A high frequency spectrum analysis method and system

Abstract

The present invention discloses a high-frequency spectrum analysis method and system, and relates to the field of data processing technology. The method comprises: collecting a device test signal when a target device sends a preset instruction in an environment, and collecting environmental characteristic parameters; based on the environmental characteristic parameters, performing a device operation impact analysis on the spectrum analysis device, and obtaining the device operation characteristic parameters; performing basic noise filtering on the device test signal, and obtaining a noise filtering test signal and a composite signal-to-noise ratio; performing spectrum analysis on the device operation characteristic parameters, and obtaining spectrum analysis results; calculating the integration ratio according to the composite signal-to-noise ratio; correcting the integration ratio, and obtaining a corrected integration ratio, and based on the integrated analysis, performing a performance analysis of the target device on the spectrum analysis results, and obtaining the device performance analysis results. The technical problem of inaccurate high-frequency spectrum analysis results due to noise influence in the prior art is solved, and the technical effect of improving the accuracy of spectrum analysis is achieved through noise filtering.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to a high-frequency spectrum analysis method and system. Background Art

[0002] In high-tech fields such as wireless communications, radar detection, and electronic countermeasures, high-frequency spectrum analysis technology plays a vital role. With the continuous advancement of technology and the continuous expansion of applications, the requirements for the accuracy and reliability of spectrum analysis are becoming higher and higher. However, in actual operation, high-frequency spectrum analysis is often interfered by various factors, especially environmental noise and equipment operation noise. These noise sources are not only complex and changeable, but also difficult to completely eliminate, which brings great challenges to spectrum analysis. Traditional spectrum analysis methods often only focus on the characteristics of the signal itself, ignoring the impact of environmental factors and equipment status on test results. This leads to the difficulty of obtaining accurate and reliable test results in high-frequency spectrum analysis, even with the most advanced instruments and technologies. Summary of the invention

[0003] The embodiments of the present application provide a high-frequency spectrum analysis method and system, which solve the technical problem in the prior art that the high-frequency spectrum analysis results are inaccurate due to noise influence.

[0004] In view of the above problems, an embodiment of the present application provides a high-frequency spectrum analysis method and system.

[0005] A first aspect of an embodiment of the present application provides a high frequency band spectrum analysis method, the method comprising:

[0006] The device test signal when the target device sends a preset instruction is collected in the environment, and the environmental characteristic parameters in the environment are collected; according to the environmental characteristic parameters, the noise impact analysis of the test signal is performed to obtain the environmental noise impact parameters; based on the environmental characteristic parameters, the device operation impact analysis of the spectrum analysis device is performed to obtain the device operation characteristic parameters, and the noise impact analysis of the test signal is performed to obtain the device noise impact parameters; the device test signal is subjected to basic noise filtering processing, and based on the environmental noise impact parameters and the device noise impact parameters, the device test signal after basic noise filtering is subjected to environmental noise filtering processing and device noise filtering processing to obtain a noise-filtered test signal and a composite signal-to-noise ratio; based on the spectrum analysis device, the device operation characteristic parameters are subjected to spectrum analysis to obtain spectrum analysis results; according to the composite signal-to-noise ratio, the integration ratio for performing the target device performance integration analysis is calculated and determined; the performance impact coefficient of the environmental characteristic parameters on the target device is analyzed and obtained, the integration ratio is corrected to obtain the corrected integration ratio, and according to the corrected integration ratio, based on the integrated analysis, the performance analysis of the target device is performed on the spectrum analysis result to obtain the device performance analysis result.

[0007] A second aspect of an embodiment of the present application provides a high-frequency spectrum analysis system, the system comprising:

[0008] an acquisition module, the acquisition module is used to acquire the device test signal when the target device sends a preset instruction in the environment, and acquire the environmental characteristic parameters in the environment; a first analysis module, the first analysis module is used to perform noise impact analysis on the test signal according to the environmental characteristic parameters, and obtain environmental noise impact parameters; a second analysis module, the second analysis module is used to perform device operation impact analysis on the spectrum analysis device based on the environmental characteristic parameters, obtain device operation characteristic parameters, and perform noise impact analysis on the test signal, and obtain device noise impact parameters; a noise filtering processing module, the noise filtering processing module is used to perform basic noise filtering on the device test signal, and based on the environmental noise impact parameters and the device noise impact parameters, perform basic noise filtering on the basic noise filtered signal. The device test signal is subjected to environmental noise filtering processing and device noise filtering processing to obtain a noise filtering test signal and a composite signal-to-noise ratio; a spectrum analysis module, the spectrum analysis module is used to perform spectrum analysis on the device operation characteristic parameters based on the spectrum analysis device to obtain a spectrum analysis result; a calculation module, the calculation module is used to calculate and determine the integration ratio for performing integrated analysis of the target device performance according to the composite signal-to-noise ratio; a performance analysis module, the performance analysis module is used to analyze and obtain the performance influence coefficient of the environmental characteristic parameters on the target device, correct the integration ratio to obtain a corrected integration ratio, and according to the corrected integration ratio, based on the integrated analysis, perform performance analysis of the target device on the spectrum analysis result to obtain a device performance analysis result.

