Frequency measurement method and device, electronic equipment and computer program product

Abstract

The invention relates to the technical field of electronic measurement and signal processing, in particular to a frequency measurement method and device, electronic equipment and a computer program product, and the method comprises the steps: receiving a to-be-measured signal; determining a target filtering parameter based on the to-be-detected signal, performing signal lifting on the to-be-detected signal, and performing filtering processing based on the target filtering parameter to obtain a pre-processed signal; and determining a target high-precision time interval measurement strategy based on the preprocessed signal, and measuring the frequency of the preprocessed signal based on the target high-precision time interval measurement strategy. Therefore, the problems of limited measurement precision, low response speed, poor adaptability and the like of a traditional analog circuit are solved, the frequency measurement precision and the response speed are remarkably improved, and wide applicability and high accuracy of a measurement result are ensured.

Description

Technical Field

[0001] The present application relates to the technical field of electronic measurement and signal processing, and in particular to a frequency measurement method, device, electronic equipment and computer program product. Background Art

[0002] In the field of modern electronic measurement and signal processing, frequency measurement is a basic and key technology, which is widely used in many industries such as communications, radar, aerospace, industrial automation, etc. With the continuous development of technology, higher and higher requirements are placed on the accuracy, speed and adaptability of frequency measurement. Although traditional frequency measurement methods, such as frequency counters based on analog circuits or frequency measurement systems based on microprocessors, can meet general needs to a certain extent, they often have problems such as limited measurement accuracy, slow response speed, and poor adaptability when facing high frequency, wide bandwidth, and complex signal environments. Summary of the invention

[0003] The present application provides a frequency measurement method, device, electronic device and computer program product to solve the problems of limited measurement accuracy, slow response speed and poor adaptability of traditional analog circuits.

[0004] The first aspect of the present application provides a frequency measurement method, comprising the following steps: receiving a signal to be measured; determining a target filtering parameter based on the signal to be measured, and performing signal lifting on the signal to be measured and filtering processing based on the target filtering parameter to obtain a preprocessed signal; determining a target high-precision time interval measurement strategy based on the preprocessed signal, and measuring the frequency of the preprocessed signal based on the target high-precision time interval measurement strategy.

[0005] Optionally, determining the target filtering parameters based on the signal to be tested includes: obtaining the spectral characteristics of the signal to be tested; if the proportion of high-frequency noise in the signal to be tested is greater than a first preset proportion, increasing the current cutoff frequency in the current filtering parameters to the first target cutoff frequency to obtain the target filtering parameters, or increasing the current passband bandwidth in the current filtering parameters to the target passband bandwidth to obtain the target filtering parameters; if the low-frequency proportion in the signal to be tested is greater than a second preset proportion, reducing the cutoff frequency in the current filtering parameters to the second target cutoff frequency to obtain the target filtering parameters.

[0006] Optionally, determining the target high-precision time interval measurement strategy based on the preprocessed signal includes: monitoring the real-time signal frequency of the preprocessed signal; if the real-time signal frequency of the preprocessed signal is at a low frequency, the target high-precision time interval measurement strategy is to measure the frequency of the preprocessed signal using a direct counting method; if the real-time signal frequency of the preprocessed signal is at an intermediate frequency, the target high-precision time interval measurement strategy is to measure the frequency of the preprocessed signal using a precision measurement method or an FPGA-based time-to-digital conversion method; if the real-time signal frequency of the preprocessed signal is at a high frequency, the target high-precision time interval measurement strategy is to measure the frequency of the preprocessed signal using a frequency estimation algorithm based on FFT.

[0007] Optionally, the signal boosting and filtering based on the target filtering parameters to obtain a preprocessed signal includes: using a preset amplifier to increase the voltage of the signal to be tested to a preset voltage range, and using target filtering parameters to remove high-frequency noise and low-frequency interference in the signal to be tested to obtain the preprocessed signal.

[0008] The second aspect of the present application provides a frequency measurement device, including: a receiving module, used to receive a signal to be measured; a processing module, used to determine a target filtering parameter based on the signal to be measured, and perform signal lifting and filtering processing on the signal to be measured based on the target filtering parameter to obtain a preprocessed signal; a measuring module, used to determine a target high-precision time interval measurement strategy based on the preprocessed signal, and measure the frequency of the preprocessed signal based on the target high-precision time interval measurement strategy.

