CN110765651A - Modeling and intelligent design method of microstrip direct coupling filter - Google Patents
Modeling and intelligent design method of microstrip direct coupling filter Download PDFInfo
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Abstract
The invention discloses a modeling and intelligent design method of a microstrip direct coupling filter, which comprises the steps of obtaining S parameters of an initial filter, calculating out phase-removing loading factors α and β by adopting an optimization algorithm, obtaining a pole P and a residue R by vector fitting calculation, carrying out complete standard coupling matrix synthesis to obtain a filter coupling matrix M, and obtaining a decoupling matrix M meeting decoupling transformation conditions by adopting numerical iteration decoupling transformationd(ii) a Determining the design sizes of a plurality of groups of filters, acquiring S parameters of the filters based on measurement or electromagnetic simulation, extracting a decoupling matrix according to the steps, and establishing a space mapping model of the design sizes and the decoupling matrix; adjusting decoupling matrix elements of the initially designed filter through an optimization algorithm according to the expected design value to obtain a decoupling matrix M of the filter coupling matrix close to the expected design valued‑opt(ii) a Using the spatial mapping model according to a decoupling matrix Md‑optAnd calculating a design parameter L.
Description
Technical Field
The invention relates to the technical field of radio frequency microwave modeling simulation design, in particular to a modeling and intelligent design method of a microstrip direct coupling filter.
Background
In the theoretical research and design of microwave filters, the planar direct-coupled microwave filter is still the most frequently used filter in a microwave system due to the simple structure of the planar direct-coupled microwave filter. The general design flow is based on an ideal coupling matrix, combines indexes and an actual engineering structure, finds the resonator length of the actual engineering structure by adopting methods such as a single resonator eigenmode and the like, obtains the initial value of a gap between resonators through the operation of two eigenmodes coupled by the two resonators, and finds the initial value of the position of a feeder line through group delay.
However, since the actual engineering structure has cross coupling which is not described by the ideal direct coupling matrix, the design process causes two problems: firstly, the ideal coupling matrix cannot be matched with the physical structure of the final filter, so that the initial value of the design parameter and the direction of initial value adjustment cannot be accurately given at the beginning of design; secondly, the obtained initial values have poor corresponding responses of S11, S21 and the like, and long-time adjustment needs to be carried out by taking commercial electromagnetic FEA (finite element analysis) software as a main simulation means.
Disclosure of Invention
The technical problem to be solved by the invention is as follows: aiming at the problems of long period and complex process caused by adopting heuristic or full-parameter scanning to carry out simulation design by experience according to key indexes in the prior art, the modeling and intelligent design method of the microstrip direct coupling filter is provided.
The technical scheme adopted by the invention is as follows:
a modeling and intelligent design method of a microstrip direct coupling filter comprises the following steps:
step S1, determining the structure and the initial design size of the filter, and acquiring the S parameter of the initial filter based on measurement or electromagnetic simulation;
step S2, calculating dephasing loading factors α and β of the S parameter obtained in the step S1 by adopting an optimization algorithm;
step S3, obtaining a pole P and a residue R through vector fitting calculation by using the dephase loading factors α and β calculated in the step S2;
step S4, carrying out complete standard coupling matrix synthesis by using the pole P and the residue R calculated in the step S3 to obtain a filter coupling matrix M;
step S5, a decoupling matrix M meeting the decoupling transformation condition is obtained by adopting numerical iteration decoupling transformation on the filter coupling matrix M obtained in the step S4d；
S6, obtaining design sizes and S parameters of a plurality of groups of filters by adopting measurement or electromagnetic simulation, extracting a decoupling matrix according to the steps S2 to S5, and establishing a space mapping model of the design sizes and the decoupling matrix;
step S7, according to the expected design value, adjusting the decoupling matrix element of the initially designed filter through an optimization algorithm to obtain the decoupling matrix M of the filter coupling matrix close to the expected design valued-opt；
Step S8, utilizing the space mapping model to obtain the decoupling matrix M of the optimized filter coupling matrixd-optAnd calculating a design parameter L.