[0009] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0010] First, the device test signal when the target device sends a preset instruction is collected in the environment, and the environmental characteristic parameters in the environment are collected. Then, according to the environmental characteristic parameters, the noise impact analysis of the test signal is performed to obtain the environmental noise impact parameters. Based on the environmental characteristic parameters, the equipment operation impact analysis of the spectrum analysis device is performed to obtain the equipment operation characteristic parameters, and the noise impact analysis of the test signal is performed to obtain the equipment noise impact parameters. Next, the device test signal is subjected to basic noise filtering, and based on the environmental noise impact parameters and the equipment noise impact parameters, the device test signal after basic noise filtering is subjected to environmental noise filtering and equipment noise filtering to obtain the noise filtering test signal and the composite signal-to-noise ratio. Based on the spectrum analysis device, the device operation characteristic parameters are subjected to spectrum analysis to obtain the spectrum analysis results. According to the composite signal-to-noise ratio, the integration ratio for the target device performance integration analysis is calculated and determined. Finally, the performance impact coefficient of the environmental characteristic parameters on the target device is analyzed and obtained, the integration ratio is corrected to obtain the corrected integration ratio, and according to the corrected integration ratio, based on the integrated analysis, the performance analysis of the target device is performed on the spectrum analysis results to obtain the device performance analysis results. The technical problem of inaccurate high-frequency spectrum analysis results due to noise in the prior art is solved, and the technical effect of improving the accuracy of spectrum analysis is achieved through noise filtering. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0012] Figure 1 A schematic diagram of a high-frequency spectrum analysis method provided in an embodiment of the present application;

[0013] Figure 2 A schematic diagram of the structure of a high-frequency spectrum analysis system provided in an embodiment of the present application.

[0014] Explanation of reference numerals: acquisition module 11 , first analysis module 12 , second analysis module 13 , noise filtering module 14 , spectrum analysis module 15 , calculation module 16 , performance analysis module 17 . DETAILED DESCRIPTION

[0015] The embodiments of the present application provide a high-frequency spectrum analysis method and system to solve the technical problem in the prior art that high-frequency spectrum analysis results are inaccurate due to noise influence.

[0016] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0017] It should be noted that the terms "including" and "having" are intended to cover non-exclusive inclusions. For example, a process, method, system, product or server that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or modules that are not explicitly listed or are inherent to these processes, methods, products or devices. Embodiment 1

[0018] like Figure 1 As shown, the embodiment of the present application provides a high frequency band spectrum analysis method, wherein the method includes:

[0019] The device test signal is collected in the environment when the target device sends a preset instruction, and the environmental characteristic parameters in the environment are collected.

[0020] The device test signal when the target device sends a preset instruction is collected in the environment where the target device is located, wherein the preset instruction is a test instruction. At the same time, environmental characteristic parameters in the environment are collected, such as temperature, humidity, electromagnetic interference, etc. These environmental characteristic parameters may affect the device test signal.

[0021] Furthermore, the device test signal when the target device sends a preset instruction is collected in the environment, and the environmental characteristic parameters in the environment are collected, including:

[0022] The target device is tested in the environment using preset test instructions, and the device test signal when the target device sends the preset test instructions is collected; the temperature parameters, humidity parameters and electromagnetic parameters in the environment are collected as environmental characteristic parameters.

[0023] In the environment where the target device is located, the target device is tested using the preset test instructions, that is, the target device is tested using the test instructions, and when the target device responds to the preset instructions, the device test signal generated by the target device is collected using a signal acquisition device (such as an oscilloscope, spectrum analyzer, logic analyzer, etc.). At the same time, the temperature, humidity and electromagnetic parameters in the environment are measured using devices such as thermometers, hygrometers and electromagnetic field measuring instruments, and the collected temperature parameters, humidity parameters and electromagnetic parameters are used as environmental characteristic parameters.

[0024] According to the environmental characteristic parameters, a noise impact analysis of the test signal is performed to obtain environmental noise impact parameters.

[0025] Based on the collected environmental characteristic parameters, the noise impact analysis of the test signal is performed. For example, the signal-to-noise ratio change of the test signal under different temperatures, humidity and electromagnetic interference levels can be calculated to quantify the specific impact of environmental noise on the test signal, and then obtain the environmental noise impact parameters. The environmental noise impact parameters are used to describe the specific degree of impact of environmental noise on the test signal.

