A debugging method and system for filter debugging in the intermediate stage

Abstract

The present invention aims at improving the accuracy of obtaining the intermediate state when debugging the filter. By improving the Cauchy method to extract the coupling matrix, the average value RLA of the in-band return loss measured in real time is used instead of the target return loss value RL of the prior art as the return loss value in the intermediate state, and the value is used as the basis for correcting the ripple coefficient, so as to improve the accuracy of obtaining the intermediate state when debugging the filter.

Description

Technical Field

[0001] The invention relates to a debugging method and system for the intermediate stage of filter debugging, and in particular to a filter coupling matrix extraction method system based on dynamic average return loss value. Background Art

[0002] The communication system has higher and higher requirements for the environmental adaptability of communication equipment. The design and manufacturing of the communication industry also face a large number of test measurements and data acquisition experiments. For example, RF wireless communication requires the use of filters to remove useless information and interference. When the signal passes through the filter, it will produce a phase shift, resulting in an increase in the bit error rate. The development direction of modern wireless data communication is high speed, reliability and confidentiality, which requires the filter to have excellent characteristics and less phase shift, thereby reducing the bit error rate.

[0003] To manufacture a high-performance filter, in addition to design, debugging is more important. Because the inductance of the coil in the filter is difficult to accurately test, various factors such as the inter-turn capacitance, contact capacitance and mutual inductance between the coils (collectively referred to as parasitic parameters) will cause a large difference between the characteristics of the filter actually manufactured and the characteristics expected during design. Therefore, debugging is necessary to compensate for the influence and errors caused by these parasitic parameters.

[0004] For the production process of filters (including cavity filters, ceramic medium filters, etc.), filter debugging has always been the focus and difficulty. The industry and academia have successively developed a variety of filter debugging methods and theories. Filter diagnosis has important guiding significance for filter debugging. The so-called filter diagnostic technology refers to extracting the required information based on the current scattering parameters (S parameters) of the filter, and then obtaining the errors of each tuning rod in the current state of the filter. The coupling matrix-based diagnostic technology is a common method for filter diagnosis. This method reconstructs the coupling matrix of the filter according to the S parameters, and compares the coupling matrix with the standard coupling matrix of the filter to obtain the errors of each tuning rod. Since each element of the coupling matrix can correspond to the tuning rod one by one, the practical guiding significance of this method in debugging is very clear.

[0005] In the existing coupling matrix diagnosis method, the Cauchy method is used to obtain the characteristic polynomial of the filter, and then the admittance parameters of the filter are obtained based on the characteristic polynomial. The method of partially decomposing the admittance parameters to obtain all the elements of the coupling matrix has achieved good diagnostic accuracy.

[0006] However, during the debugging process, the process from detuning the filter to fully achieving the technical indicators is a gradual process, so there are many intermediate states in the debugging process, and the existing technology has the problem of insufficient accuracy in obtaining the intermediate states, resulting in misjudgment. According to the method proposed by Amari in the document "Adaptive synthesis and design of resonator filters with source / load-multiresonator coupling", the corresponding S parameters can be inferred from the coupling matrix, and the inferred S parameters can be compared with the S parameters measured by the vector network analyzer to indicate whether the obtained coupling matrix is ​​accurate. Summary of the invention

[0007] The present invention aims at improving the method for obtaining the intermediate state accuracy during filter debugging.

[0008] To achieve the above object, the present invention provides a filter debugging method, which extracts a coupling matrix by an improved Cauchy method to improve the accuracy of obtaining an intermediate state.

[0009] Step 1, using a vector network analyzer (VNA) to extract the S parameters of the filter to be adjusted for later use;

[0010] Step 2, construct the H matrix, solve it to get the characteristic polynomial and obtain the eigenvector;

[0011] Step 3, after obtaining the eigenvector, construct an admittance matrix according to the eigenvector, wherein when calculating the ripple coefficient, the average value of the in-band return loss measured in real time is used as the return loss value in the intermediate state;

[0012] Step 4, according to the admittance matrix, the characteristic roots and residues of the admittance parameters are obtained, and the coupling matrix corresponding to the filter element structure is obtained;

[0013] This application uses the average value of the in-band return loss measured in real time RL A Replace the target return loss value of the existing technology RL The return loss value in the intermediate state is used as the basis for correcting the ripple coefficient, thereby improving the accuracy of obtaining the intermediate state when debugging the filter. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0015] Figure 1 A flow chart of a method for debugging a filter provided by an embodiment of the present invention;

[0016] Figure 2 To use the method proposed by the present invention, RL A replace RL The results of comparing the S parameters inferred from the coupling matrix with the measured S parameters are as follows: DETAILED DESCRIPTION

[0017] The present invention is further described below in conjunction with the accompanying drawings and embodiments.

