CN114567386B - High-precision channel group delay characteristic fitting and simulation implementation method, system, storage medium and communication system - Google Patents

Abstract

The invention discloses a high-precision channel group delay characteristic fitting and simulating method and system, which designs a complete set of complete high-precision navigation channel group delay characteristic fitting and simulating realization method and process, changes the mode that the traditional channel simulator only supports the pre-defined channel model to drive simulation, and has the capability of externally importing and reproducing various actual physical/user-defined channel characteristics through reasonable process design. The method is also suitable for simulation requirements of external channel amplitude characteristics, frequency characteristics and the like, improves the scene construction capacity of the channel simulator, expands the channel model category supported by the channel simulator, and effectively meets the actual requirements of various users for carrying out signal transceiving tests based on channel simulation equipment.

Description

High-precision channel group delay characteristic fitting and simulation method, system, and storage medium and communication system

technical field

The invention relates to the field of navigation channel simulation, in particular to a high-precision channel group delay characteristic fitting and simulation method and system.

Background technique

Channel simulators are widely used in the testing of various signal receiving and transmitting equipment in communication and navigation systems. They simulate real signal complex transmission channels for docking tests, so as to evaluate the signal receiving and transmitting performance of various equipment in actual use. Important build equipment to reproduce real-world test scenarios. A general channel simulator device can simulate according to an optional or pre-set channel characteristic mathematical model, and drive the device to adjust the channel characteristics of the radio frequency signal passing through the channel simulator.

However, the default pre-defined channel characteristic mathematical model can only represent the more typical transmission channel characteristics that can be modeled and analyzed. For many users to test the channel characteristics of each link in the signal transmission of different application background equipment, it cannot fully take into account and achieve accurate equivalence. , such as nonlinear distortion channels of high-power power amplifiers, non-ideal channels of repeating analog radio frequency equipment, and characteristic custom channels that meet specific user needs, etc., which are ubiquitous in actual use and have individual differences. .

Contents of the invention

The present invention aims to solve at least one of the technical problems existing in the prior art. For this reason, the present invention proposes a high-precision channel group delay characteristic fitting and simulation method and system, which can solve the problem that existing channel simulation devices cannot fully take into account and realize channels with accurate equivalent and individualized difference characteristics.

The high-precision channel group delay characteristic fitting and simulation implementation method according to the first aspect embodiment of the present invention includes the following steps:

S100. Build a channel simulation process that supports the import of delay data of external channel characteristics or custom channel characteristic groups;

S200. Formulate a standard data format for importing external data and constraint conditions for key parameters to be met, obtain external channel characteristics or custom channel characteristic targets, and then import the external data;

S300. Extract the imported external data sampling points according to the data extraction algorithm to obtain model fitting data and accuracy evaluation data;

S400. Perform approximate fitting on the imported group delay characteristic data based on the model fitting data, and obtain an expression of the group delay characteristic fitting result model;

S500. According to the evaluation method, the model fitting data is regarded as known, and the accuracy evaluation data is regarded as unknown, and the comprehensive accuracy evaluation is performed by comparing the group delay characteristic fitting result model;

S600. Formulate rules for selecting internal and external models, and then perform matching selection of internal and external channel group delay characteristic models according to the rules;

S700. According to the selected channel group delay characteristic model, simulate and drive the channel simulator to adjust the group delay characteristic of the radio frequency signal passing through the channel simulator.

The high-precision channel group delay characteristic fitting and simulation implementation method according to the embodiment of the first aspect of the present invention has at least the following technical effects: the embodiment of the present invention provides a complete set of high-precision navigation channel group delay characteristic fitting and simulation. The simulation implementation method and process have changed the traditional channel simulator that only supports the pre-defined channel model-driven simulation mode. Through reasonable process design, it has external import and high-precision fitting to reproduce various actual physical/user-defined channel characteristics. ability. The invention is also applicable to the simulation requirements of external channel amplitude characteristics, frequency characteristics, etc., improves the scene construction ability of the channel simulator, expands the scope of the channel model supported by it, and effectively satisfies all kinds of users for signal transmission and reception tests based on channel simulation equipment actual needs.

According to some embodiments of the present invention, the external data imported in the step S200 is in the form of an array, and the data type is a double-precision floating point number.

According to some embodiments of the present invention, the key parameters in the step S200 include the channel starting frequency f _L , the channel cut-off frequency f _H , the sampling point frequency f _n , the number of sampling data points L, and the group delay value τ _n corresponding to each sampling point , channel type, wherein n=1, 2, ..., L; the constraint expression that the key parameters need to satisfy is:

B _max ≥f _H -f _L

Where Bmax is the upper limit of the data channel bandwidth that can be supported.

According to some embodiments of the present invention, the specific steps of the data extraction algorithm in step S300 are as follows

S301. Calculate the inter-sampling time delay change rate value _Δn between adjacent sampling points;

S302. According to the calculated (L-1) delay change rate values, find the minimum value among them and set it as the mth one;

S303. Extract the sampling point f _m corresponding to the group delay value τ _m as part of the accuracy evaluation data, and recalculate the delay change rate Δ _n-1 according to the remaining sampling points after the sampling point f _m is extracted;

S304. According to the calculated (L-2) time delay change rates Δn _-1 , find the minimum value among them and assume that it is the kth, then extract the sampling point f _k corresponding to the group delay value τ _k as the accuracy In the evaluation data part, recalculate the delay change rate Δn _-2 according to the above remaining sampling points;

S305. Steps S302-S304 are repeated until the extraction and classification of model fitting data and precision evaluation data are completed according to the set ratio.

According to some embodiments of the present invention, the expression of the time delay change rate value _Δn between sampling points in the step S301 is:

Wherein, f _n , τ _n represent the frequency and time delay value of the nth sampling point, and f _n-1 , τ _n-1 represent the frequency and time delay value of the n-1th sampling point.