[0026] Furthermore, according to the environmental characteristic parameters, performing noise impact analysis on the test signal to obtain environmental noise impact parameters includes:

[0027] Collect a set of sample environment characteristic parameters; obtain a set of sample environment noise impact parameters based on the noise characteristics of the noise impact on the test signal under different sample environment characteristic parameters; use the sample environment characteristic parameter set and the sample environment noise impact parameter set to train an environmental noise impact analyzer, perform noise impact analysis on the test signal with respect to the environmental characteristic parameters, and obtain environmental noise impact parameters.

[0028] Preferably, different combinations of environmental characteristic parameters are collected to form a sample environmental characteristic parameter set, and each sample represents a different set of environmental characteristic parameters; under different sample environmental characteristic parameters, a preset instruction is sent to the target device, and a test signal is collected, and the noise characteristics in the test signal are analyzed, such as noise amplitude, frequency distribution, signal-to-noise ratio, etc. These noise characteristics reflect the noise impact of the environment on the test signal, and the noise impact parameters are associated with the corresponding sample environmental characteristic parameters to form a sample environmental noise impact parameter set; according to a machine learning or deep learning algorithm, a suitable model is selected as an environmental noise impact analyzer, and the sample environmental characteristic parameter set and the sample environmental noise impact parameter set are used as training data, the sample environmental characteristic parameter set is used as input features, and the corresponding sample environmental noise impact parameter set is used as the target output, and the model is trained so that the model can learn the mapping relationship from environmental characteristic parameters to noise impact parameters. After the training is completed, an environmental noise impact analyzer is obtained; the environmental characteristic parameters are input into the trained environmental noise impact analyzer, and the environmental noise impact analyzer will output corresponding environmental noise impact parameters according to the input environmental characteristic parameters. The environmental noise impact parameters reflect the degree of noise impact on the test signal under a specific environment.

[0029] Based on the environmental characteristic parameters, an equipment operation impact analysis of the spectrum analysis equipment is performed to obtain equipment operation characteristic parameters, and a noise impact analysis of the test signal is performed to obtain equipment noise impact parameters.

[0030] Environmental parameters can affect the operating parameters of the spectrum analyzer (for example, temperature affects the thermal noise of the device), which in turn affects the signals acquired by the spectrum analyzer. Based on the environmental characteristic parameters, the operation of the spectrum analyzer is analyzed to obtain the characteristic parameters of the device operation. The noise impact of the test signal is analyzed on the characteristic parameters of the device operation to obtain the device noise impact parameters.

[0031] Further, based on the environmental characteristic parameters, performing equipment operation impact analysis of the spectrum analysis equipment to obtain equipment operation characteristic parameters, and performing noise impact analysis of the test signal to obtain equipment noise impact parameters, including:

[0032] Based on the operation data record of the spectrum analysis device, a set of sample environmental characteristic parameters is collected, and the thermal noise parameters in the spectrum analysis device under different sample environmental characteristic parameters are collected to obtain a set of sample device operation characteristic parameters; the sample environmental characteristic parameter set and the sample device operation characteristic parameter set are used to train a spectrum analysis device impact analyzer, and the environmental characteristic parameters are used to perform an equipment operation impact analysis of the spectrum analysis device to obtain equipment operation characteristic parameters; noise characteristics that affect the test signal under different thermal noise parameters are collected to obtain a set of sample device noise impact parameters; the sample device operation characteristic parameter set is converted into an input, and the sample device noise impact parameter set is used as an input to train a device noise impact analyzer, and the device operation characteristic parameters are used to perform a noise impact analysis to obtain the device noise impact parameters.

[0033] Preferably, the environmental characteristic parameters of the spectrum analysis device in different environments are collected to form a sample environmental characteristic parameter set, and the operation data records of the spectrum analysis device in different environments are collected at the same time; the thermal noise parameters in the spectrum analysis device corresponding to each sample environmental characteristic parameter in the sample environmental characteristic parameter set, such as thermal noise level, spectrum distribution, etc., are obtained; these thermal noise parameters are associated with the corresponding environmental characteristic parameters to form a sample device operation characteristic parameter set. According to the machine learning or deep learning algorithm, a suitable model is selected as the spectrum analysis device impact analyzer, the sample environmental characteristic parameter set and the sample device operation characteristic parameter set are used as training data, the sample environmental characteristic parameter set is used as input features, and the corresponding sample device operation characteristic parameter set is used as the target output. The model is trained so that the model can learn the mapping relationship from environmental characteristic parameters to device operation characteristic parameters. After the training is completed, the spectrum analysis device impact analyzer is obtained; the environmental characteristic parameters are input into the trained spectrum analysis device impact analyzer, and the spectrum analysis device impact analyzer will output the corresponding device operation characteristic parameters according to the input environmental characteristic parameters. The noise characteristics of the noise impact on the test signal under different thermal noise parameters, such as noise amplitude, frequency distribution, signal-to-noise ratio, etc., are collected to form a set of sample equipment noise impact parameters; a machine learning or deep learning algorithm is used to select a suitable model as the equipment noise impact analyzer, and the equipment operation characteristic parameters output by the spectrum analysis equipment impact analyzer are used as input features, and the corresponding set of sample equipment noise impact parameters is used as the target output. The model is trained so that the model can learn the mapping relationship from the equipment operation characteristic parameters to the equipment noise impact parameters. After the training is completed, the equipment noise impact analyzer is obtained; the equipment operation characteristic parameters are input into the trained equipment noise impact analyzer, and the equipment noise impact analyzer will output the equipment noise impact parameters according to the input equipment operation characteristic parameters. The equipment noise impact parameters reflect the degree of noise impact on the test signal under different environments.