Further, in step S2, for the S parameter obtained in step S1, the method for calculating the dephase loading factors α and β by using the optimization algorithm includes:
initializing dephasing loading factors α and β;
determining the S parameter S after dephasing loadingqS parameter S obtained in step S1mThe relationship of (1):
wherein f issIs the sampling frequency, j is the imaginary unit;
adjusting the dephasing loading factors α and β by an optimization algorithm to make it possible to adjust the S parameter S obtained in the step S1 within the engineering accuracymPhase removing and loading, namely, taking an evaluation index calculation formula as an optimization objective function, adopting an optimization algorithm, and finding phase removing and loading factors α and β meeting the precision of the evaluation index through iterative automatic adjustment, wherein the evaluation index calculation formula is as follows:
wherein
Is the reflection coefficient calculated using the vector fitted Y parameter,and
by vector fittingThe reflection coefficients calculated by the latter extracted coupling matrix,and
are the dephasing reflection coefficients calculated directly with the same set of dephasing loading factors.
Further, the optimization algorithm is an evolutionary algorithm, a group intelligence algorithm, a gradient algorithm or an optimization algorithm mixed by the foregoing algorithms.
Further, in step S3, the method for obtaining the pole P and the residue R by vector fitting calculation using the dephasing loading factors α and β calculated in step S2 includes:
step S3.1, calculating S parameter S after dephasing loading by using the dephasing loading factors α and β calculated in step S2qAnd admittance parameter Yq；
Step S3.2, rational function is adopted to the admittance parameter YqCarrying out vector fitting so as to calculate and obtain a pole P and a residue R of the rational function; the rational function is:
wherein N represents the order of the filter, s represents the normalized frequency of the filter, j is an imaginary unit, R11k、R12k、R21k、R21kAs admittance parameter YqResidue sum of approximate polynomial0Is a factor related to the finite transmission zero.
Further, in step S5, a decoupling matrix M satisfying a decoupling transformation condition is obtained by applying numerical iterative decoupling transformation to the filter coupling matrix M obtained in step S4dThe method comprises the following steps:
step S5.1, the filter coupling matrix M obtained in the step S4 is rotated and eliminated to obtain an initial decoupling matrix Me；
S5.2, adopting numerical iteration decoupling variation to the initial decoupling matrix after rotating eliminationObtaining a decoupling matrix M meeting decoupling conversion conditions through conversiond。
Further, in step S5.2, the decoupling matrix M satisfying the decoupling transformation condition is obtained by applying numerical iterative decoupling transformation to the initial decoupling matrix after rotating eliminationdThe method comprises the following steps:
optimizing convergence to decouple matrix MdWith initial decoupling matrix MeReflection coefficient S of11Or S22The sum of squared errors of (a) is used as an evaluation index;
by adopting an evolutionary algorithm, a group intelligence algorithm, a gradient algorithm or a hybrid optimization algorithm, a globally optimal decoupling matrix M meeting decoupling transformation conditions is automatically solvedd。
Furthermore, the elimination sequence of the rotation elimination element is from right to left, in advance, in the back row and in the alternate row and column.
Further, the decoupling transition condition includes:
1) eigenvalues and eigenvectors of the matrix, or an approximation of the calculated S-parameters and the initial decoupling matrix;
2) elements except the first row, the first column and the last row are non-zero elements;
3) the non-zero elements must satisfy symmetry about both the major diagonal and the minor diagonal;
4) except the diagonal line and the elements at two adjacent sides, the absolute values of other non-zero elements are required to be consistent with the gap width rule of the actual filter along the direction of the main diagonal line.