According to some embodiments of the present invention, the specific steps of the step S400 are as follows

S401. Perform N-order Fourier expansion of the model fitting data g(f _n1 ) of the actual group delay characteristic function within (-B/2, B/2) to obtain an approximate result function F(f _n1 ), and then The difference between the approximate result function F(f _n1 ) and the model fitting data g(f _n1 ) is obtained to obtain the residual component h(f _n1 );

S402. Using the effective inflection point value to divide the residual component h(f _n1 ) into intervals;

S403, start to calibrate from the first extreme point, if the frequency interval between the next extreme point and the previous extreme point is less than the judgment interval, discard the extreme point, and use the two endpoints of the residual component and each pole The value point is used as the end point of the interval to divide the interval, find the inflection point in each interval and take the smallest inflection point value as the effective inflection point value;

S404. Using the calibrated effective inflection point value, perform segmental polynomial fitting on the residual component according to the divided segmental interval, and obtain the residual component fitting result H(f _n1 );

S405. Add the residual component fitting result H(f _n1 ) to the Fourier approximation result F(f _n1 ), to obtain a complete group delay characteristic fitting result model expression g ^* (f _n1 ).

According to some embodiments of the present invention, the search range for finding the inflection point in the step S403 is the 25%-75% area of the center of the interval.

According to some embodiments of the present invention, the specific steps of the step S500 are as follows

S501. Evaluate the error between the group delay characteristic fitting result and known sampling points: make a difference between the group delay characteristic fitting result g ^* (f _n1 ) and the model fitting data part g(f _n1 ), Obtain the absolute value of the fitting error d(f _n1 ) of known sampling points, the expression of d(f _n1 ) is

d(f _n1 )＝|g ^* (f _n1 )-g(f _n1 )|;

S502. Evaluate the error between the group delay characteristic fitting result at the same frequency point and the unknown sampling point: bring all the sampling frequency point f _n2 data corresponding to the accuracy evaluation data g(f _n2 ) treated as the unknown point into the group The expression g ^* (f _n1 ) of the delay characteristic fitting result, obtains the group delay characteristic result g ^* (f _n2 ) corresponding to the frequency matching of the unknown point, and combines g ^* (f _n2 ) with the fitting data part g( Take the absolute value of the difference between f _n2 ), and obtain the unknown sampling point matching error d(f _n2 ), the expression of d(f _n2 ) is

d(f _n2 )＝|g ^* (f _n2 )-g(f _n2 )|;

S503. Fitting accuracy determination: set the fitting accuracy threshold D, and jointly evaluate known sampling points and unknown sampling points, if any sampling point contained in the two satisfies the following expression:

d(f _n1 )≤D

d(f _n2 )≤D

Then it is considered that it meets the fitting error judgment threshold, and the accuracy of the group delay characteristic fitting result model is judged according to the coverage of the fitting sampling point combined with the known sampling point and the unknown sampling point;

S504. Fitting model availability determination and iteration: If the accuracy determination of the group delay characteristic fitting result model is not available, return to step S400, increase one order on the basis of the original fitting, and perform N+1 order Fourier expansion, The subsequent steps are continued until the accuracy determination of the group delay characteristic fitting result model obtained in step S503 is available.

According to some embodiments of the present invention, the specific steps in the step S700 are

S701. Connect the required input and output radio frequency signals of the test object to the channel simulator through radio frequency cables;

S702. Operate the channel emulator simulation control software, set the channel simulation scene, acquire simulation objects, channel models and link relationships, and select internal and external channel models;

S702. Start channel simulation control, complete channel group delay characteristic simulation implementation according to external channel characteristics or self-defined channel characteristics, and output radio frequency signals superimposed with corresponding channel characteristics.

The high-precision channel group delay characteristic fitting and simulation system according to the embodiment of the second aspect of the present invention includes a channel simulation hardware platform and simulation control software, and the simulation control software includes

An external interface module, the external interface module is used for input parameter configuration and scene selection settings, and import data files;

A data extraction module, the external interface module is connected to the data extraction module for extracting externally imported data into model fitting data and accuracy evaluation data according to a data extraction algorithm;

A characteristic fitting module, the data extraction module is connected to the characteristic fitting module, so as to complete high-precision channel characteristic fitting calculation according to the model fitting data, and generate a group delay characteristic fitting result model obtained by fitting external data expression;

An accuracy evaluation module, the characteristic fitting module is connected to the accuracy evaluation module, so that according to the data fitting result, the model fitting data part is regarded as a known point, and the accuracy evaluation data part is regarded as an unknown point, and is based on the evaluation algorithm Accuracy evaluation of the fitted model expression from the fit;

A model matching module, the accuracy evaluation module is connected to the model matching module, and the model matching module is used to analyze various internal predefined channel models and channel models obtained by fitting external data, and perform adaptive matching;

A parameter calculation module, the model matching module is connected to the parameter calculation module, the parameter calculation module is used to perform simulation operations and calculate the fast-changing parameters required for channel characteristic simulation, and the parameter calculation module is connected to the channel simulation hardware platform for Enter the fast-changing parameters;

An operation control module, the operation control module is connected to the external interface module for importing external input parameters, and the operation control module is respectively connected to the model matching module and the channel simulation hardware platform for generating and outputting operation control instructions;

The channel simulation hardware platform is used to receive operation control instructions and various fast-changing parameters from the simulation control software, access external input radio frequency signals, implement channel simulation operations, and output external radio frequency signals.

The high-precision channel group delay characteristic fitting and simulation implementation method according to the embodiment of the second aspect of the present invention has at least the following technical effects: the embodiment of the present invention provides a complete set of high-precision navigation channel group delay characteristic fitting and simulation method. The simulation implementation method and process have changed the traditional channel simulator that only supports the pre-defined channel model-driven simulation mode. Through reasonable process design, it has external import and high-precision fitting to reproduce various actual physical/user-defined channel characteristics. ability. The invention is also applicable to the simulation requirements of external channel amplitude characteristics, frequency characteristics, etc., improves the scene construction ability of the channel simulator, expands the scope of the channel model supported by it, and effectively satisfies all kinds of users for signal transmission and reception tests based on channel simulation equipment actual needs.