[0034] The device test signal is subjected to basic noise filtering processing, and based on the environmental noise impact parameter and the device noise impact parameter, the device test signal after basic noise filtering is subjected to environmental noise filtering processing and device noise filtering processing to obtain a noise-filtered test signal and a composite signal-to-noise ratio.

[0035] The device test signal is subjected to noise filtering, including basic noise filtering, environmental noise filtering and device noise filtering. Specifically, basic noise filtering refers to filtering the test signal using a digital filter (such as a low-pass filter, a band-pass filter, etc.) to eliminate high-frequency noise and other irrelevant signals; environmental noise filtering refers to further processing the test signal after basic noise filtering by selecting a noise suppression algorithm (such as adaptive filtering, Wiener filtering, etc.) according to the environmental noise influencing parameters to eliminate or reduce the influence of environmental noise; device noise filtering refers to further processing the test signal after environmental noise filtering by selecting a suitable noise suppression technology (such as calibration, hardware filtering, etc.) according to the equipment noise influencing parameters to eliminate or reduce the influence of the internal noise of the equipment. After basic noise filtering, environmental noise filtering and device noise filtering, the noise level of the noise-filtered test signal should be significantly reduced and the signal quality should be improved. Calculate the composite signal-to-noise ratio, which is the ratio of the power of the device test signal to the remaining noise power after noise filtering.

[0036] Further, performing basic noise filtering on the device test signal, and performing environmental noise filtering and device noise filtering on the device test signal after basic noise filtering based on the environmental noise impact parameter and the device noise impact parameter, to obtain a noise-filtered test signal and a composite signal-to-noise ratio, including:

[0037] Perform basic noise filtering on the device test signal; determine noise signal characteristics according to the environmental noise impact parameters and the device noise impact parameters, perform environmental noise filtering and device noise filtering on the device test signal after the basic noise filtering to obtain a noise filtering test signal; calculate and obtain a composite signal-to-noise ratio according to the noise filtering test signal and the device test signal.

[0038] Perform basic noise filtering on the device test signal, and use digital filters (such as low-pass filters, band-pass filters, etc.) to remove high-frequency noise and other signals unrelated to the test signal; analyze and determine the main characteristics of the noise signal, including the frequency distribution, amplitude, phase, etc. of the noise, according to the environmental noise influencing parameters and the equipment noise influencing parameters. After determining the characteristics of the noise signal, use a more sophisticated noise filtering algorithm to further process the device test signal after basic noise filtering. In environmental noise filtering, adaptive filtering, Wiener filtering and other algorithms can be used to eliminate or reduce noise caused by environmental factors (such as electromagnetic interference, temperature changes, etc.). In equipment noise filtering, hardware filtering, calibration and other technologies are used to eliminate or reduce noise caused by internal factors of the device (such as electronic noise, thermal noise, etc.). By combining environmental noise filtering and equipment noise filtering, the noise in the test signal can be more effectively suppressed and the signal quality can be improved. After environmental noise filtering and equipment noise filtering, the signal obtained is the noise filtering test signal. The composite signal-to-noise ratio is calculated based on the noise-filtered test signal and the original device test signal. The composite signal-to-noise ratio is an important indicator for evaluating the effect of noise filtering, which reflects the power ratio between the signal after noise filtering and the remaining noise.

[0039] Based on the spectrum analysis equipment, the spectrum analysis is performed on the equipment operation characteristic parameters to obtain the spectrum analysis results.

[0040] Spectrum analysis equipment is used to perform spectrum analysis on the characteristic parameters of equipment operation, that is, spectrum analysis is performed on the signal after noise filtering. The spectrum analysis of the signal reflects the performance of the control signal generated by the equipment, and the spectrum analysis result is obtained.

[0041] Based on the composite signal-to-noise ratio, an integration ratio for performing integrated analysis of target device performance is calculated and determined.

[0042] A benchmark composite signal-to-noise ratio is set according to the performance requirements, historical data or industry standards of the equipment, and the difference between the composite signal-to-noise ratio and the benchmark composite signal-to-noise ratio is calculated as the integration ratio for the target equipment performance integration analysis.