[0018] The variable symbols used in the present invention are not limited to the symbols used in the present invention. If other variable symbols are used to replace the variable symbols used in the filter debugging method described in the present invention, they can all be considered to be within the protection scope of the present invention. The basic flow chart of constructing the coupling matrix using the Cauchy method is as follows: Figure 1 :

[0019] The detailed process of extracting the coupling matrix by the improved Cauchy method of the present invention is as follows.

[0020] S1. Use a vector network analyzer (VNA) to extract the S parameters of the filter to be adjusted for later use.

[0021] S2. Construction H The matrix is ​​as follows:

[0022] (1)

[0023] Among them, V M (f L ) is a Vandermonde matrix, which is constructed as follows:

[0024] (2)

[0025] (2)

[0026] in, f 0 is the passband center frequency, B is the passband bandwidth, and Qu This is the unloaded Q value that needs to be extracted. f(i) The frequency corresponding to the S-parameter extracted by the VNA.

[0027] (3)

[0028] Also note:

[0029] (4)

[0030] in, np is the number of filter poles and reflection zeros, nz is the number of transmission zeros of the filter. Then solving equation (5) can obtain the characteristic polynomial Fs , Ps and Es The coefficient values ​​are a (1) ,a (2) and a (3) .

[0031] (5)

[0032] We can use the singular value decomposition method of the H matrix to solve a (1) ,a (2) and a (3) . That is:

[0033]

[0034] V The last column of is the eigenvector, which is composed of a (1) ,a (2) and a (3) constitute.

[0035] S3. After obtaining the eigenvector, the admittance matrix can be constructed based on the eigenvector [Y N ]

[0036]

[0037] If the order of the filter is N , and y 11 and 12 It is not needed in subsequent calculations, so y 21 and 22 The solution is as follows:

[0038] N For an even number:

[0039]

[0040] N For odd numbers:

[0041]

[0042] in,

[0043]

[0044] ei and f i , where i = 0, 1, 2, 3... N Polynomial E S and F S The complex coefficient of .

[0045] And ε and ε r is the ripple coefficient. If the return loss within the design band of the filter is a constant RL , then its definition is as follows:

[0046] (6)

[0047] The present invention uses the average value of the in-band return loss measured in real time RL A replace RL The return loss value in the intermediate state is defined as follows:

[0048]

[0049] in, S 11 (i), where i = 1, 2, … M , is S in the filter passband 11 Measurement value.

[0050] For the case of asymmetric zeros and a finite number of zeros less than the filter order, we have:

[0051]

[0052] otherwise:

[0053]

[0054] S4. According to formula (7), for the fractional form y 21 and 22 By performing partial fraction expansion, we can find the corresponding extreme point λ 11 , 21 and residue r 11 、r 21 , note that 11 , 21 and residue r 11 、r 21 The elements of 21 Sort in ascending order of the imaginary part.

[0055]

[0056] (7)

[0057] S5, according to the extreme point λ 11 (k), λ 21 (k) and the residue r 11 (k), r 21 (k), the elements of the coupling matrix can be constructed according to (8):

[0058]

[0059] (8)

[0060] Then the lateral coupling matrix can be obtained as follows:

[0061]

[0062] According to the lateral coupling matrix, the coupling matrix corresponding to the filter structure of various practical applications can also be obtained through matrix similarity transformation.

[0063] The present invention, if the design target return loss of the filter is used RL As the basis for calculation, during the debugging process of the filter, due to the large gap between the in-band return loss and the target RL, and the uneven gap at each frequency point, there is a large difference between the S parameters obtained by inverse calculation of the coupling matrix and the S parameters measured by the actual filter.

[0064] The effect of the present invention is explained below by taking the debugging of a filter with 10 reflection zeros, 10 poles and 4 zeros as an example.

[0065] According to the present invention, the average value of the in-band return loss measured in real time is RL A replace RL The coupling matrix constructed by the above method as the return loss value in the intermediate state is as follows:

[0066]

[0067] According to certain implementation needs, the embodiments of the present invention can be implemented in hardware or software. The implementation can be performed using the following digital storage medium on which electronically readable control signals are stored: for example, a floppy disk, DVD, CD, ROM, PROM, EPROM, EEPROM or flash memory, which cooperates with a programmable computer system (or can cooperate with a programmable computer system) so that the corresponding method is executed.

[0068] Some embodiments according to the invention comprise a data carrier having electronically readable control signals, which are capable of cooperating with a programmable computer system, such that one of the methods described herein is performed.

[0069] Generally, embodiments of the present invention can be implemented as a computer program product with a program code, wherein when the computer program product runs on a computer, the program code can be operated to perform one of the methods.For example, the program code can be stored on a machine-readable carrier.