According to the computer-readable storage medium of the embodiment of the third aspect of the present invention, the computer-readable storage medium stores computer instructions, and the computer instructions are used to make the computer perform the above-mentioned high-precision channel group delay characteristic fitting and Simulation method.

The high-precision channel group delay characteristic fitting and simulation implementation method according to the embodiment of the third aspect of the present invention has at least the following technical effects: the embodiment of the present invention provides a complete set of high-precision navigation channel group delay characteristic fitting and simulation. The simulation implementation method and process have changed the traditional channel simulator that only supports the pre-defined channel model-driven simulation mode. Through reasonable process design, it has external import and high-precision fitting to reproduce various actual physical/user-defined channel characteristics. ability. The invention is also applicable to the simulation requirements of external channel amplitude characteristics, frequency characteristics, etc., improves the scene construction ability of the channel simulator, expands the scope of the channel model supported by it, and effectively satisfies all kinds of users for signal transmission and reception tests based on channel simulation equipment actual needs.

The communication system according to the embodiment of the fourth aspect of the present invention includes:

at least one processor;

and a memory connected in communication with the at least one processor; wherein, the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the At least one processor executes the above-mentioned high-precision channel group delay characteristic fitting and simulation implementation method.

According to the fourth aspect of the present invention, the high-precision channel group delay characteristic fitting and simulation implementation method has at least the following technical effects: the embodiment of the present invention provides a complete set of high-precision navigation channel group delay characteristic fitting and simulation. The simulation implementation method and process have changed the traditional channel simulator that only supports the pre-defined channel model-driven simulation mode. Through reasonable process design, it has external import and high-precision fitting to reproduce various actual physical/user-defined channel characteristics. ability. The invention is also applicable to the simulation requirements of external channel amplitude characteristics, frequency characteristics, etc., improves the scene construction ability of the channel simulator, expands the scope of the channel model supported by it, and effectively satisfies all kinds of users for signal transmission and reception tests based on channel simulation equipment actual needs.

Additional aspects and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention.

Description of drawings

The above and/or additional aspects and advantages of the present invention will become apparent and comprehensible from the description of the embodiments in conjunction with the following drawings, wherein:

Fig. 1 is the flow chart of the high-precision navigation channel characteristic fitting and simulation implementation method in the embodiment of the present invention;

Fig. 2 is a functional block diagram of a high-precision channel group delay characteristic fitting and simulation system in an embodiment of the present invention;

Fig. 3 is a flow chart of high-precision fitting of channel group delay characteristics imported from outside in an embodiment of the present invention.

Detailed ways

Embodiments of the present invention are described in detail below, examples of which are shown in the drawings, wherein the same or similar reference numerals designate the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the figures are exemplary only for explaining the present invention and should not be construed as limiting the present invention.

In the description of the invention, it should be understood that the orientation descriptions, such as up, down, front, back, left, right, etc. indicated orientations or positional relationships are based on the orientations or positional relationships shown in the drawings, and are only for the purpose of It is convenient to describe the present invention and simplify the description, but does not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operate in a specific orientation, and thus should not be construed as limiting the present invention.

In the description of the invention, several means one or more, and multiple means more than two. Greater than, less than, exceeding, etc. are understood as not including the original number, and above, below, within, etc. are understood as including the original number. If the description of the first and second is only for the purpose of distinguishing the technical features, it cannot be understood as indicating or implying the relative importance or implicitly indicating the number of the indicated technical features or implicitly indicating the order of the indicated technical features relation.

In the description of the present invention, unless otherwise clearly defined, words such as setting, installation, and connection should be understood in a broad sense, and those skilled in the art can reasonably determine the specific meanings of the above words in the present invention in combination with the specific content of the technical solution.

The channel simulator obtains the simulation object, channel model and link relationship based on the setting of the simulation scene. The channel model description objects mainly include ionosphere, troposphere, multipath fading, antenna, radio frequency channel, power amplification and other links related to signal transmission. All of the above objects have different classical mathematical models to choose from, which are used to calculate the fast-changing parameters related to various signal power, frequency, delay, phase and other characteristics required for channel simulation. Considering that many users test the channel characteristics of each link of signal transmission of equipment with different application backgrounds, there are individual differences, and various preset mathematical models cannot achieve full consideration and accurate equivalence. The channel simulator needs to have open data import Interface, import and fit different types of external non-ideal channel characteristics and custom channel characteristics that meet user needs to obtain corresponding mathematical models, and use them equivalently with various predefined mathematical models to support external import And realize the function of high-precision channel simulation.

As shown in Figure 1, a high-precision channel group delay characteristic fitting and simulation implementation method includes the following steps:

S100. Build a channel simulation process that supports the import of delay data of external channel characteristics or custom channel characteristic groups;

S200. Formulate a standard data format for importing external data and constraint conditions for key parameters to be satisfied, obtain external channel characteristics or user-defined channel characteristic targets, and then import external data to obtain channel bandwidth for imported data;

S300. Extract the imported data sampling points according to the data extraction algorithm to obtain model fitting data and accuracy evaluation data;

S400. Perform approximate fitting on the imported group delay characteristic data based on the model fitting data, and obtain an expression of the group delay characteristic fitting result model;

S500. Treat the model fitting data as known and the accuracy evaluation data as unknown according to a preset evaluation method, and compare the group delay characteristic fitting result model with a comprehensive accuracy evaluation;

S600. Formulate rules for selecting internal and external models, and then perform matching selection of internal and external channel group delay characteristic models according to the rules;

S700. According to the selected channel group delay characteristic model, simulate and drive the channel simulator to adjust the group delay characteristic of the radio frequency signal passing through the channel simulator.