[0009] Optionally, the processing module is also used to: obtain the spectral characteristics of the signal to be tested; if the proportion of high-frequency noise in the signal to be tested is greater than a first preset proportion, then increase the current cutoff frequency in the current filtering parameters to the first target cutoff frequency to obtain the target filtering parameters, or increase the current passband bandwidth in the current filtering parameters to the target passband bandwidth to obtain the target filtering parameters; if the low-frequency proportion in the signal to be tested is greater than a second preset proportion, then reduce the cutoff frequency in the current filtering parameters to the second target cutoff frequency to obtain the target filtering parameters.

[0010] Optionally, the measurement module is also used to: monitor the real-time signal frequency of the preprocessed signal; if the real-time signal frequency of the preprocessed signal is at a low frequency, the target high-precision time interval measurement strategy is to measure the frequency of the preprocessed signal using a direct counting method; if the real-time signal frequency of the preprocessed signal is at an intermediate frequency, the target high-precision time interval measurement strategy is to measure the frequency of the preprocessed signal using a precision measurement method or an FPGA-based time-to-digital conversion method; if the real-time signal frequency of the preprocessed signal is at a high frequency, the target high-precision time interval measurement strategy is to measure the frequency of the preprocessed signal using an FFT-based frequency estimation algorithm.

[0011] Optionally, the processing module is further used to: use a preset amplifier to increase the voltage of the signal to be tested to a preset voltage range, and use target filtering parameters to remove high-frequency noise and low-frequency interference in the signal to be tested to obtain the preprocessed signal.

[0012] A third aspect of the present application provides an electronic device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the frequency measurement method as described in the above embodiment.

[0013] A fourth aspect of the present application provides a computer program product on which a computer program is stored. The program is executed by a processor to implement the frequency measurement method as described in the above embodiment.

[0014] In the above implementation, a signal to be tested is received, a target filtering parameter is determined based on the signal to be tested, and the signal to be tested is lifted and filtered based on the target filtering parameter to obtain a preprocessed signal, a target high-precision time interval measurement strategy is determined based on the preprocessed signal, and the frequency of the preprocessed signal is measured based on the target high-precision time interval measurement strategy. Thus, the problems of limited measurement accuracy, slow response speed, and poor adaptability of traditional analog circuits are solved, the frequency measurement accuracy and response speed are significantly improved, and the wide applicability and high accuracy of the measurement results are ensured.

[0015] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0017] Figure 1 A flow chart of a frequency measurement method provided according to an embodiment of the present application;

[0018] Figure 2 is a schematic diagram of a frequency measurement structure according to an embodiment of the present application;

[0019] Figure 3 is an exemplary diagram of a frequency measurement device according to an embodiment of the present application;

[0020] Figure 4 Schematic diagram of the structure of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0021] Embodiments of the present application are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.

[0022] The frequency measurement method, device, electronic device and computer program product of the embodiment of the present application are described below with reference to the accompanying drawings. In view of the problems of limited measurement accuracy, slow response speed and poor adaptability of the traditional analog circuit mentioned in the above background technology, the present application provides a frequency measurement method, in which a signal to be measured is received, a target filtering parameter is determined based on the signal to be measured, and the signal to be measured is lifted and filtered based on the target filtering parameter to obtain a preprocessed signal, a target high-precision time interval measurement strategy is determined based on the preprocessed signal, and the frequency of the preprocessed signal is measured based on the target high-precision time interval measurement strategy. As a result, the problems of limited measurement accuracy, slow response speed and poor adaptability of the traditional analog circuit are solved, the frequency measurement accuracy and response speed are significantly improved, and the wide applicability and high accuracy of the measurement results are ensured.

[0023] Specifically, Figure 1 A flow chart of a frequency measurement method provided in an embodiment of the present application.

[0024] like Figure 1 As shown, the frequency measurement method includes the following steps:

[0025] In step S101, a signal to be tested is received.

[0026] like Figure 2 As shown, a high performance analog front end is used to receive the signal to be measured.

[0027] In step S102, target filtering parameters are determined based on the signal to be tested, and the signal to be tested is boosted and filtered based on the target filtering parameters to obtain a preprocessed signal.