Further, in step S6, the method for obtaining the design size and S parameters of the multiple sets of filters by measurement or electromagnetic simulation, extracting the decoupling matrix according to steps S2 to S5, and establishing the spatial mapping model of the design size and the decoupling matrix includes: using a multiple-input multiple-output neural network model FANNEstablishing a decoupling matrix MdAnd a space mapping model with a design size, wherein the paradigm of the space mapping model is that L ═ fANN(Md，ω)；
Wherein, L is the design size parameter vector of the filter represented by the corresponding decoupling matrix; omega is an internal parameter of the space mapping model, and is obtained by carrying out comparison on L-Md samplesObtaining data pair training; mdAre the decoupling matrices extracted for the sets of filters through steps S2 through S5.
Further, in step S7, according to the expected design value, the decoupling matrix element of the initially designed filter is adjusted by the optimization algorithm to obtain the decoupling matrix M of the filter coupling matrix close to the expected design valued-optThe method comprises the following steps:
decoupling matrix M for initially dimensioned filtersdOptimizing and iteratively adjusting the main diagonal line and the elements on two adjacent sides of the main diagonal line;
with decoupling matrix M in an iterative processdCalculating the reflection coefficient S11Or S22Calculating the error square sum of the scattering coefficient and the expected value;
adjusting decoupling matrix M by error inverse gradient propagation optimization algorithmdUntil the error meets the precision, obtaining a decoupling matrix M of the optimized filter coupling matrixd-opt。
In summary, due to the adoption of the technical scheme, the invention has the beneficial effects that:
according to the invention, by establishing the spatial mapping model of the coupling matrix and the filter design size, the specific design size parameters of the filter meeting the performance requirements are automatically and quickly optimized according to the expected design indexes of the filter, the method is suitable for the design of the microstrip direct coupling filter with the symmetrical structures of different orders, is particularly suitable for quickly evaluating the feasibility of the filter design indexes, and can optimize and provide refined recommended parameters to be directly used for manufacturing products.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.
Fig. 1 is a flow chart of a modeling and intelligent design method of a microstrip direct coupling filter according to the present invention.
Fig. 2 is a schematic structural diagram of a fifth-order microstrip direct-coupled filter according to embodiment 1 of the present invention.
Fig. 3 is a decoupling matrix form of a fifth-order microstrip direct-coupled filter according to embodiment 1 of the present invention.
FIG. 4 is a comparison graph of S-parameters before and after dephasing loading in example 1 of the present invention.
FIG. 5 shows the reflection coefficient S of the filter before and after optimization according to embodiment 1 of the present invention11Compare the figures.
FIG. 6 shows insertion loss S of filters before and after optimization according to embodiment 1 of the present invention21Compare the figures.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the detailed description and specific examples, while indicating the preferred embodiment of the invention, are intended for purposes of illustration only and are not intended to limit the scope of the invention. The components of embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present invention, presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present invention without making any creative effort, shall fall within the protection scope of the present invention.
A modeling and intelligent design method of a microstrip direct coupling filter comprises the following steps:
step S1, determining the structure and the initial design size of the filter, and acquiring the S parameter of the initial filter based on measurement or electromagnetic simulation; the S parameter covers the working frequency band of the microstrip direct coupling filter;
step S2, calculating dephasing loading factors α and β of the S parameter obtained in the step S1 by adopting an optimization algorithm;
in this step, the de-phase loading factors α and β are initialized, with α being the phase loading constant term that contains the higher order modes introduced by the input and output ports, and with β being the phase loading transmission line equivalent electrical length that contains the phase shift introduced by the transmission line of the input and output ports.