[0043] Analyze and obtain the performance influence coefficient of the environmental characteristic parameters on the target device, correct the integration ratio to obtain the corrected integration ratio, and perform performance analysis of the target device on the spectrum analysis results based on the integrated analysis according to the corrected integration ratio to obtain the device performance analysis result.

[0044] The performance impact coefficient of the target device is obtained by analyzing the environmental characteristic parameters, and the integration ratio is corrected according to the performance impact coefficient to obtain the corrected integration ratio. According to the corrected integration ratio, the spectrum analysis results are integrated and analyzed. The goal of the integrated analysis is to convert the spectrum analysis results into an evaluation of the overall performance of the device. Based on the results of the integrated analysis, the performance of the target device is evaluated to obtain the device performance analysis results.

[0045] Further, analyzing and obtaining the performance influence coefficient of the environmental characteristic parameter on the target device, correcting the integration ratio to obtain the corrected integration ratio, and performing performance analysis of the target device on the spectrum analysis result based on the integrated analysis according to the corrected integration ratio, including:

[0046] Based on the operation data records of the target device under different environmental characteristic parameters, the performance impact coefficient of the environmental characteristic parameters on the target device is analyzed and obtained, wherein, by collecting sample environmental characteristic parameters and sample performance impact coefficients, a performance impact analyzer is trained to perform performance impact analysis; based on the performance impact coefficient, the integration ratio is corrected and calculated to obtain a corrected integration ratio; according to the corrected integration ratio, based on the integration analysis, the performance analysis of the target device is performed on the spectrum analysis results to obtain a device performance analysis result.

[0047] Preferably, sample environmental characteristic parameters and sample performance impact coefficients are collected as training data, and a machine learning algorithm is used to train a performance impact analyzer (such as a regression model, decision tree, neural network, etc.). The model can predict the performance impact coefficient based on the input environmental characteristic parameters, and the environmental characteristic parameters are input into the trained performance impact analyzer. The performance impact analyzer will output the performance impact coefficient of the target device based on the environmental characteristic parameters; the integration ratio is corrected and calculated based on the performance impact coefficient, and a new integration ratio, i.e., the corrected integration ratio, is obtained through weighted calculation. The spectrum analysis results are integrated and analyzed based on the corrected integration ratio, and the performance of the target device is evaluated based on the results of the integrated analysis to obtain the device performance analysis results.

[0048] Furthermore, according to the modified integration ratio, based on the integrated analysis, the performance analysis of the target device is performed on the spectrum analysis result, including:

[0049] Based on the historical test data of the same type of equipment as the target equipment, a set of sample spectrum analysis results and a set of sample equipment performance analysis results are collected as an integrated training data set; a portion of the integrated training data in the integrated training data set is randomly selected as a first training data set, and a first equipment performance analysis branch is obtained through training; a portion of the integrated training data in the integrated training data set is randomly selected again as a second training data set, and a second equipment performance analysis branch is obtained through training; the training is continued to obtain multiple equipment performance analysis branches, and the equipment performance analyzer is obtained through integration; according to the corrected integration ratio, the performance analysis of the target equipment is performed on the spectrum analysis results in the equipment performance analysis branches of the corresponding proportion of the equipment performance analyzer, and a number of basic performance analysis results are obtained; according to the several basic performance analysis results, the equipment performance analysis results of the target equipment are obtained through classification.

[0050] From the historical test data of the target device and the same type of device, collect the sample spectrum analysis result set (input data) and the corresponding sample device performance analysis result set (target), and combine the sample spectrum analysis results and the corresponding device performance analysis results into an integrated training data set. Randomly select part of the data in the integrated training data set as the first training data set for training the first device performance analysis branch, and use the first training data set to train the first device performance analysis model (such as a neural network, a decision tree, etc.) to obtain the first device performance analysis branch. Repeat the above steps, but select a different data subset as the training data set each time to train multiple device performance analysis branches. Integrate the trained multiple device performance analysis branches and form a device performance analyzer by weighted averaging. Input the spectrum analysis results of the target device to be evaluated into the device performance analyzer, and select the corresponding proportion of device performance analysis branches in the device performance analyzer for evaluation according to the corrected integration ratio. Use the selected analysis branch to perform performance analysis on the spectrum analysis results, and each branch will output a basic performance analysis result. Classify and comprehensively analyze all basic performance analysis results to obtain the device performance analysis results of the target device.

