA)
  • General Engineering & Computer Science (AREA)
  • Manufacturing & Machinery (AREA)
  • Filters That Use Time-Delay Elements (AREA)

Abstract

The invention relates to a method for improving the precision of obtaining an intermediate state during filter debugging. The coupling matrix is extracted by improving the Cauchy method, the target return loss value RL in the prior art is replaced by the average value RLA of the in-band return loss measured in real time to be used as the return loss value in the intermediate state, and the value is used as the basis for correcting the ripple factor, so that the precision of obtaining the intermediate state is improved when the filter is debugged.

Description

Debugging method and system for filter debugging intermediate stage
Technical Field
The invention relates to a debugging method and a debugging system for a filter debugging intermediate stage, in particular to a filter coupling matrix extraction method and a filter coupling matrix extraction system based on a dynamic average return loss value.
Background
The environment adaptation requirements of communication systems to communication equipment are higher and higher, and the design and manufacture of the communication industry also face a large number of test measurement and data acquisition tests. For example, radio frequency wireless communications require filters to remove unwanted information and interference. The signal passing through the filter will cause a phase shift resulting in an increase in the error rate. The development of modern wireless data communication is high speed, reliable and secure, which requires excellent filter characteristics and low phase offset, thereby reducing the bit error rate.
To manufacture a high performance filter, debugging is more important than design. Because the inductance of the coils in the filter is difficult to accurately test, various factors (collectively referred to as parasitic parameters) such as turn-to-turn capacitance, contact capacitance, and mutual inductance between the coils can cause a large difference between the characteristics of the actually manufactured filter and the characteristics expected during design. The effects and errors caused by these parasitic parameters must be adjusted to compensate.
The debugging of the filter has been a major and difficult point for the production process of the filter (including cavity filter, ceramic dielectric filter, etc.). Various filter debugging methods and theories have been successively developed by the industry and academia. The diagnosis of the filter has important guiding significance for the debugging of the filter. The filter diagnosis technique is to extract necessary information from the current scattering parameter (S parameter) of the filter and obtain the error of each tuning rod in the current state of the filter. The coupling matrix based diagnostic technique is a common method of filter diagnostics, which reconstructs the coupling matrix of the filter from the S-parameters and compares the coupling matrix with the standard coupling matrix of the filter to derive the error of each tuning rod. Since each element of the coupling matrix can correspond to the tuning rod one to one, the practical guiding significance of the method in debugging is very clear.
In the existing coupling matrix diagnosis method, a characteristic polynomial of a filter is obtained by using a Cauchy method, admittance parameters of the filter are obtained according to the characteristic polynomial, and partial fractional decomposition is carried out on the admittance parameters so as to obtain all elements of the coupling matrix, so that better diagnosis precision is obtained.
However, in the debugging process, it is a gradual process from detuning to completely reaching the technical index, so that the debugging process has many intermediate states, and the prior art has the problem of erroneous judgment caused by insufficient accuracy of obtaining the intermediate states when the intermediate states are obtained. According to the method proposed by Amari in the document "Adaptive synthesis and design of receiver filters with source/load-multiresotor coupling", the corresponding S parameters can be reversely deduced through the coupling matrix, and the reversely deduced S parameters can be compared with the S parameters measured by the vector network analyzer, so that whether the obtained coupling matrix is accurate or not can be guided.
Disclosure of Invention
The invention relates to a method for improving the precision of obtaining an intermediate state during filter debugging.