Further, the S parameter after dephasing loading is denoted as SqThe S parameter acquired at step S1 is denoted as SmThen S isqAnd SmThe following relationships exist:
wherein f issIs the sampling frequency, j is the imaginary unit;
furthermore, an evaluation index calculation formula is used as an optimization objective function, a searching algorithm is adopted, and phase-removing loading factors α and β meeting the precision of the evaluation index are found through iterative automatic adjustment, wherein the searching algorithm is an evolutionary algorithm (such as a genetic algorithm), a swarm intelligence algorithm (such as an ant colony algorithm), a gradient algorithm or an optimization algorithm mixed by the algorithms, and the evaluation index calculation formula is as follows:
wherein
Is the reflection coefficient calculated using the vector fitted Y parameter,
and
is the reflection coefficient calculated using the extracted coupling matrix after vector fitting,
and
are the dephasing reflection coefficients calculated directly with the same set of dephasing loading factors.
In step S3, using the dephasing loading factors α and β calculated in step S2, the pole P and the residue R are obtained by vector fitting calculation:
step S3.1, calculating S parameter S after dephasing loading by using the dephasing loading factors α and β calculated in step S2qAnd admittance parameter Yq；
Step S3.2, rational function is adopted to the admittance parameter YqCarrying out vector fitting so as to calculate and obtain a pole P and a residue R of the rational function; the rational function is:
wherein N represents the order of the filter, s represents the normalized frequency of the filter, j is an imaginary unit, R11k、R12k、R21k、R21kAs admittance parameter YqResidue sum of approximate polynomial0Is a factor related to the finite transmission zero.
Step S4, carrying out complete standard coupling matrix synthesis by using the pole P and the residue R calculated in the step S3 to obtain a filter coupling matrix M;
step S5, a decoupling matrix M meeting the decoupling transformation condition is obtained by adopting numerical iteration decoupling transformation on the filter coupling matrix M obtained in the step S4d：
Step S5.1, the filter coupling matrix M obtained in the step S4 is rotated and eliminated to obtain an initial decoupling matrix Me(ii) a And (3) performing rotation elimination on the completely normalized coupling matrix obtained by synthesis by multiplying the rotation matrix to obtain an initial decoupling matrix which is used as a starting point for obtaining the decoupling matrix, wherein the eigenvalue and the eigenvector of the matrix are unchanged after the rotation elimination. The elimination sequence of the rotary elimination is from right to left and firstThe rows are arranged in a back row mode, the rows and the columns are selected according to the specific element elimination positions, the matrix forms obtained after element elimination is rotated are different, and the folding matrix is as follows:
after rotating and eliminating element, initially decoupling matrix MeIs a symmetric matrix, the main diagonal and both sides, i.e. the elements denoted by the letters s and m are non-zero, the elements denoted by the letters x and y and their symmetric positions with respect to the main diagonal are non-zero.
S5.2, carrying out numerical iteration decoupling transformation on the initial decoupling matrix after rotating elimination to obtain a decoupling matrix M meeting decoupling transformation conditionsd：
Optimizing convergence to decouple matrix MdWith initial decoupling matrix MeReflection coefficient S of11Or S22The sum of squared errors of (a) is used as an evaluation index;
by adopting an evolutionary algorithm, a group intelligence algorithm, a gradient algorithm or a hybrid optimization algorithm, a globally optimal decoupling matrix M meeting decoupling transformation conditions is automatically solvedd。
Further, the decoupling transition condition includes:
1) eigenvalues and eigenvectors of the matrix, or an approximation of the calculated S-parameters and the initial decoupling matrix;
2) elements except the first row, the first column and the last row are non-zero elements;
3) the non-zero elements must satisfy symmetry about both the major diagonal and the minor diagonal;
4) except the diagonal line and the elements at two adjacent sides, the absolute values of other non-zero elements are required to be consistent with the gap width rule of the actual filter along the direction of the main diagonal line.
Step S6, obtaining design sizes and S parameters of a plurality of groups of filters by adopting measurement or electromagnetic simulation, extracting a decoupling matrix according to the steps S2 to S5, and establishing a space mapping model of the design sizes and the decoupling matrix:
using a multiple-input multiple-output neural network model FANNEstablishing a decoupling matrix MdAnd a space mapping model with a design size, wherein the paradigm of the space mapping model is that L ═ fANN(Md，ω)；
Wherein, L is the design size parameter vector of the filter represented by the corresponding decoupling matrix; omega is an internal parameter of the space mapping model and is obtained by training L-Md sample data pairs; mdAre the decoupling matrices extracted for the sets of filters through steps S2 through S5.