[0028] Optionally, in some embodiments, the target filtering parameters are determined based on the signal to be tested, including: obtaining the spectral characteristics of the signal to be tested; if the proportion of high-frequency noise in the signal to be tested is greater than a first preset proportion, increasing the current cutoff frequency in the current filtering parameters to the first target cutoff frequency to obtain the target filtering parameters, or increasing the current passband bandwidth in the current filtering parameters to the target passband bandwidth to obtain the target filtering parameters; if the low-frequency proportion in the signal to be tested is greater than a second preset proportion, reducing the cutoff frequency in the current filtering parameters to the second target cutoff frequency to obtain the target filtering parameters.

[0029] Among them, the first preset ratio, the second preset ratio, the first target cutoff frequency and the second target cutoff frequency, and the target passband bandwidth can be thresholds set in advance by the user, can be thresholds obtained through a limited number of experiments, or can be thresholds obtained through a limited number of computer simulations, and are not specifically limited here.

[0030] In an embodiment of the present application, the intelligent algorithm optimization module within the FPGA evaluates whether the current filtering parameters are appropriate by real-time analysis of the spectral characteristics of the digital signal, including frequency distribution, noise level, etc., and determines whether the current filtering parameters can effectively filter out noise and harmonics based on preset evaluation criteria (such as signal-to-noise ratio threshold, harmonic distortion rate, etc.).

[0031] If the evaluation results show that the filtering effect is not good, the intelligent algorithm will automatically adjust the filtering parameters. For example, if the signal to be tested contains more high-frequency noise, the algorithm may increase the filter's cutoff frequency or passband bandwidth. If the signal to be tested contains more low-frequency components, the algorithm may reduce the cutoff frequency to retain more low-frequency information.

[0032] For example, assume that the current filter parameters are: current cutoff frequency: 1kHz, current passband bandwidth: 5kHz

[0033] If the high-frequency noise ratio in the signal to be tested reaches 35% (greater than the first preset ratio of 30%), the cutoff frequency is increased. The current cutoff frequency can be adjusted from 1kHz to 20kHz, or the current passband bandwidth can be adjusted from 5kHz to 10kHz (select one method according to specific needs).

[0034] If it is detected that the proportion of the low-frequency component in the signal to be tested reaches 45% (greater than the second preset proportion of 40%), the cutoff frequency is reduced, and the current cutoff frequency can be adjusted from 1 kHz to 500 Hz.

[0035] Optionally, in some embodiments, the signal to be tested is boosted and filtered based on target filtering parameters, including: using a preset amplifier to increase the voltage of the signal to be tested to a preset voltage range, and using target filtering parameters to remove high-frequency noise and low-frequency interference in the signal to be tested to obtain a preprocessed signal.

[0036] The preset voltage range may be a threshold value preset by a user, a threshold value obtained through a limited number of experiments, or a threshold value obtained through a limited number of computer simulations, which is not specifically limited here.

[0037] Specifically, the digital processing module in the FPGA converts the signal to be tested into a digital signal, and performs signal boosting and filtering. If the digital processing module in the FPGA detects that the amplitude of the signal to be tested is low, the signal to be tested is boosted. For example, a preset amplifier can be used to increase the voltage of the signal to be tested to a preset voltage range to improve the signal-to-noise ratio and the accuracy of subsequent processing. This can also be achieved by adding a DC bias, adjusting the gain, etc., and using the target filtering parameters to remove high-frequency noise and low-frequency interference in the signal to be tested to obtain a preprocessed signal with a higher signal-to-noise ratio and better spectral characteristics.

[0038] In step S103, a target high-precision time interval measurement strategy is determined based on the preprocessed signal, and the frequency of the preprocessed signal is measured based on the target high-precision time interval measurement strategy.

[0039] Optionally, in some embodiments, a target high-precision time interval measurement strategy is determined based on the preprocessed signal, including: monitoring the real-time signal frequency of the preprocessed signal; if the real-time signal frequency of the preprocessed signal is at a low frequency, the target high-precision time interval measurement strategy is to measure the frequency of the preprocessed signal using a direct counting method; if the real-time signal frequency of the preprocessed signal is at an intermediate frequency, the target high-precision time interval measurement strategy is to measure the frequency of the preprocessed signal using a precision measurement method or an FPGA-based time-to-digital conversion method; if the real-time signal frequency of the preprocessed signal is at a high frequency, the target high-precision time interval measurement strategy is to measure the frequency of the preprocessed signal using an FFT-based frequency estimation algorithm.