[0051] In summary, the embodiments of the present application have at least the following technical effects:

[0052] First, the device test signal when the target device sends a preset instruction is collected in the environment, and the environmental characteristic parameters in the environment are collected. Then, according to the environmental characteristic parameters, the noise impact analysis of the test signal is performed to obtain the environmental noise impact parameters. Based on the environmental characteristic parameters, the equipment operation impact analysis of the spectrum analysis device is performed to obtain the equipment operation characteristic parameters, and the noise impact analysis of the test signal is performed to obtain the equipment noise impact parameters. Next, the device test signal is subjected to basic noise filtering, and based on the environmental noise impact parameters and the equipment noise impact parameters, the device test signal after basic noise filtering is subjected to environmental noise filtering and equipment noise filtering to obtain the noise filtering test signal and the composite signal-to-noise ratio. Based on the spectrum analysis device, the device operation characteristic parameters are subjected to spectrum analysis to obtain the spectrum analysis results. According to the composite signal-to-noise ratio, the integration ratio for the target device performance integration analysis is calculated and determined. Finally, the performance impact coefficient of the environmental characteristic parameters on the target device is analyzed and obtained, the integration ratio is corrected to obtain the corrected integration ratio, and according to the corrected integration ratio, based on the integrated analysis, the performance analysis of the target device is performed on the spectrum analysis results to obtain the device performance analysis results. The technical problem of inaccurate high-frequency spectrum analysis results due to noise in the prior art is solved, and the technical effect of improving the accuracy of spectrum analysis is achieved through noise filtering. Embodiment 2

[0053] Based on the same inventive concept as the high frequency spectrum analysis method in the above-mentioned embodiment, Figure 2 As shown, the present application provides a high-frequency spectrum analysis system, and the system and method embodiments in the present application are based on the same inventive concept. The system includes:

[0054] A collection module 11, the collection module 11 is used to collect a device test signal when the target device sends a preset instruction in the environment, and collect environmental characteristic parameters in the environment;

[0055] A first analysis module 12, the first analysis module 12 is used to perform noise impact analysis of the test signal according to the environmental characteristic parameters to obtain environmental noise impact parameters;

[0056] A second analysis module 13, the second analysis module 13 is used to perform an equipment operation impact analysis of the spectrum analysis device based on the environmental characteristic parameters to obtain equipment operation characteristic parameters, and to perform a noise impact analysis of the test signal to obtain equipment noise impact parameters;

[0057] A noise filtering processing module 14, wherein the noise filtering processing module 14 is used to perform basic noise filtering processing on the device test signal, and based on the environmental noise influence parameter and the device noise influence parameter, perform environmental noise filtering processing and device noise filtering processing on the device test signal after basic noise filtering to obtain a noise filtered test signal and a composite signal-to-noise ratio;

[0058] A spectrum analysis module 15, wherein the spectrum analysis module 15 is used to perform spectrum analysis on the equipment operation characteristic parameters based on the spectrum analysis equipment to obtain spectrum analysis results;

[0059] A calculation module 16, the calculation module 16 is used to calculate and determine the integration ratio for performing the target device performance integration analysis according to the composite signal-to-noise ratio;

[0060] The performance analysis module 17 is used to analyze and obtain the performance influence coefficient of the environmental characteristic parameters on the target device, correct the integration ratio to obtain the corrected integration ratio, and perform performance analysis of the target device on the spectrum analysis results based on the integrated analysis according to the corrected integration ratio to obtain the device performance analysis result.

[0061] Furthermore, the acquisition module 11 is used to execute the following method:

[0062] The target device is tested in the environment using preset test instructions, and the device test signal when the target device sends the preset test instructions is collected; the temperature parameters, humidity parameters and electromagnetic parameters in the environment are collected as environmental characteristic parameters.

[0063] Furthermore, the second analysis module 13 is used to perform the following method:

[0064] Based on the operation data record of the spectrum analysis device, a set of sample environmental characteristic parameters is collected, and the thermal noise parameters in the spectrum analysis device under different sample environmental characteristic parameters are collected to obtain a set of sample device operation characteristic parameters; the sample environmental characteristic parameter set and the sample device operation characteristic parameter set are used to train a spectrum analysis device impact analyzer, and the environmental characteristic parameters are used to perform an equipment operation impact analysis of the spectrum analysis device to obtain equipment operation characteristic parameters; noise characteristics that affect the test signal under different thermal noise parameters are collected to obtain a set of sample device noise impact parameters; the sample device operation characteristic parameter set is converted into an input, and the sample device noise impact parameter set is used as an input to train a device noise impact analyzer, and the device operation characteristic parameters are used to perform a noise impact analysis to obtain the device noise impact parameters.

[0065] Furthermore, the first analysis module 12 is used to perform the following method:

[0066] Collect a set of sample environment characteristic parameters; obtain a set of sample environment noise impact parameters based on the noise characteristics of the noise impact on the test signal under different sample environment characteristic parameters; use the sample environment characteristic parameter set and the sample environment noise impact parameter set to train an environmental noise impact analyzer, perform noise impact analysis on the test signal with respect to the environmental characteristic parameters, and obtain environmental noise impact parameters.