Step S7, according to the expected design value, adjusting the decoupling matrix element of the initially designed filter through an optimization algorithm to obtain the decoupling matrix M of the filter coupling matrix close to the expected design valued-opt；
Decoupling matrix M for initially dimensioned filtersdOptimizing and iteratively adjusting the main diagonal line and the elements on two adjacent sides of the main diagonal line;
with decoupling matrix M in an iterative processdCalculating the reflection coefficient S11Or S22Calculating the error square sum of the scattering coefficient and the expected value;
adjusting decoupling matrix M by error inverse gradient propagation optimization algorithmdUntil the error meets the precision, obtaining a decoupling matrix M of the optimized filter coupling matrixd-opt。
Step S8, utilizing the space mapping model to obtain the decoupling matrix M of the optimized filter coupling matrixd-optAnd calculating a design parameter L.
The features and properties of the present invention are described in further detail below with reference to examples.
Example 1
The modeling and intelligent design method for the microstrip direct coupling filter provided by the embodiment, as shown in fig. 1, includes the following steps:
step S1, determining the structure and the initial design size of the filter, and acquiring the S parameter of the initial filter based on measurement or electromagnetic simulation;
in the step, determining a filter structure as shown in fig. 2, and an initial design size as shown in table 2, and acquiring an S parameter (scattering parameter) of a fifth-order microstrip direct coupling filter based on electromagnetic simulation, wherein the S parameter covers a working frequency band of the microstrip direct coupling filter;
step S2, calculating dephasing loading factors α and β of the S parameter obtained in the step S1 by adopting an optimization algorithm;
(1) initializing the dephasing loading factors α and β, setting the initialization range of α to pi · [0.9, 1.1], and the initialization range of β to pi · [0, 0.25 ];
(2) determining the S parameter S after dephasing loadingqS parameter S obtained in step S1mThe relationship of (1):
wherein f issIs the sampling frequency, j is the imaginary unit;
(3) the method comprises the following steps of taking an evaluation index calculation formula as an optimization objective function, adopting a genetic optimization algorithm, and finding out phase-removed loading factors α and β meeting the precision of an evaluation index through iterative automatic adjustment, wherein the evaluation index calculation formula is as follows:
wherein
Is the reflection coefficient calculated using the vector fitted Y parameter,
and
is the reflection coefficient calculated using the extracted coupling matrix after vector fitting,
andare the dephasing reflection coefficients calculated directly with the same set of dephasing loading factors.
If and only when the phase-removed loading factors α and β approach the actual values, the sum of the squares of the errors of the evaluation index calculation formula approaches 0, and the genetic optimization algorithm is adopted in the embodiment to calculate α -3.1434 and β -0.1541, the accuracy of the evaluation index calculation formula is optimal.
Step S3, obtaining a pole P and a residue R through vector fitting calculation by using the dephase loading factors α and β calculated in the step S2;
when α -3.1434 and β -0.1541 are used, the S parameter S after phase removal loading is calculatedqAnd admittance parameter YqThe S parameters before and after de-phase loading are shown in FIG. 3, and then the admittance parameter Y is calculatedqAnd (4) adopting a rational function to carry out vector fitting, thereby calculating the pole P and the residue R of the rational function. The rational function is:
where N denotes the order of the microstrip direct-coupled filter, and in this embodiment, a fifth-order microstrip direct-coupled filter is designed, where N is 5, s denotes the normalized frequency of the filter, j is an imaginary unit, and R is the imaginary unit11k、R12k、R21k、R21kAs admittance parameter YqResidue sum of approximate polynomial0Is a factor related to the finite transmission zero. The pole P and the residue R of the rational function obtained by calculation are shown in table 1.