[0040] Specifically, the intelligent algorithm optimization module in the FPGA can identify the approximate frequency band of the current signal based on the signal frequency range of the preprocessed signal monitored in real time.

[0041] According to the frequency band characteristics of the preprocessed signal, select the appropriate frequency measurement strategy. According to the real-time frequency monitoring results, the frequency of the signal is divided into three ranges: low frequency, medium frequency and high frequency. The low frequency range can be defined as 0-10kHz, the medium frequency range can be defined as 10kHz-1MHz, and the high frequency range can be defined as above 1MHz (these ranges can be adjusted according to actual needs).

[0042] When the real-time frequency of the preprocessed signal is in the low-frequency range, the direct counting method is selected as the high-precision time interval measurement strategy. The direct counting method records the number of cycles of the signal within a certain period of time through a counter, thereby calculating the frequency of the signal. This method has high accuracy and stability in the low-frequency range.

[0043] When the real-time frequency of the preprocessed signal is in the intermediate frequency range, you can choose the precision measurement method or the FPGA-based time-to-digital conversion method (TDC). The precision measurement method measures the frequency by comparing the signal period with a known high-precision clock period. The FPGA-based TDC uses the FPGA's hardware resources to achieve high-precision time measurement and can accurately measure the signal's cycle time.

[0044] When the real-time frequency of the preprocessed signal is in the high-frequency range, the FFT-based frequency estimation algorithm is selected as the high-precision time interval measurement strategy. The FFT algorithm can accurately estimate the frequency components of the signal by analyzing the spectrum of the signal, and is particularly suitable for frequency measurement of high-frequency signals.

[0045] During the measurement process, if the signal frequency changes (such as signal frequency hopping, frequency drift, etc.), the intelligent algorithm optimization module will adjust the frequency measurement strategy in real time to adapt to the new frequency environment.

[0046] Finally, the signal data after filtering and frequency measurement will be further processed and analyzed, and the processing results can be output to the subsequent processing module or displayed to the user through the data interface.

[0047] According to the frequency measurement method proposed in the embodiment of the present application, a signal to be measured is received, a target filtering parameter is determined based on the signal to be measured, and the signal to be measured is lifted and filtered based on the target filtering parameter to obtain a preprocessed signal, a target high-precision time interval measurement strategy is determined based on the preprocessed signal, and the frequency of the preprocessed signal is measured based on the target high-precision time interval measurement strategy. Thus, the problems of limited measurement accuracy, slow response speed, and poor adaptability of traditional analog circuits are solved, the frequency measurement accuracy and response speed are significantly improved, and the wide applicability and high accuracy of the measurement results are ensured.

[0048] Next, the frequency measurement device proposed according to the embodiment of the present application is described with reference to the accompanying drawings.

[0049] Figure 3 is a block diagram of a frequency measurement device according to an embodiment of the present application.

[0050] like Figure 3 As shown, the frequency measurement device 10 includes: a receiving module 100 , a processing module 200 and a measuring module 300 .

[0051] Among them, the receiving module 100 is used to receive the signal to be tested; the processing module 200 is used to determine the target filtering parameters based on the signal to be tested, and to perform signal lifting and filtering processing on the signal to be tested based on the target filtering parameters to obtain a preprocessed signal; the measuring module 300 is used to determine the target high-precision time interval measurement strategy based on the preprocessed signal, and to measure the frequency of the preprocessed signal based on the target high-precision time interval measurement strategy.

[0052] Optionally, in some embodiments, the processing module 200 is also used to: obtain the spectral characteristics of the signal to be tested; if the proportion of high-frequency noise in the signal to be tested is greater than a first preset proportion, then increase the current cutoff frequency in the current filtering parameters to the first target cutoff frequency to obtain the target filtering parameters, or increase the current passband bandwidth in the current filtering parameters to the target passband bandwidth to obtain the target filtering parameters; if the low-frequency proportion in the signal to be tested is greater than a second preset proportion, then reduce the cutoff frequency in the current filtering parameters to the second target cutoff frequency to obtain the target filtering parameters.