Among them, it supports the external import process architecture design link, constructing a channel simulation process that supports the delay data import of external channel characteristics or custom channel characteristic groups; the import data standard format and parameter design link, formulating the standard data format and key parameter requirements for external data import. Satisfied constraints, obtain external channel characteristics or custom channel characteristic targets, and then import external data to obtain imported data channel bandwidth; import data sampling point extraction grouping design link, according to the set extraction algorithm, extract imported data into models The fitting data part (accounting for about 90%-95%) and the accuracy evaluation data part (accounting for about 5%-10%); the high-precision group delay characteristic fitting design link is to carry out the fitting data part of the above model Fourier decomposition approximation fitting, the difference curve generated by Fourier decomposition is fitted by piecewise second-order polynomial based on the least square method, and the model expression of the imported group delay characteristic high-precision fitting result is obtained by adding ;In the link of automatic evaluation of fitting accuracy and iterative design, according to the data fitting results, the part of the above-mentioned model fitting data is regarded as a known point, and the part of the above-mentioned accuracy evaluation data is regarded as an unknown point, and based on the set evaluation algorithm, the fitting accuracy is calculated. Evaluation; the matching design link of internal and external channel models is to judge the matching of internal and external channel models on the premise that the fitting model meets the requirements through the accuracy evaluation results, and supports optional implementation mechanism design to support users in specific models Combination selection operation implementation; channel characteristic simulation implementation process link design is the operation control process for the specific implementation of the channel simulation process, which is used to drive the device to perform specific operations according to the selected channel model. details as follows:

S100. Build a channel simulation process that supports the import of external channel characteristics or user-defined channel characteristic group delay data. This step is used to import channel group delay characteristic parameters, and replace the steps related to the group delay characteristic operation in the link with the amplitude characteristic operation. It can be used to import channel amplitude characteristic parameters.

S200. Mainly complete the formulation of the standard data format for external data import and the declaration and definition of relevant key parameters, as follows:

S201 external data is imported in the form of an array, the data type is double-precision floating point number (float), the file format is *.txt text, and the upper limit of the supported channel bandwidth is Bmax. Relevant key parameters mainly include channel starting frequency f _L (unit MHZ), channel cut-off frequency f _H (unit MHZ), sampling point frequency f _n (unit MHZ) where n=1, 2, ..., L, the number of sampling data points L (unit 1), the group delay value τ _n (unit ns) corresponding to each sampling point, and the channel type (including ionosphere, troposphere, multipath, antenna, radio frequency, power amplifier, etc.) need to be declared. The above standard data format and definition of key parameters are just examples. In actual design and implementation, other data formats and parameter definition forms can be used, and are not limited to the import of group delay characteristic parameters, and can also be used to import parameters such as amplitude characteristics and frequency characteristics.

S202 , agree on the relationship between the parameters. The above-mentioned related key parameter settings need to meet specific constraints, and the expressions are as follows:

B _max ≥f _H -f _L

Wherein, the parameters in the above formula are the same as those defined in step S201. Relevant key parameters that meet the above constraints can only be matched with relevant operations and data verification in the subsequent import process.

S203. Obtain an external channel feature or a custom channel feature target. For external channel targets, instruments and equipment such as vector network analyzers and high-speed oscilloscopes can be used to measure channel group delay characteristics; for user-defined channel characteristic targets, Matlab or other mathematical software can be used to generate custom data. In this way, the sampling point function g(f _n ) of the imported channel group delay characteristics is obtained, and standardized processing is performed according to the defined standard data format, and key parameter declaration definitions are added at the same time, so as to obtain data files that can be imported into the channel simulator.

S204, an operation of importing external data. Operate the channel simulator simulation control software, click the user-defined feature option, select to load the data file into the specified file directory, and after the data import is completed, the data format and parameter definition will be checked. If all of them meet the requirements, "data format does not match" will pop up , and give a specific prompt, if it meets the requirements, the loading can be completed.

S205. Obtain bandwidth of the imported data channel. Further automatically calculate and obtain the channel bandwidth B according to the definition of key parameters, the expression is as follows:

B＝ _fH - _fL

The channel bandwidth B is used in subsequent data fitting operations.

S300. Extract the imported data sampling points according to the data extraction algorithm to obtain model fitting data and accuracy evaluation data, which mainly includes the following steps:

S301. Import data sampling point classification. In order to effectively evaluate the accuracy of the channel model expression obtained by subsequent fitting, the externally imported data is defined as g(f _n ), which is extracted into two parts: model fitting data g(f _n1 ) and precision evaluation data g(f _n2 ), The model fitting data part g(f _n1 ) will be regarded as known data, which is used to simulate and generate the channel model expression, and at the same time, it is used to check and evaluate the accuracy of the fitted model expression obtained by fitting the known data, and the precision evaluation data Part g(f _n2 ) will be used as an unknown data point in the accuracy evaluation of the fitted model expression obtained from the fitting for comparative evaluation.

S302. A method for extracting data sampling points is imported. There are fluctuations in the channel group delay characteristics. In order to refer to the effective fluctuation information as much as possible during the fitting and improve the fitting accuracy, the time delay change rate between adjacent sampling points is used as the judgment basis. The change rate A larger value means that the fluctuation here is large, and the effective information content of the sampling point is high, which is classified as the model fitting data part. Accuracy evaluation data. The above-mentioned delay change rate value between sampling points is calculated according to the group delay value and its frequency interval between adjacent sampling points, and the delay change rate _Δn expression is as follows:

In the formula, f _n , τ _n represent the frequency and delay value of the nth sampling point, f _n-1 , τ _n-1 represent the frequency and delay value of the n-1th sampling point, and the delay change rate Δ _n It is used to judge the magnitude of the delay characteristic fluctuation between adjacent sampling points.