Table 1:
| order k | 1 | 2 | 3 | 4 | 5 |
| Reflection parameter margin RS11 | 0.0845 | 0.1559 | 0.1037 | 0.1694 | 0.1413 |
| Insertion loss allowance RS21 | 0.0839 | -0.1556 | 0.1041 | -0.1705 | 0.1409 |
| Pole P | 1.4463i | 0.7075i | 1.4719i | 0.2654i | 0.4041i |
Step S4, carrying out complete standard coupling matrix synthesis by using the pole P and the residue R calculated in the step S3 to obtain a filter coupling matrix M;
step S5, a decoupling matrix M meeting the decoupling transformation condition is obtained by adopting numerical iteration decoupling transformation on the filter coupling matrix M obtained in the step S4d；
Step S5.1, the filter coupling matrix M obtained in the step S4 is rotated and eliminated to obtain an initial decoupling matrix Me；
Step S5.2, the initial decoupling matrix M after the rotation elimination is usedeObtaining decoupling matrix M meeting decoupling transformation conditions by adopting numerical iteration decoupling transformationd(ii) a Transforming the initial decoupling matrix M according to the filter structure shown in FIG. 2 and the matrix form of the decoupling matrix shown in FIG. 3eBefore iteration, the elements in the last column of row 2 need to be zeroed out, and the lower triangle position element about the secondary diagonal is replaced by the upper triangle position element.
Optimizing convergence to decouple matrix MdWith initial decoupling matrix MeReflection coefficient S of11Or S22The sum of squared errors of (a) is used as an evaluation index;
using genetic algorithm to initially decouple matrix MeAnd (5) carrying out preliminary solution, carrying out evolution for 40 times of iteration, and then converging to global optimum, and carrying out local optimization by adopting a gradient algorithm. When iteration meets the engineering precision condition, a decoupling matrix M obtained by decoupling transformation at the momentdWith initial decoupling matrix MeEquivalent in engineering precision, and obtaining a decoupling matrix M meeting decoupling transformation conditionsdComprises the following steps:
step S6, obtaining design sizes and S parameters of a plurality of groups of filters by adopting measurement or electromagnetic simulation, extracting a decoupling matrix according to the steps S2 to S5, and establishing a space mapping model of the design sizes and the decoupling matrix:
in this step, a multi-input multi-output neural network model F is adoptedANNEstablishing a decoupling matrix MdAnd a space mapping model with a design size, wherein the paradigm of the space mapping model is that L ═ fANN(Md，ω)；
Wherein, L is the design size parameter vector of the filter represented by the corresponding decoupling matrix, and can be directly used for the verification of simulation design software; omega is an internal parameter of the space mapping model and is obtained by training L-Md sample data pairs; mdAre the decoupling matrices extracted for the sets of filters through steps S2 through S5.
Step S7, according to the expected design value, adjusting the decoupling matrix element of the initially designed filter through an optimization algorithm to obtain the decoupling matrix M of the filter coupling matrix close to the expected design valued-opt；
In this step, the expected design value is an optimized design index of the microstrip direct coupling filter, such as an S-parameter curve shown in fig. 4, 5, and 6.
Decoupling matrix M for initially dimensioned filtersdThe main diagonal line and the two adjacent side elements of the main diagonal line are optimized and iteratively adjusted, namely elements m12, m23, m34, m22, m33 and m44 in the figure 3 and elements which are respectively symmetrically positioned about the main diagonal line and the auxiliary diagonal line, and the rest is kept unchanged;
with decoupling matrix M in an iterative processdCalculating the reflection coefficient S11Or S22Calculating the error square sum of the scattering coefficient and the expected value;
adjusting decoupling matrix M by error inverse gradient propagation optimization algorithmdUntil the error meets the precision, obtaining a decoupling matrix M of the optimized filter coupling matrixd-opt。
Step S8, utilizing the space mapping model to obtain the decoupling matrix M of the optimized filter coupling matrixd-optAnd calculating a design parameter L.