[0067] Furthermore, the noise filtering processing module 14 is used to perform the following method:

[0068] Perform basic noise filtering on the device test signal; determine noise signal characteristics according to the environmental noise impact parameters and the device noise impact parameters, perform environmental noise filtering and device noise filtering on the device test signal after the basic noise filtering to obtain a noise filtering test signal; calculate and obtain a composite signal-to-noise ratio according to the noise filtering test signal and the device test signal.

[0069] Furthermore, the performance analysis module 17 is used to execute the following method:

[0070] Based on the operation data records of the target device under different environmental characteristic parameters, the performance impact coefficient of the environmental characteristic parameters on the target device is analyzed and obtained, wherein, by collecting sample environmental characteristic parameters and sample performance impact coefficients, a performance impact analyzer is trained to perform performance impact analysis; based on the performance impact coefficient, the integration ratio is corrected and calculated to obtain a corrected integration ratio; according to the corrected integration ratio, based on the integration analysis, the performance analysis of the target device is performed on the spectrum analysis results to obtain a device performance analysis result.

[0071] Furthermore, the performance analysis module 17 is used to execute the following method:

[0072] Based on the historical test data of the same type of equipment as the target equipment, a set of sample spectrum analysis results and a set of sample equipment performance analysis results are collected as an integrated training data set; a portion of the integrated training data in the integrated training data set is randomly selected as a first training data set, and a first equipment performance analysis branch is obtained through training; a portion of the integrated training data in the integrated training data set is randomly selected again as a second training data set, and a second equipment performance analysis branch is obtained through training; the training is continued to obtain multiple equipment performance analysis branches, and the equipment performance analyzer is obtained through integration; according to the corrected integration ratio, the performance analysis of the target equipment is performed on the spectrum analysis results in the equipment performance analysis branches of the corresponding proportion of the equipment performance analyzer, and a number of basic performance analysis results are obtained; according to the several basic performance analysis results, the equipment performance analysis results of the target equipment are obtained through classification.

[0073] It should be noted that the above-mentioned sequence of the embodiments of the present application is only for description and does not represent the advantages and disadvantages of the embodiments. And the above-mentioned specific embodiments of this specification are described. The processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0074] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

[0075] This specification and drawings are merely exemplary illustrations of the present application and are deemed to cover any and all modifications, variations, combinations or equivalents within the scope of the present application. Obviously, a person skilled in the art may make various modifications and variations to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalents, the present application intends to include these modifications and variations.

Claims

1. A high frequency spectrum analysis method, It is characterized in that The method comprises: Collecting device test signals when the target device sends preset instructions in the environment, and collecting environmental characteristic parameters in the environment; According to the environmental characteristic parameters, a noise impact analysis of the test signal is performed to obtain environmental noise impact parameters; Based on the environmental characteristic parameters, perform equipment operation impact analysis of the spectrum analysis equipment to obtain equipment operation characteristic parameters, and perform noise impact analysis of the test signal to obtain equipment noise impact parameters; Performing basic noise filtering on the device test signal, and performing environmental noise filtering and device noise filtering on the device test signal after basic noise filtering based on environmental noise influence parameters and device noise influence parameters, to obtain a noise-filtered test signal and a composite signal-to-noise ratio; Based on the spectrum analysis equipment, spectrum analysis is performed on the equipment operation characteristic parameters to obtain spectrum analysis results; Calculating and determining an integration ratio for performing an integrated analysis of target device performance based on the composite signal-to-noise ratio; Analyze and obtain the performance influence coefficient of the environmental characteristic parameters on the target device, correct the integration ratio to obtain a corrected integration ratio, and perform performance analysis of the target device on the spectrum analysis result based on the integrated analysis according to the corrected integration ratio to obtain a device performance analysis result; The step of analyzing and obtaining the performance influence coefficient of the environmental characteristic parameters on the target device, correcting the integration ratio to obtain a corrected integration ratio, and performing performance analysis of the target device on the spectrum analysis result based on the integrated analysis according to the corrected integration ratio includes: Based on the operation data records of the target device under different environmental characteristic parameters, the performance impact coefficient of the environmental characteristic parameters on the target device is analyzed and obtained, wherein the performance impact analyzer is trained to perform performance impact analysis by collecting sample environmental characteristic parameters and sample performance impact coefficients; Based on the performance impact coefficient, a correction calculation is performed on the integration ratio to obtain a corrected integration ratio; According to the corrected integration ratio, based on the integrated analysis, the performance analysis of the target device is performed on the spectrum analysis result to obtain a device performance analysis result; Based on the historical test data of similar devices of the target device, a set of sample spectrum analysis results and a set of sample device performance analysis results are collected as an integrated training data set; Randomly selecting a portion of the integrated training data in the integrated training data set as a first training data set, and training to obtain a first device performance analysis branch; Randomly selecting a portion of the integrated training data in the integrated training data set again as a second training data set, and training to obtain a second device performance analysis branch; Continue training to obtain multiple device performance analysis branches, and integrate to obtain a device performance analyzer; According to the corrected integration ratio, in the device performance analysis branches of the device performance analyzer corresponding to the ratio, the performance analysis of the target device is performed on the spectrum analysis results to obtain a number of basic performance analysis results; According to the plurality of basic performance analysis results, the device performance analysis results of the target device are classified and obtained.