[0053] Optionally, in some embodiments, the measurement module 300 is also used to: monitor the real-time signal frequency of the preprocessed signal; if the real-time signal frequency of the preprocessed signal is at a low frequency, the target high-precision time interval measurement strategy is to measure the frequency of the preprocessed signal using a direct counting method; if the real-time signal frequency of the preprocessed signal is at an intermediate frequency, the target high-precision time interval measurement strategy is to measure the frequency of the preprocessed signal using a precision measurement method or an FPGA-based time-to-digital conversion method; if the real-time signal frequency of the preprocessed signal is at a high frequency, the target high-precision time interval measurement strategy is to measure the frequency of the preprocessed signal using an FFT-based frequency estimation algorithm.

[0054] Optionally, in some embodiments, the processing module 200 is further used to: use a preset amplifier to increase the voltage of the signal to be tested to a preset voltage range, and use target filtering parameters to remove high-frequency noise and low-frequency interference in the signal to be tested to obtain a preprocessed signal.

[0055] It should be noted that the above explanation of the frequency measurement method embodiment is also applicable to the frequency measurement device of this embodiment, and will not be repeated here.

[0056] According to the frequency measurement device proposed in the embodiment of the present application, a signal to be measured is received, a target filtering parameter is determined based on the signal to be measured, and the signal to be measured is lifted and filtered based on the target filtering parameter to obtain a preprocessed signal, a target high-precision time interval measurement strategy is determined based on the preprocessed signal, and the frequency of the preprocessed signal is measured based on the target high-precision time interval measurement strategy. Thus, the problems of limited measurement accuracy, slow response speed, and poor adaptability of traditional analog circuits are solved, the frequency measurement accuracy and response speed are significantly improved, and the wide applicability and high accuracy of the measurement results are ensured.

[0057] Figure 4 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. The electronic device may include:

[0058] Memory 401 , processor 402 , and a computer program stored in the memory 401 and executable on the processor 402 .

[0059] When the processor 402 executes the program, the frequency measurement method provided in the above embodiment is implemented.

[0060] Furthermore, the electronic device further comprises:

[0061] The communication interface 403 is used for communication between the memory 401 and the processor 402 .

[0062] The memory 401 is used to store computer programs that can be executed on the processor 402 .

[0063] The memory 401 may include a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.

[0064] If the memory 401, the processor 402 and the communication interface 403 are implemented independently, the communication interface 403, the memory 401 and the processor 402 can be connected to each other through a bus and communicate with each other. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 4 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0065] Optionally, in a specific implementation, if the memory 401, the processor 402 and the communication interface 403 are integrated on a chip, the memory 401, the processor 402 and the communication interface 403 can communicate with each other through an internal interface.

[0066] The processor 402 may be a central processing unit (CPU), or an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application.

[0067] An embodiment of the present application also provides a computer program product, on which a computer program is stored, and when the program is executed by a processor, the above frequency measurement method is implemented.

[0068] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or N embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0069] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include at least one of the features. In the description of this application, "N" means at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0070] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, fragment or portion of code comprising one or more executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in reverse order depending on the functions involved, which should be understood by technicians in the technical field to which the embodiments of the present application belong.

[0071] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer program product for use with an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in combination with these instruction execution systems, devices or apparatuses. For the purposes of this specification, a "computer program product" can be any device that can contain, store, communicate, propagate or transmit a program for use with an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses. More specific examples of computer program products (a non-exhaustive list) include the following: an electrical connection with one or N wirings (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disk read-only memory (CDROM). Furthermore, the computer program product may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example by optically scanning the paper or other medium and then editing, interpreting or, if necessary, processing in another suitable manner, and then storing it in a computer memory.

[0072] It should be understood that the various parts of the present application can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiment, the N steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0073] A person skilled in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer program product, which, when executed, includes one or a combination of the steps of the method embodiment.

[0074] In addition, each functional unit in each embodiment of the present application may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer program product.

[0075] The computer program product mentioned above may be a read-only memory, a disk or an optical disk, etc. Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limiting the present application. A person of ordinary skill in the art may change, modify, replace and modify the above embodiments within the scope of the present application.

Claims

1. A frequency measurement method, characterized in that: The following steps are involved: receiving a signal to be tested; Determine a target filtering parameter based on the signal to be tested, and perform signal lifting on the signal to be tested and filter processing based on the target filtering parameter to obtain a preprocessed signal; A target high-precision time interval measurement strategy is determined based on the preprocessed signal, and the frequency of the preprocessed signal is measured based on the target high-precision time interval measurement strategy.