In order to achieve the above object, the present invention provides a filter debugging method, which improves the cauchy method to extract the coupling matrix to improve the accuracy of obtaining the intermediate state.
Step 1, extracting S parameters of a filter to be adjusted for later use by using a Vector Network Analyzer (VNA);
step 2, constructing an H matrix, and solving to obtain a characteristic polynomial and a characteristic vector;
step 3, after the eigenvector is obtained, constructing an admittance matrix according to the eigenvector, wherein when the ripple factor is calculated, the average value of in-band return loss measured in real time is used as the return loss value in the intermediate state;
step 4, solving a characteristic root and a residue of an admittance parameter according to the admittance matrix to obtain a coupling matrix corresponding to the filter element structure;
the present application makes use of the average value of the in-band return loss for real-time measurementsRL A Replacing the target return loss value of the prior artRLThe method is used as a return loss value in the intermediate state and the value is used as a basis for correcting the ripple factor, so that the accuracy of obtaining the intermediate state is improved when the filter is debugged.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the provided drawings without creative efforts.
Fig. 1 is a flowchart of a method for debugging a filter according to an embodiment of the present invention;
FIG. 2 shows a method for using the present invention toRL A SubstitutionRLThe result of comparing the S parameter of the coupling matrix reverse deduction with the actually measured S parameter is as follows:
Detailed Description
The invention is further illustrated by the following figures and examples.
The variable symbols used in the present invention are not limited to those used in the present invention. It is considered to be within the scope of the present invention to use other variable symbols instead of the variable symbols used in the filter tuning method of the present invention. The basic flow chart of constructing the coupling matrix by using the Cauchy method is shown in FIG. 1:
the detailed process of extracting the coupling matrix by improving the Cauchy method is as follows.
And S1, extracting the S parameters of the filter to be adjusted by using a Vector Network Analyzer (VNA) for standby.
S2, StructureHThe matrix is as follows:
Figure DEST_PATH_IMAGE001
（1）
wherein, VM(fL) Is a van der mond matrix, which is constructed as follows:
Figure 96264DEST_PATH_IMAGE002
（2）
(2) in (1),
Figure DEST_PATH_IMAGE003
wherein,f 0 is the center frequency of the pass band and is,Bis the passband bandwidth, andQunamely the unloaded Q value to be extracted.f(i)The frequency corresponding to the S-parameter extracted for the VNA.
Figure 826454DEST_PATH_IMAGE004
（3）
Remember again:
Figure DEST_PATH_IMAGE005
（4）
wherein,npfor the number of filter poles and reflection zeros,nzthe number of zeros is transmitted for the filter. Then solving equation (5) yields a characteristic polynomialFs、PsAndEsrespectively is a(1),a(2)And a(3)。
Figure 668508DEST_PATH_IMAGE006
(5)
The method for solving a by carrying out singular value decomposition on the H matrix(1),a(2)And a(3). Namely, the method comprises the following steps:
Figure DEST_PATH_IMAGE007
Vthe last column of (a) is the feature vector, which is represented by a(1),a(2)And a(3)And (4) forming.
S3, after the eigenvector is obtained, the admittance matrix can be constructed according to the eigenvector[Y N ]
Figure 378231DEST_PATH_IMAGE008
If the order of the filter is recorded asNAnd y is11And y12Need not be used in subsequent calculations, then y21And y22Is solved as follows:
Nis an even number:
Figure DEST_PATH_IMAGE009
Nis odd number:
Figure 192604DEST_PATH_IMAGE010
wherein,
Figure DEST_PATH_IMAGE011
e i andf i ,i=0,1,2,3...Nare respectively polynomialE S AndF S the complex coefficient of (a).
And erThe ripple factor, if the designed in-band return loss of the filter is constantRLThen it is defined as follows:
Figure 77383DEST_PATH_IMAGE012
(6)
the invention measures the average value of the in-band return loss in real timeRL A Instead of the formerRLAs a return loss value in the intermediate state, it is defined as follows:
Figure DEST_PATH_IMAGE013
wherein,S 11 (i),i=1,2,…Mis S in the pass band of the filter11And (6) measuring the values.
For the case of asymmetric zeros and a finite number of zeros smaller than the filter order, there are:
Figure 891886DEST_PATH_IMAGE014
otherwise:
Figure DEST_PATH_IMAGE015