2. A high frequency spectrum analysis method according to claim 1, It is characterized in that Collect the device test signal when the target device sends the preset command in the environment, and collect the environmental characteristic parameters in the environment, including: Testing the target device using preset test instructions in the environment, and collecting device test signals when the target device sends the preset instructions; The temperature parameters, humidity parameters and electromagnetic parameters in the environment are collected as environmental characteristic parameters.

3. A high frequency spectrum analysis method according to claim 1, It is characterized in that Based on the environmental characteristic parameters, performing equipment operation impact analysis of the spectrum analysis equipment to obtain equipment operation characteristic parameters, and performing noise impact analysis of the test signal to obtain equipment noise impact parameters, including: Based on the operation data record of the spectrum analysis device, a set of sample environment characteristic parameters is collected, and thermal noise parameters in the spectrum analysis device under different sample environment characteristic parameters are collected to obtain a set of sample device operation characteristic parameters; Using the sample environment characteristic parameter set and the sample device operation characteristic parameter set, training a spectrum analysis device impact analyzer, performing device operation impact analysis on the environment characteristic parameters for the spectrum analysis device, and obtaining device operation characteristic parameters; Collect the noise characteristics of the noise impact on the test signal under different thermal noise parameters to obtain a set of sample equipment noise impact parameters; The sample equipment operation characteristic parameter set is converted into input, the sample equipment noise impact parameter set is used as input, an equipment noise impact analyzer is trained, noise impact analysis is performed on the equipment operation characteristic parameters, and equipment noise impact parameters are obtained.

4. A high frequency spectrum analysis method according to claim 1, It is characterized in that According to the environmental characteristic parameters, the noise impact analysis of the test signal is performed to obtain the environmental noise impact parameters, including: Collecting a set of sample environment characteristic parameters; Based on the noise characteristics of the noise impact on the test signal under different sample environment characteristic parameters, a set of sample environment noise impact parameters is obtained; The sample environment characteristic parameter set and the sample environment noise impact parameter set are used to train an environment noise impact analyzer, and the noise impact of the test signal is analyzed on the environment characteristic parameters to obtain the environment noise impact parameters.

5. A high frequency spectrum analysis method according to claim 1, It is characterized in that The device test signal is subjected to basic noise filtering processing, and based on the environmental noise impact parameter and the device noise impact parameter, the device test signal after the basic noise filtering is subjected to environmental noise filtering processing and device noise filtering processing to obtain a noise filtering test signal and a composite signal-to-noise ratio, including: Performing basic noise filtering on the device test signal; Determine noise signal characteristics according to the environmental noise impact parameters and the equipment noise impact parameters, perform environmental noise filtering and equipment noise filtering on the equipment test signal after basic noise filtering to obtain a noise filtering test signal; A composite signal-to-noise ratio is obtained by calculation according to the noise filtering test signal and the device test signal.

6. A high frequency spectrum analysis system, It is characterized in that A system for implementing a high frequency spectrum analysis method according to any one of claims 1 to 5, comprising: A collection module, the collection module is used to collect device test signals when the target device sends preset instructions in the environment, and collect environmental characteristic parameters in the environment; A first analysis module, the first analysis module is used to perform noise impact analysis of the test signal according to the environmental characteristic parameters to obtain environmental noise impact parameters; A second analysis module, the second analysis module is used to perform an equipment operation impact analysis of the spectrum analysis device based on the environmental characteristic parameters to obtain equipment operation characteristic parameters, and to perform a noise impact analysis of the test signal to obtain equipment noise impact parameters; A noise filtering processing module, wherein the noise filtering processing module is used to perform basic noise filtering processing on the device test signal, and based on the environmental noise influence parameter and the device noise influence parameter, perform environmental noise filtering processing and device noise filtering processing on the device test signal after basic noise filtering to obtain a noise filtering test signal and a composite signal-to-noise ratio; A spectrum analysis module, wherein the spectrum analysis module is used to perform spectrum analysis on the equipment operation characteristic parameters based on the spectrum analysis equipment to obtain spectrum analysis results; A calculation module, the calculation module is used to calculate and determine the integration ratio for performing the target device performance integration analysis according to the composite signal-to-noise ratio; A performance analysis module, the performance analysis module is used to analyze and obtain the performance influence coefficient of the environmental characteristic parameters on the target device, correct the integration ratio to obtain the corrected integration ratio, and perform performance analysis of the target device on the spectrum analysis results based on the integrated analysis according to the corrected integration ratio to obtain the device performance analysis result.

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