[0070] Other embodiments comprise the computer program for performing one of the methods described herein, wherein the program is stored on a machine readable carrier or a non-transitory storage medium.

[0071] In other words, an embodiment of the inventive method is, therefore, a computer program having a computer code for performing one of the methods described herein, when the computer program runs on a computer.

[0072] A further embodiment of the inventive method is, therefore, a data carrier (or a digital storage medium, or a computer-readable medium) comprising, recorded thereon, the computer program for performing one of the methods described herein.

[0073] Another embodiment of the invention is therefore a data stream or a sequence of signals representing the computer program for performing one of the methods described herein.The data stream or the sequence of signals may, for example, be configured to be transferred via a data communication connection, for example via the Internet.

[0074] Another embodiment comprises a processing means, for example a computer or a programmable logic device, configured to or adapted to perform one of the methods described herein.

[0075] A further embodiment comprises a computer having installed on the computer the computer program for performing one of the methods described herein.

[0076] 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 collaborate with a microprocessor to perform one of the methods described herein. Typically, the method is preferably performed by any hardware device.

[0077] The above embodiments are merely illustrative of the principles of the present invention. It should be understood that modifications and variations to the arrangements and details described herein will be apparent to those skilled in the art. Therefore, it is intended that the present invention be limited only by the scope of the pending patent claims and not by the specific details provided by the description and illustration of the embodiments herein.

Claims

1. A filter debugging method, characterized in that: The following steps are involved: Step 1, using a vector network analyzer (VNA) to extract the S parameters of the filter to be adjusted for later use; Step 2, construct the H matrix, and solve it to get the characteristic polynomial of the filter and the characteristic vector; Step 3, after obtaining the eigenvector, construct an admittance matrix according to the eigenvector, wherein when calculating the ripple coefficient, the average value of the in-band return loss measured in real time is used as the return loss value in the intermediate state; Step 4, according to the admittance matrix, the characteristic roots and residues of the admittance parameters are obtained, and the coupling matrix corresponding to the filter element structure is obtained; The step 2 specifically includes: constructing the H matrix as follows: Where M is the number of points of the extracted S parameters, V M (f L ) is a Vandermonde matrix, which is constructed as follows: (2) Where f0 is the passband center frequency, B is the passband bandwidth, and Qu is the unloaded Q value to be extracted; f(i) is the frequency corresponding to the S parameter extracted by VNA; S 11M =diagS 11 (f L (i)) i＝1，...，M S 21M =diagS 21 (f L (i)) i＝1，...，M (3) Also note: Where np is the number of filter poles and reflection zeros, and nz is the number of filter transmission zeros. Then, by solving equation (5), we can obtain the coefficients of the characteristic polynomials Fs, Ps, and Es, which are respectively (1) , a (2) and a (3) ; We can use the singular value decomposition method of the H matrix to solve a (1) , a (2) and a (3) ; That is: SVD(H) = [U, S, V]; The last column of V is the eigenvector, which consists of a (1) , a (2) and a (3) constitute; The step 3 specifically includes: after obtaining the eigenvector, the admittance matrix [Y N ]; If the order of the filter is N, and y 11 and 12 It is not needed in subsequent calculations, so y 21 and 22 The solution is as follows: N is an even number: N is an odd number: in, m1(s)=Re(e0+f0 / ε r )+...+jIm(e N +f N / ε r )s; n1(s)=jIm(e0++f0 / ε r )+...+Re(e N +f N / ε r )s; e i and f i , i=0,1,2,3...N are polynomials E S and F S The complex coefficients of And ε and ε r is the ripple coefficient. If the return loss in the design band of the filter is a constant RL, its definition is as follows: The average return loss RL in the band is measured in real time. A Instead of RL as the return loss value in the intermediate state, it is defined as follows: Among them, S 11 (i), i=1,2,…M, is S in the filter passband 11 Measurement value; For the case of asymmetric zeros and a finite number of zeros less than the filter order, we have: e r =1 otherwise: The step 4 specifically includes: According to formula (7), for the fractional form y 21 and 22 By performing partial fraction expansion, we can find the corresponding extreme point λ 11 , 21 and residue r 11 、r 21 , note that 11 , 21 and residue r 11 、r 21 The elements of 21 Sort in ascending order of the imaginary part; According to the extreme point λ 11 (k), λ 21 (k) and the residue r 11 (k), r 21 (k), the elements of the coupling matrix can be constructed according to (8): C k ＝1； B k =-λ 21 (k); M kk =B k ; Then the lateral coupling matrix can be obtained as follows:

2. A computer-readable storage medium storing a program, wherein when the program is executed by a processor, the steps of claim 1 are performed.

3. A device for debugging a filter, comprising a processor and a memory, wherein the memory stores a program, and when the program is executed by the processor, the steps of claim 1 are performed.

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