2. The method according to claim 1, characterized in that: The determining of a target filtering parameter based on the signal to be measured comprises: Acquiring the frequency spectrum characteristics of the signal to be measured; If the high-frequency noise ratio in the signal to be tested is greater than a first preset ratio, the current cutoff frequency in the current filtering parameters is increased to the first target cutoff frequency to obtain the target filtering parameters, or the current passband bandwidth in the current filtering parameters is increased to the target passband bandwidth to obtain the target filtering parameters. If the low-frequency ratio in the signal to be tested is greater than a second preset ratio, the cutoff frequency in the current filtering parameters is reduced to the second target cutoff frequency to obtain the target filtering parameters.

3. The method according to claim 1, characterized in that The step of determining a target high-precision time interval measurement strategy based on the preprocessed signal includes: Monitoring the real-time signal frequency of the preprocessed signal; If the real-time signal frequency of the preprocessed signal is at a low frequency, the target high-precision time interval measurement strategy is to measure the frequency of the preprocessed signal using a direct counting method; If the real-time signal frequency of the preprocessed signal is at an intermediate frequency, the target high-precision time interval measurement strategy is to measure the frequency of the preprocessed signal using a precision measurement method or a time-to-digital conversion method based on FPGA; If the real-time signal frequency of the preprocessed signal is at a high frequency, the target high-precision time interval measurement strategy is to measure the frequency of the preprocessed signal using a frequency estimation algorithm based on FFT.

4. The method according to claim 1, wherein the step of performing signal lifting on the signal to be tested and filtering based on the target filtering parameters to obtain a preprocessed signal comprises: The voltage of the signal to be measured is increased to a preset voltage range by using a preset amplifier, and high-frequency noise and low-frequency interference in the signal to be measured are removed by using target filtering parameters to obtain the preprocessed signal.

5. A frequency measuring device, characterized in that: include: A receiving module, used for receiving a signal to be tested; A processing module, used to determine a target filtering parameter based on the signal to be tested, and perform signal lifting on the signal to be tested and filter processing based on the target filtering parameter to obtain a preprocessed signal; A measurement module is used to determine a target high-precision time interval measurement strategy based on the preprocessed signal, and measure the frequency of the preprocessed signal based on the target high-precision time interval measurement strategy.

6. The device according to claim 5, characterized in that The processing module is further used for: Acquiring the frequency spectrum characteristics of the signal to be measured; If the high-frequency noise ratio in the signal to be tested is greater than a first preset ratio, the current cutoff frequency in the current filtering parameters is increased to the first target cutoff frequency to obtain the target filtering parameters, or the current passband bandwidth in the current filtering parameters is increased to the target passband bandwidth to obtain the target filtering parameters. If the low-frequency ratio in the signal to be tested is greater than a second preset ratio, the cutoff frequency in the current filtering parameters is reduced to the second target cutoff frequency to obtain the target filtering parameters.

7. The device according to claim 5, characterized in that The measuring module is further used for: Monitoring the real-time signal frequency of the preprocessed signal; If the real-time signal frequency of the preprocessed signal is at a low frequency, the target high-precision time interval measurement strategy is to measure the frequency of the preprocessed signal using a direct counting method; If the real-time signal frequency of the preprocessed signal is at an intermediate frequency, the target high-precision time interval measurement strategy is to measure the frequency of the preprocessed signal using a precision measurement method or a time-to-digital conversion method based on FPGA; If the real-time signal frequency of the preprocessed signal is at a high frequency, the target high-precision time interval measurement strategy is to measure the frequency of the preprocessed signal using a frequency estimation algorithm based on FFT.

8. The device according to claim 5, characterized in that The processing module is further used for: The voltage of the signal to be measured is increased to a preset voltage range by using a preset amplifier, and high-frequency noise and low-frequency interference in the signal to be measured are removed by using target filtering parameters to obtain the preprocessed signal.

9. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the frequency measurement method according to any one of claims 1 to 4.

10. A computer program product having a computer program stored thereon, characterized in that: The program is executed by a processor to implement the frequency measurement method according to any one of claims 1 to 4.

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