s4, for y in fractional form according to equation (7)21And y22Partial expansion is carried out to obtain corresponding pole lambda11、λ21And a residue r11、r21Note λ11、λ21And a residue r11、r21Is to be according to lambda21The imaginary parts are sorted in ascending order.
Figure 90786DEST_PATH_IMAGE016
Figure DEST_PATH_IMAGE017
(7)
S5, according to the pole lambda11(k)、λ21(k) And a residue r11(k)、r21(k) The elements of the coupling matrix may be constructed according to (8):
Figure 87561DEST_PATH_IMAGE018
Figure DEST_PATH_IMAGE019
(8)
further, the lateral coupling matrix can be obtained as follows:
Figure 392510DEST_PATH_IMAGE020
according to the transverse coupling matrix, coupling matrixes corresponding to various filter structures in practical application can be obtained through matrix similarity transformation.
The invention, if the design target return loss of the filter is utilizedRLAs a basis for calculation, in the process of debugging the filter, since the difference between the in-band return loss and the target RL is large and the difference at each frequency point is not uniform, the S parameter of the coupling matrix back-estimation obtained by the method is greatly different from the S parameter measured by the actual filter.
The effect of the invention is illustrated below by taking the tuning of a filter with 10 reflection zeros, 10 poles and 4 zeros as an example,
average value of in-band return loss measured in real time according to the inventionRL A Instead of the formerRLThe coupling matrix constructed by the above method as the return loss value at the intermediate state is as follows:
Figure DEST_PATH_IMAGE021
embodiments of the present invention can be implemented in hardware or software, depending on certain implementation requirements. The implementation can be performed using the following digital storage medium having electronically readable control signals stored thereon: such as a floppy disk, DVD, CD, ROM, PROM, EPROM, EEPROM or flash memory, which cooperates with (or is capable of cooperating with) a programmable computer system such that the respective method is performed.
Some embodiments according to the invention comprise a data carrier with electronically readable control signals, the data carrier being capable of cooperating with a programmable computer system such that one of the methods described herein is performed.
Generally, embodiments of the invention can be implemented as a computer program product having a program code which is operable to perform one of the methods when the computer program product runs on a computer. For example, the program code may be stored on a machine readable carrier.
Other embodiments include a computer program for performing one of the methods described herein, where the program is stored on a machine-readable carrier or non-transitory storage medium.
In other words, an embodiment of the inventive method is thus a computer program with computer code for performing one of the methods described herein, when the computer program runs on a computer.
Another embodiment of the inventive method is thus a data carrier (or digital storage medium, or computer readable medium) comprising a computer program recorded thereon for performing one of the methods described herein.
Another embodiment of the invention is thus a data stream or signal sequence representing a computer program for performing one of the methods described herein. The data stream or signal sequence may for example be configured to be communicated via a data communication connection, for example via the internet.
Another embodiment comprises a processing device, such as a computer or programmable logic device, configured or adapted to perform one of the methods described herein.
Another embodiment comprises a computer having installed thereon a computer program for performing one of the methods described herein.
In some embodiments, a programmable logic device (e.g., a field programmable gate array) may be used to perform some or all of the functions of the methods described herein. In some embodiments, a field programmable gate array may cooperate with a microprocessor to perform one of the methods described herein. In general, the method is preferably performed by any hardware device.
The above-described embodiments are merely illustrative of the principles of the present invention. It is to be understood that modifications and variations to the arrangements and details described herein will be apparent to those skilled in the art. It is therefore intended that the scope of the claims be limited only by the pending patent claims and not by the specific details given herein by way of the description and illustration of the embodiments.