S303. Data extraction algorithm setting. According to the calculated (L-1) delay change rates, find the minimum value and assume that it is the mth one, the expression is as follows:

minΔ _n =min{Δ ₁ ,Δ ₂ ,…Δ _n }=Δ _m

Then extract the sampling point f _m corresponding to the group delay value τ _m as part of the accuracy evaluation data, and the corresponding frequency points of all remaining sampling points are expressed as follows:

{f ₁ ,f ₂ ,…f _m-1 ,f _m+1 …f _n }

According to the above remaining sampling points, recalculate the delay change rate Δn _-1 , because the sampling point f _m corresponding to the group delay value τ _m has been extracted, and f _m-1 and f _m+1 are adjacent samples point. At this time, the delay change rate Δ _m is expressed as follows:

Calculation methods for other time delay change rates Δn _-1 points remain unchanged. According to the calculated (L-2) time delay change rates Δ _n-1 , find the minimum value and assume it is the kth, then extract the sampling point f _k corresponding to the group delay value τ _k as the accuracy evaluation data part, according to the above remaining sampling points, recalculate the delay change rate Δn _-2 ...;

S304. Complete the extraction and classification of model fitting data and precision evaluation data according to a set ratio. Set the proportion of data points in the part of the target model fitting data of the extraction ratio, taking 90% as an example, the proportion of data points in the accuracy evaluation data part is 10%.

Assume that the number of frequency points corresponding to the model fitting data part after extraction is n1, corresponding to the sampling frequency f _n1 respectively, the number of frequency points corresponding to the accuracy evaluation data part is n2, corresponding to the sampling frequency f _n2 , and the natural numbers n1 and n2 and the total number of sampling points L satisfy the following expression:

L=n1+n2

Then the model fitting data part after extraction can be expressed as g(f _n1 ), and the accuracy evaluation data part can be expressed as g(f _n2 ). Repeat the process of finding and extracting the minimum value in the above step S304 until g(f _n2 ) data points account for 10%, and all sampling points that have not been extracted are classified as g(f _n1 ), and the data points account for 90%.

S400. Perform approximate fitting on the imported group delay characteristic data based on the model fitting data, and obtain the expression of the group delay characteristic fitting result model, as shown in FIG. 3 , mainly including the following steps:

S401. Perform N-order Fourier expansion of the model fitting data part g(f _n1 ) of the actual group delay characteristic function within (-B/2, B/2) to obtain an approximate result function F(f _n1 ). Due to the Gibbs effect produced by Fourier decomposition, the residual between the approximate result F(f _n1 ) and g(f _n1 ) has certain volatility, so the difference between the two is obtained to obtain the residual component h(f The expression of _n1 ) is as follows:

Wherein, a _i and b _i are Fourier coefficients, i=1, 2, . . . , N, and a ₀ is an initial coefficient.

S402. Using the effective inflection point value to segment the residual component into intervals. Considering that in the actual process, due to measurement conditions and interference, there are local small-scale fluctuations in the difference curve, that is, there are multiple extreme points. Under the condition of N-order Fourier decomposition, in order to avoid local small-scale fluctuations on the Subsequent segment interval selection will have an impact, and extreme point calibration of the residual component is required. Merge the part from the leftmost end of the difference curve to the first extreme point and the part from the last extreme point to the rightmost end of the difference curve into one section, and each section between adjacent extreme points, then the whole difference curve is divided into 2N+1 segment, the expression of the judgment interval Δ is as follows:

Among them, k is a decimal between 0 and 1, and generally takes a value between 0.7-0.9.

S403, start to calibrate from the first extreme point, if the frequency interval between the next extreme point and the previous extreme point is less than the judgment interval, discard the extreme point, and use the two endpoints of the residual component and each pole The value point is used as the end point of the interval to divide the interval, and the inflection point is found in each interval and the smallest inflection point value is taken as the effective inflection point value. The recommended search range for finding the inflection point is the 25%-75% area of the interval center. For different residual components and different Fourier decomposition orders, the search interval can be appropriately widened with a 5% gradient to ensure that each interval finds an inflection point.

S404. Using the calibrated effective inflection point value, perform piecewise polynomial fitting on the residual component according to the divided piecewise intervals. The endpoints of the segmented interval are the two endpoints of the residual component and the effective inflection point values. The number of intervals is 2N+2, and quadratic polynomial fitting is performed in each interval to obtain 2N+2 second-order polynomial fittings of the residual component. The equation is as follows:

Wherein H(f _n1 ) is a polynomial fitting function, k _i,j are fitting coefficients, i=1,...,2N+2; j=0,1,2.

S405. Adding the residual component fitting result H(f _n1 ) and the Fourier approximation result F(f _n1 ) to obtain a complete group delay characteristic fitting result g ^* (f _n1 ), the expression is as follows:

S500. Taking the model fitting data as known and the accuracy evaluation data as unknown according to the preset evaluation method, and comparing the group delay characteristic fitting result model to perform comprehensive accuracy evaluation, which mainly includes the following steps:

S501. Evaluate an error between a group delay characteristic fitting result and a known sampling point. By making the difference between the above result g ^* (f _n1 ) and the model fitting data part g(f _n1 ), the absolute value of the fitting error d(f _n1 ) of the known sampling points can be obtained, and the expression is as follows:

d(f _n1 )＝|g ^* (f _n1 )-g(f _n1 )|

S502. Evaluate an error between a group delay characteristic fitting result at the same frequency point and an unknown sampling point. Because the fitting result of group delay characteristics g ^* (f _n1 ) is a continuous model function of a known expression, the data of all sampling frequency points f _n2 corresponding to the accuracy evaluation data g(f _n2 ) treated as unknown points are brought into the expression Formula g ^* (f _n1 ), the group delay characteristic result g ^* (f _n2 ) corresponding to the frequency matching of the unknown point can be obtained, the expression is as follows:

Taking the absolute value of the difference between it and the fitted data part g(f _n2 ), the matching error d(f _n2 ) of the unknown sampling point can be obtained, and the expression is as follows:

d(f _n2 )＝|g ^* (f _n2 )-g(f _n2 )|

S504, a fitting accuracy determination method. Set the fitting accuracy threshold D, and jointly evaluate the known sampling points and unknown sampling points, if any sampling point contained in the two satisfies the following expression:

d(f _n1 )≤D

d(f _n2 )≤D

Then it is considered that it meets the fitting error judgment threshold. Assuming that the total number of sampling points meeting the above requirements is L ₀ , the sampling point coverage S is defined as:

Where L is the total number of sampling points. The fitting accuracy of g ^* (f _n1 ) obtained in step S405 can be judged according to the combined fitting sampling point coverage of known sampling points and unknown sampling points.