Table 2, a table of the design dimensions of the initial design and the optimized design and the coupling matrix elements:
after one round of optimization, the original filter, the ideal design index and the reflection coefficient S of the optimized filter are combined11And the insertion loss coefficient S22The curves in the frequency domain are plotted in fig. 5 and fig. 6, and it can be seen that the method can be adopted to converge to an ideal design effect through one round of optimization design based on the filter with poor initial performance, and the method is fast and effective.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and improvements made within the spirit and principle of the present invention are intended to be included within the scope of the present invention.
Claims (10)
1. A modeling and intelligent design method of a microstrip direct coupling filter is characterized by comprising the following steps:
step S1, determining the structure and the initial design size of the filter, and acquiring the S parameter of the initial filter based on measurement or electromagnetic simulation;
step S2, calculating dephasing loading factors α and β of the S parameter obtained in the step S1 by adopting an optimization algorithm;
step S3, obtaining a pole P and a residue R through vector fitting calculation by using the dephase loading factors α and β calculated in the step S2;
step S4, carrying out complete standard coupling matrix synthesis by using the pole P and the residue R calculated in the step S3 to obtain a filter coupling matrix M;
step S5, a decoupling matrix M meeting the decoupling transformation condition is obtained by adopting numerical iteration decoupling transformation on the filter coupling matrix M obtained in the step S4d；
Step S6, determining the design sizes of the multiple groups of filters, acquiring S parameters of the filters based on measurement or electromagnetic simulation, extracting a decoupling matrix according to the steps S2 to S5, and establishing a space mapping model of the design sizes and the decoupling matrix;
step S7, according to the expected design value, adjusting the decoupling matrix element of the initially designed filter through an optimization algorithm to obtain the decoupling matrix M of the filter coupling matrix close to the expected design valued-opt；
Step S8, utilizing the space mapping model to obtain the decoupling matrix M of the optimized filter coupling matrixd-optCalculating design parametersAnd (4) the number L.
2. The modeling and intelligent design method of microstrip direct coupling filter according to claim 1, wherein the step S2 is a method of calculating the dephase loading factors α and β for the S parameters obtained in step S1 by using an optimization algorithm, which comprises:
initializing dephasing loading factors α and β;
determining the S parameter S after dephasing loadingqS parameter S obtained in step S1mThe relationship of (1):
wherein f issIs the sampling frequency, j is the imaginary unit;
adjusting the dephasing loading factors α and β by an optimization algorithm to make it possible to adjust the S parameter S obtained in the step S1 within the engineering accuracymPhase removing and loading, namely, taking an evaluation index calculation formula as an optimization objective function, adopting an optimization algorithm, and finding phase removing and loading factors α and β meeting the precision of the evaluation index through iterative automatic adjustment, wherein the evaluation index calculation formula is as follows:
wherein
Is the reflection coefficient calculated using the vector fitted Y parameter,and
is the reflection coefficient calculated using the extracted coupling matrix after vector fitting,
and
are the dephasing reflection coefficients calculated directly with the same set of dephasing loading factors.
3. The method of claim 1, wherein the optimization algorithm is an evolutionary algorithm, a group intelligence algorithm, a gradient algorithm, or a hybrid optimization algorithm.
4. The modeling and intelligent design method of microstrip direct coupling filter according to claim 1, wherein the method of obtaining the pole P and the residue R by vector fitting calculation using the dephasing loading factors α and β calculated in step S2 in step S3 is:
step S3.1, calculating S parameter S after dephasing loading by using the dephasing loading factors α and β calculated in step S2qAnd admittance parameter Yq；
Step S3.2, rational function is adopted to the admittance parameter YqCarrying out vector fitting so as to calculate and obtain a pole P and a residue R of the rational function; the rational function is:
wherein N represents the order of the filter, s represents the normalized frequency of the filter, j is an imaginary unit, R11k、R12k、R21k、R21kAs admittance parameter YqResidue sum of approximate polynomial0Is a factor related to the finite transmission zero.