Claims (6)

1. A method for debugging a filter, comprising the steps of:
step 1, extracting S parameters of a filter to be adjusted for later use by using a Vector Network Analyzer (VNA);
step 2, constructing an H matrix, and solving to obtain a characteristic polynomial of the filter and a characteristic vector;
step 3, after the eigenvector is obtained, constructing an admittance matrix according to the eigenvector, wherein when the ripple factor is calculated, the average value of in-band return loss measured in real time is used as the return loss value in the intermediate state;
and 4, solving the characteristic root and the residue of the admittance parameters according to the admittance matrix to obtain a coupling matrix corresponding to the filter element structure.
2. The filter debugging method of claim 1, wherein the step 2 specifically comprises:
the H matrix is constructed as follows:
Figure RE-FDA0002583624390000011
wherein M is the number of points of the extracted S parameter, VM(fL) Is a van der mond matrix, which is constructed as follows:
Figure RE-FDA0002583624390000012
(2) in (1),
Figure RE-FDA0002583624390000013
wherein f is0The passband center frequency, B the passband bandwidth, and Qu the unloaded Q value to be extracted. f (i) is the frequency corresponding to the S parameter extracted by the VNA.
S11M＝diagS11(fL(i))i＝1，...，M
S21M＝diagS21(fL(i))i＝1，...，M
(3)
Remember again:
Figure RE-FDA0002583624390000014
Figure RE-FDA0002583624390000015
Figure RE-FDA0002583624390000016
wherein np is the number of poles and reflection zeros of the filter, and nz is the number of transmission zeros of the filter. Then solving equation (5) yields a characteristic polynomialCoefficient values of Fs, Ps and Es, respectively, are a(1)，a(2)And a(3)。
Figure RE-FDA0002583624390000021
The method for solving a by carrying out singular value decomposition on the H matrix(1)，a(2)And a(3). Namely, the method comprises the following steps:
SVD(H)＝[U，S，V]
the last column of V is the feature vector, which is represented by a(1)，a(2)And a(3)And (4) forming.
3. The filter debugging method of claim 1, wherein the step 3 specifically comprises:
after the eigenvectors are obtained, an admittance matrix [ Y ] can be constructed according to the eigenvectorsN]
Figure RE-FDA0002583624390000022
If the order of the filter is N, y11And y12Need not be used in subsequent calculations, then y21And y22Is solved as follows:
n is an even number:
Figure RE-FDA0002583624390000023
Figure RE-FDA0002583624390000024
n is an odd number:
Figure RE-FDA0002583624390000025
Figure RE-FDA0002583624390000026
wherein,
m1(s)＝Re(e0+f0/εr)+...+jIm(eN+fN/εr)s
n1(s)＝jIm(e0++f0/εr)+...+Re(eN+fN/εr)s
eiand fiN is a polynomial E, 0, 1,2, 3SAnd FSThe complex coefficient of (a).
And erThe ripple factor is obtained, and if the designed in-band return loss of the filter is a constant RL, it is defined as follows:
Figure RE-FDA0002583624390000031
average value RL of in-band return loss measured in real timeAInstead of RL as the return loss value in the intermediate state, it is defined as follows:
Figure RE-FDA0002583624390000032
wherein S is11(i) I 1,2, … M, S in the filter passband11And (6) measuring the values.
For the case of asymmetric zeros and a finite number of zeros smaller than the filter order, there are:
εr＝1
otherwise:
Figure RE-FDA0002583624390000033
4. the filter debugging method of claim 1, wherein the step 4 specifically comprises:
according to equation (7), for y in fractional form21And y22Partial expansion is carried out to obtain corresponding pole lambda11、λ21And a residue r11、r21Note λ11、λ21And a residue r11、r21Is to be according to lambda21The imaginary parts are sorted in ascending order.
Figure RE-FDA0002583624390000034
According to the pole lambda11(k)、λ21(k) And a residue r11(k)、r21(k) The elements of the coupling matrix may be constructed according to (8):
Ck＝1；
Bk＝-λ21(k)；
Mkk＝Bk；
Figure RE-FDA0002583624390000041
Figure RE-FDA0002583624390000042
Figure RE-FDA0002583624390000043
further, the lateral coupling matrix can be obtained as follows:
Figure RE-FDA0002583624390000044
5. a computer readable storage medium storing a program which when executed by a processor performs the steps of one of claims 1 to 4.
6. An apparatus for debugging a filter, comprising a processor and a memory, said memory storing a program which, when executed by said processor, performs the steps of one of claims 1 to 4.
CN202010459872.XA 2020-05-29 2020-05-29 Debugging method and system for filter debugging intermediate stage Pending CN113745789A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202010459872.XA CN113745789A (en) 2020-05-29 2020-05-29 Debugging method and system for filter debugging intermediate stage

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202010459872.XA CN113745789A (en) 2020-05-29 2020-05-29 Debugging method and system for filter debugging intermediate stage

Publications (1)

Publication Number Publication Date
CN113745789A true CN113745789A (en) 2021-12-03

Family

ID=78723615

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202010459872.XA Pending CN113745789A (en) 2020-05-29 2020-05-29 Debugging method and system for filter debugging intermediate stage

Country Status (1)

Country Link
CN (1) CN113745789A (en)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115184716A (en) * 2022-09-13 2022-10-14 苏州畅恒通信科技有限公司 Carrier difference correction method for electrical performance detection of radio frequency filter or duplexer