S503, determining and iterating the availability of the fitting model. In order to combine d(f _n1 ) to determine the fitting accuracy of known sampling points, combined with d(f _n2 ) to determine the fitting accuracy of unknown sampling points, according to the set joint accuracy determination requirements of known points and unknown points, automatically determine the group time Extend the availability of the characteristic fitting result g ^* (f _n1 ), if it is not available, return to step S401, increase the first order on the original basis, perform N+1 order Fourier expansion, and continue the subsequent steps until the group time in step S503 Continue until the characteristic fitting result g ^* (f _n1 ) is available; if available, continue to the next step. The following is a complete implementation example to illustrate the above-mentioned group delay characteristic fitting method. The group delay measurement accuracy of the corresponding vector network analyzer is 0.1 ns, 401 sampling points, and the difference under the third-order Fourier decomposition is used. Segmented fitting, the results show that the absolute value of the difference between 399 fitting points and sampling points is less than 0.1 ns, and the coverage rate of sampling points is 99.5%, which meets the internal predefined fitting error conditions.

S600. Formulate rules for selecting internal and external models, and then perform matching selection of internal and external channel group delay characteristic models according to the rules, mainly including the following steps:

S601. Type matching analysis of internal and external channel models. In the internal and external channel model, channels of the same type are mutually exclusive during user configuration, and only one can be selected, and there is no conflict between different types of channels. The results of automatic analysis by the software will be displayed on the operation interface of channel model selection for users to click and use. Internal and external channel models with conflicting types do not support simultaneous selection.

S602. The internal and external channel model matching selection strategy support. Support to bypass the same type of original channel model and only use the fitting result model, or use different types of original channel and fitting result models in series, or only select some types of internal and external channel models to bypass other types Internal and external channel models.

S603. The user selects the internal and external channel models by himself according to the support strategy in step S602 according to the test requirements. After the selection is completed, the externally imported channel characteristic model of the channel simulator is automatically imported into the background calculation process to calculate various fast-changing parameters required for channel characteristic changes.

S700. According to the selected channel group delay characteristic model, the simulation drives the channel simulator to adjust the group delay characteristic of the radio frequency signal passing through the channel simulator, mainly including the following steps:

S701. Connect the input and output radio frequency signals required by the test object to the channel simulator through radio frequency cables, and provide peripheral conditions such as power supply and time-frequency signals necessary for the equipment to work.

S702. Operate the simulation control software of the channel simulator to set the channel simulation scene to obtain simulation objects, channel models and link relationships. The channel model description objects mainly include ionosphere, troposphere, multipath fading, antenna, radio frequency channel, power For all links involving signal transmission such as amplification, the above objects have different classical mathematical models to choose from, which are used to calculate the fast-changing parameters related to various signal power, frequency, delay, phase and other characteristics required for channel simulation, according to The support strategy described in step S602 selects the internal and external channel models by itself, and simultaneously sets other necessary parameters for the operation of the channel simulation equipment.

S702. Start channel simulation control, complete channel group delay characteristic simulation implementation according to external channel characteristics or self-defined channel characteristics, and output radio frequency signals superimposed with corresponding channel characteristics.

Referring to Fig. 2, the present invention also discloses a high-precision channel group delay characteristic fitting and simulation system, including a channel simulation hardware platform and simulation control software, and the simulation control software includes an external interface module, a data extraction module, a characteristic simulation Integration module, accuracy evaluation module, model matching module, parameter calculation module, operation control module, etc. Among them, the external interface module mainly completes the necessary parameter configuration for user setting input, scene selection setting access, external imported data file access, etc.; the data extraction module mainly extracts external imported data as model fitting data part and accuracy according to the established algorithm. Evaluate the data part; the characteristic fitting module completes the high-precision channel characteristic fitting calculation according to the model fitting data part, and generates the fitted model expression obtained by fitting the external data; the precision evaluation module evaluates the fitting accuracy in two parts, and according to the data fitting As a result, the model fitting data part is regarded as a known point, and the precision evaluation data part is regarded as an unknown point, and based on the set evaluation algorithm, the precision evaluation of the fitted model expression obtained by fitting is carried out; the model matching module mainly includes the analysis internal pre- The channel models obtained by fitting various defined channel models and external data are adaptively matched for user selection and configuration; the parameter calculation module performs simulation operations according to the settings of the channel model module, and calculates and obtains various types of fast parameters required for channel characteristic simulation. Variable parameters; the operation control module mainly completes the generation of various operation control instructions necessary for the operation of the simulation control software and the channel simulation hardware platform.

The channel simulation hardware platform receives operation control instructions and various fast-changing parameters from the simulation control software, accesses external input radio frequency signals, implements channel simulation operations, and outputs external radio frequency signals.

The present invention also provides a computer-readable storage medium, the computer-readable storage medium stores computer instructions, and the computer instructions are used to make the computer perform the above-mentioned high-precision channel group delay characteristic fitting and Simulation method.

The readable storage medium can be used to store non-transitory software programs, non-transitory computer executable programs and modules, such as program instructions/modules corresponding to the control method in the embodiments of the present disclosure.

One or more modules are stored in the storage medium, and when executed by one or more processors, the high-precision channel group delay characteristic fitting and simulation implementation method is executed.

Those skilled in the art can understand that all or part of the processes in the methods of the above-mentioned embodiments can be completed by instructing related hardware through computer programs, and the programs can be stored in a computer-readable storage medium. , may include the processes of the embodiments of the above-mentioned control methods. Wherein, the storage medium may be a magnetic disk, an optical disk, a read-only memory (Read-OnlyMemory, ROM), a random access memory (RandomAccessMemory, RAM), a flash memory (FlashMemory), a hard disk (HardDiskDrive, abbreviated: HDD) or A solid-state drive (Solid-State Drive, SSD), etc.; the storage medium may also include a combination of the above-mentioned types of memories.

It should be noted that the steps shown in the flowcharts of the accompanying drawings may be performed in a computer system, such as a set of computer-executable instructions, and that although a logical order is shown in the flowcharts, in some cases, The steps shown or described may be performed in an order different than here.