5. The modeling and intelligent design method of microstrip direct coupling filter according to claim 1, wherein in step S5, decoupling matrix satisfying decoupling transformation condition is obtained by applying numerical iterative decoupling transformation to filter coupling matrix M obtained in step S4MdThe method comprises the following steps:
step S5.1, the filter coupling matrix M obtained in the step S4 is rotated and eliminated to obtain an initial decoupling matrix Me；
S5.2, carrying out numerical iteration decoupling transformation on the initial decoupling matrix after rotating elimination to obtain a decoupling matrix M meeting decoupling transformation conditionsd。
6. The modeling and intelligent design method of the microstrip direct coupling filter according to claim 5, wherein in step S5.2, the decoupling matrix M satisfying the decoupling transformation condition is obtained by applying numerical iterative decoupling transformation to the initial decoupling matrix after rotating eliminationdThe method comprises the following steps:
optimizing convergence to decouple matrix MdWith initial decoupling matrix MeReflection coefficient S of11Or S22The sum of squared errors of (a) is used as an evaluation index;
by adopting an evolutionary algorithm, a group intelligence algorithm, a gradient algorithm or a hybrid optimization algorithm, a globally optimal decoupling matrix M meeting decoupling transformation conditions is automatically solvedd。
7. The method for modeling and intelligently designing a microstrip direct coupling filter according to claim 5 wherein the order of rotation elimination is from right to left, leading behind, alternating rows and columns.
8. The method of modeling and intelligent design of a microstrip direct coupled filter according to claim 5 wherein said decoupling transformation conditions comprise:
1) eigenvalues and eigenvectors of the matrix, or an approximation of the calculated S-parameters and the initial decoupling matrix;
2) elements except the first row, the first column and the last row are non-zero elements;
3) the non-zero elements must satisfy symmetry about both the major diagonal and the minor diagonal;
4) except the diagonal line and the elements at two adjacent sides, the absolute values of other non-zero elements are required to be consistent with the gap width rule of the actual filter along the direction of the main diagonal line.
9. The modeling and intelligent design method of microstrip direct coupling filter according to claim 1, wherein in step S6, the design size and S parameters of the multiple sets of filters are obtained by measurement or electromagnetic simulation, and the decoupling matrix is extracted according to steps S2 to S5, and the method of establishing the spatial mapping model of the design size and the decoupling matrix is: using a multiple-input multiple-output neural network model FANNEstablishing a decoupling matrix MdAnd a space mapping model with a design size, wherein the paradigm of the space mapping model is that L ═ fANN(Md,ω)；
Wherein, L is the design size parameter vector of the filter represented by the corresponding decoupling matrix; omega is an internal parameter of the space mapping model and is obtained by training L-Md sample data pairs; mdAre the decoupling matrices extracted for the sets of filters through steps S2 through S5.
10. The modeling and intelligent design method of microstrip direct coupling filter according to claim 1, wherein in step S7, the decoupling matrix element of the initially designed filter is adjusted by the optimization algorithm according to the expected design value to obtain the decoupling matrix M of the filter coupling matrix close to the expected design valued-optThe method comprises the following steps:
decoupling matrix M for initially dimensioned filtersdOptimizing and iteratively adjusting the main diagonal line and the elements on two adjacent sides of the main diagonal line;
with decoupling matrix M in an iterative processdCalculating the reflection coefficient S11Or S22Calculating the error square sum of the scattering coefficient and the expected value;
adjusting decoupling matrix M by error inverse gradient propagation optimization algorithmdUntil the error meets the precision, obtaining a decoupling matrix M of the optimized filter coupling matrixd-opt。
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