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP3086470A1 (en) * 2015-04-21 2016-10-26 Airbus Defence and Space GmbH Method for creating a coupling matrix for tuning filters and device for tuning filters
CN107766646A (en) * 2017-10-13 2018-03-06 中国地质大学（武汉） The processing method and system of the microwave filter of limit and the residual structure of Y parameter
CN108509671A (en) * 2018-01-30 2018-09-07 西安电子科技大学 microwave filter coupling parameter extracting method
CN109063374A (en) * 2018-08-31 2018-12-21 中国地质大学（武汉） A kind of coupling matrix extracting method based on parameter optimization, equipment and storage equipment

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP3086470A1 (en) * 2015-04-21 2016-10-26 Airbus Defence and Space GmbH Method for creating a coupling matrix for tuning filters and device for tuning filters
CN107766646A (en) * 2017-10-13 2018-03-06 中国地质大学（武汉） The processing method and system of the microwave filter of limit and the residual structure of Y parameter
CN108509671A (en) * 2018-01-30 2018-09-07 西安电子科技大学 microwave filter coupling parameter extracting method
CN109063374A (en) * 2018-08-31 2018-12-21 中国地质大学（武汉） A kind of coupling matrix extracting method based on parameter optimization, equipment and storage equipment

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115184716A (en) * 2022-09-13 2022-10-14 苏州畅恒通信科技有限公司 Carrier difference correction method for electrical performance detection of radio frequency filter or duplexer
CN115184716B (en) * 2022-09-13 2022-11-29 苏州畅恒通信科技有限公司 Carrier difference correction method for electrical performance detection of radio frequency filter or duplexer

Similar Documents

Publication Publication Date Title
CN109063374B (en) Parameter optimization-based coupling matrix extraction method and device and storage device
CN108879047B (en) Method and device for debugging microwave cavity filter and storage device
CN105137373B (en) A kind of denoising method of exponential signal
CN111580137B (en) Fitting method for high-precision navigation receiver radio frequency channel group delay characteristics
CN113745789A (en) Debugging method and system for filter debugging intermediate stage
CN108509671A (en) microwave filter coupling parameter extracting method
CN113359078A (en) Vector network analyzer calibration method based on sixteen-term error model
CN117686774A (en) Broadband voltage signal monitoring method, system, equipment and storage medium
CN114167237A (en) GIS partial discharge fault identification method and system, computer equipment and storage medium
Wang et al. Diagnosis of coupled resonator bandpass filters using VF and optimization method
Zhao et al. Circuit model extraction for computer-aided tuning of a coupled-resonator diplexer
CN113255137B (en) Target object strain data processing method and device and storage medium
CN112291039B (en) Data coding transmission method based on channel signal period
CN109510734B (en) Group delay measuring method
CN115169735A (en) Electroceramic quality prediction method and system based on sample expansion
CN114993671A (en) Vibration fault diagnosis method and system based on Q factor wavelet transform
CN110426610B (en) Resonance frequency extraction method and system based on amplitude-frequency response and least square method
CN108376123A (en) A kind of satellite gravity observing data outliers extracting method, device and electronic equipment
CN114114117A (en) Magnetic resonance spectrum phase correction method based on deep learning
CN113705335A (en) Time-frequency super-resolution extraction method for low-frequency sparse line spectrum signal
CN112989965A (en) SVD-LCD-BCM-based fault feature extraction method
Oldoni et al. Accurate computation of poles of a lossless multiport network via cepstrum analysis
CN114499705B (en) Frequency response flatness calibration method and device, electronic equipment and storage medium
CN114079131B (en) Cavity filter debugging method
Wu et al. The Data Sampling Strategy for Computer Aided Diagnosis of Microwave Filters

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
CB02 Change of applicant information

Address after: 200080 7th floor, No.137 Haining Road, Hongkou District, Shanghai

Applicant after: Shanghai Changheng automation equipment Co.,Ltd.

Address before: 200080 7th floor, 137 Haining Road, Hongkou District, Shanghai

Applicant before: Shanghai teprui Communication Technology Co.,Ltd.

CB02 Change of applicant information
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
TA01 Transfer of patent application right

Effective date of registration: 20220809

Address after: 215000 zone 2fd, building 2, 345 Fengli street, Suzhou Industrial Park, Jiangsu Province

Applicant after: Suzhou Changheng Communication Technology Co.,Ltd.

Address before: 200080 7th floor, No.137 Haining Road, Hongkou District, Shanghai

Applicant before: Shanghai Changheng automation equipment Co.,Ltd.

TA01 Transfer of patent application right