The invention also relates to a communication system comprising:

at least one processor;

and a memory connected in communication with the at least one processor; wherein, the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the At least one processor executes the above-mentioned high-precision channel group delay characteristic fitting and simulation implementation method.

It may also include: an input device and an output device.

Processors, memory, input devices, and output devices may be connected by a bus or otherwise.

The processor may be a central processing unit (Central Processing Unit, CPU). The processor can also be other general-purpose processors, digital signal processors (Digital Signal Processor, DSP), application-specific integrated circuits (Application Specific Integrated Circuit, ASIC), field-programmable gate array (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gates Or chips such as transistor logic devices, discrete hardware components, or a combination of the above types of chips. A general-purpose processor may be a microprocessor, or the processor may be any conventional processor, or the like.

As a computer-readable storage medium, the memory can be used to store non-transitory software programs, non-transitory computer-executable programs and modules, such as program instructions/modules corresponding to the control method in the embodiments of the present disclosure. The processor executes various functional applications and data processing of the server by running the non-transient software programs, instructions and modules stored in the memory, that is, realizes the high-precision channel group delay characteristic fitting and simulation realization of the above method embodiment method.

The memory may include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application program required for at least one function; the data storage area may store data created according to use of the processing device operated by the server, and the like. In addition, the memory may include high-speed random access memory, and may also include non-transitory memory, such as at least one magnetic disk storage device, flash memory device, or other non-transitory solid-state storage devices. In some embodiments, the memory may optionally include memory located remotely from the processor, and such remote memory may be connected to the network connection device via a network. Examples of the aforementioned networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

The input device can receive input numbers or character information, and generate key signal input related to user setting and function control of the processing device of the server. The output device may include a display device such as a display screen.

It should be noted that the steps shown in the flowcharts of the accompanying drawings may be performed in a computer system, such as a set of computer-executable instructions, and that although a logical order is shown in the flowcharts, in some cases, The steps shown or described may be performed in an order different than here.

Although the embodiments of the present disclosure have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the present disclosure, and such modifications and variations all fall within the scope of the appended claims. within the limited range.

The present invention designs a complete set of high-precision navigation channel group delay characteristic fitting and simulation implementation methods and processes, which changes the traditional channel simulator that only supports the pre-defined channel model-driven simulation mode, and through reasonable process design, has The ability of external import and high-precision fitting to reproduce various actual physical/user-defined channel characteristics. This method is also applicable to the simulation requirements of external channel amplitude characteristics, improves the scene construction ability of the channel simulator, expands the scope of the channel model it supports, and effectively meets the actual needs of various users for signal transmission and reception testing based on channel simulation equipment.

The embodiments of the present invention have been described in detail above in conjunction with the accompanying drawings, but the present invention is not limited to the above embodiments. Within the scope of knowledge possessed by those of ordinary skill in the technical field, various modifications can be made without departing from the gist of the present invention. kind of change.

Claims (8)

1. A high-precision channel group time delay characteristic fitting and simulation method, is characterized in that, comprises the following steps: S100. Build a channel simulation process that supports the import of delay data of external channel characteristics or custom channel characteristic groups; S200. Formulate a standard data format for importing external data and constraint conditions for key parameters to be met, obtain external channel characteristics or custom channel characteristic targets, and then import the external data; S300. Extract the imported external data sampling points according to the data extraction algorithm to obtain model fitting data and accuracy evaluation data; S400. Perform approximate fitting on the imported group delay characteristic data based on the model fitting data, and obtain an expression of the group delay characteristic fitting result model; S500. According to the evaluation method, the model fitting data is regarded as known, and the accuracy evaluation data is regarded as unknown, and the comprehensive accuracy evaluation is performed by comparing the group delay characteristic fitting result model; S600. Formulate rules for selecting internal and external models, and then perform matching selection of internal and external channel group delay characteristic models according to the rules; S700. According to the selected channel group delay characteristic model, the simulation drives the channel simulator to adjust the group delay characteristic of the radio frequency signal passing through the channel simulator; Key parameters in the step S200 include channel start frequency f _L , channel cutoff frequency f _H , sampling point frequency f _n , number of sampling data points L, group delay value τ _n corresponding to each sampling point, and channel type, where n=1 , 2, ..., L; the expression of the constraint conditions that the key parameters need to satisfy is:

B _max ≥f _H -f _L Where Bmax is the upper limit of the data channel bandwidth that can be supported; The specific steps of the data extraction algorithm in the step S300 are S301. Calculate the inter-sampling time delay change rate value _Δn between adjacent sampling points; S302. According to the calculated (L-1) delay change rate values, find the minimum value among them and set it as the mth one; S303. Extract the sampling point f _m corresponding to the group delay value τ _m as part of the accuracy evaluation data, and recalculate the delay change rate Δ _n-1 according to the remaining sampling points after the sampling point f _m is extracted; S304. According to the calculated (L-2) time delay change rates Δn _-1 , find the minimum value among them and assume that it is the kth, then extract the sampling point f _k corresponding to the group delay value τ _k as the accuracy In the evaluation data part, recalculate the delay change rate Δn _-2 according to the above remaining sampling points; S305. Steps S302-S304 are repeated until the extraction and classification of model fitting data and accuracy evaluation data are completed according to the set ratio; The specific steps of the step S400 are S401. Perform N-order Fourier expansion of the model fitting data g(f _n1 ) of the actual group delay characteristic function within (-B/2, B/2) to obtain an approximate result function F(f _n1 ), and then The difference between the approximate result function F(f _n1 ) and the model fitting data g(f _n1 ) is obtained to obtain the residual component h(f _n1 ); S402. Using the effective inflection point value to divide the residual component h(f _n1 ) into intervals; S403, start to calibrate from the first extreme point, if the frequency interval between the next extreme point and the previous extreme point is less than the judgment interval, discard the extreme point, and use the two endpoints of the residual component and each pole The value point is used as the end point of the interval to divide the interval, find the inflection point in each interval and take the smallest inflection point value as the effective inflection point value; S404. Using the calibrated effective inflection point value, perform segmental polynomial fitting on the residual component according to the divided segmental interval, and obtain the residual component fitting result H(f _n1 ); S405. Add the residual component fitting result H(f _n1 ) to the Fourier approximation result F(f _n1 ) to obtain a complete group delay characteristic fitting result model expression g ^* (f _n1 ); The concrete steps of described step S500 are S501. Evaluate the error between the group delay characteristic fitting result and known sampling points: make a difference between the group delay characteristic fitting result g ^* (f _n1 ) and the model fitting data part g(f _n1 ), Obtain the absolute value of the fitting error d(f _n1 ) of known sampling points, the expression of d(f _n1 ) is d(f _n1 )＝|g ^* (f _n1 )-g(f _n1 )|; S502. Evaluate the error between the group delay characteristic fitting result at the same frequency point and the unknown sampling point: bring all the sampling frequency point f _n2 data corresponding to the accuracy evaluation data g(f _n2 ) treated as the unknown point into the group The expression g ^* (f _n1 ) of the delay characteristic fitting result, obtains the group delay characteristic result g ^* (f _n2 ) corresponding to the frequency matching of the unknown point, and combines g ^* (f _n2 ) with the fitting data part g( Take the absolute value of the difference between f _n2 ), and obtain the unknown sampling point matching error d(f _n2 ), the expression of d(f _n2 ) is d(f _n2 )＝|g ^* (f _n2 )-g(f _n2 )|; S503. Fitting accuracy determination: set the fitting accuracy threshold D, and jointly evaluate known sampling points and unknown sampling points, if any sampling point contained in the two satisfies the following expression: d(f _n1 )≤D d(f _n2 )≤D Then it is considered that it meets the fitting error judgment threshold, and the accuracy of the group delay characteristic fitting result model is judged according to the coverage of the fitting sampling point combined with the known sampling point and the unknown sampling point; S504. Fitting model availability determination and iteration: if the accuracy determination of the group delay characteristic fitting result model is not available, return to step S400, increase one order on the basis of the original fitting, and perform N+1 order Fourier expansion, Continue the subsequent steps until the accuracy determination of the group delay characteristic fitting result model obtained in step S503 is available; The specific steps of the step S600 are S601. Type matching analysis of internal and external channel models; S602. Matching selection strategies for internal and external channel models; S603. The user selects the internal and external channel models by himself according to the support strategy in step S602 according to the test requirements. 2. The method for fitting and simulating high-precision channel group delay characteristics according to claim 1, characterized in that: in the step S200, the external data is imported in the form of an array, and the data type is a double-precision floating-point number. 3. The high-precision channel group time delay characteristic fitting and simulation implementation method according to claim 1, is characterized in that: the expression of the time delay change rate value Δ _n between sampling points in the step S301 is

Wherein, f _n , τ _n represent the frequency and time delay value of the nth sampling point, and f _n-1 , τ _n-1 represent the frequency and time delay value of the n-1th sampling point. 4. The high-precision channel group delay characteristic fitting and simulation method according to claim 1, characterized in that: the search range for finding the inflection point in the step S403 is the 25%-75% area of the center of the interval. 5. The high-precision channel group time delay characteristic fitting and simulation implementation method according to claim 1, is characterized in that: the concrete steps in the described step S700 are S701. Connect the required input and output radio frequency signals of the test object to the channel simulator through radio frequency cables; S702. Operate the channel emulator simulation control software, set the channel simulation scene, acquire simulation objects, channel models and link relationships, and select internal and external channel models; S702. Start channel simulation control, complete channel group delay characteristic simulation implementation according to external channel characteristics or self-defined channel characteristics, and output radio frequency signals superimposed with corresponding channel characteristics. 6. A high-precision channel group time delay characteristic fitting and simulation system for performing any one of the methods of claims 1-5 is characterized in that it includes a channel simulation hardware platform and simulation control software, and the simulation control software includes An external interface module, the external interface module is used for input parameter configuration and scene selection settings, and import data files; A data extraction module, the external interface module is connected to the data extraction module for extracting externally imported data into model fitting data and accuracy evaluation data according to a data extraction algorithm; A characteristic fitting module, the data extraction module is connected to the characteristic fitting module, so as to complete high-precision channel characteristic fitting calculation according to the model fitting data, and generate a group delay characteristic fitting result model obtained by fitting external data expression; An accuracy evaluation module, the characteristic fitting module is connected to the accuracy evaluation module, so that according to the data fitting result, the model fitting data part is regarded as a known point, and the accuracy evaluation data part is regarded as an unknown point, and is based on the evaluation algorithm Accuracy evaluation of the fitted model expression from the fit; A model matching module, the accuracy evaluation module is connected to the model matching module, and the model matching module is used to analyze various internal predefined channel models and channel models obtained by fitting external data, and perform adaptive matching; A parameter calculation module, the model matching module is connected to the parameter calculation module, the parameter calculation module is used to perform simulation operations and calculate the fast-changing parameters required for channel characteristic simulation, and the parameter calculation module is connected to the channel simulation hardware platform for Enter the fast-changing parameters; An operation control module, the operation control module is connected to the external interface module for importing external input parameters, and the operation control module is respectively connected to the model matching module and the channel simulation hardware platform for generating and outputting operation control instructions; The channel simulation hardware platform is used to receive operation control instructions and various fast-changing parameters from the simulation control software, access external input radio frequency signals, implement channel simulation operations, and output external radio frequency signals. 7. A computer-readable storage medium, characterized in that, the computer-readable storage medium stores a computer program, and the computer program is used to enable the computer to perform the high-precision operation described in any one of claims 1 to 5. Channel Group Delay Characteristic Fitting and Simulation Method. 8. A communication system, characterized in that it comprises: at least one processor; and a memory connected in communication with the at least one processor; wherein, the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the At least one processor executes the high-precision channel group delay characteristic fitting and simulation implementation method described in any one of claims 1 to 5.

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