Frequency scale measurement method and device, computer equipment and storage medium

Abstract

The invention provides a frequency scale measurement method and device, computer equipment and a storage medium, and the method comprises the steps: carrying out the frequency division processing of a measurement signal outputted by a frequency source, and obtaining a low-frequency pulse signal; carrying out delay measurement and time interval counting on the low-frequency pulse signal by using a high-precision time interval counter, and outputting the low-frequency pulse signal in a timestamp form; the method comprises the following steps of: setting a sliding window, carrying out sliding average filtering processing on timestamps by utilizing a sliding average algorithm, carrying out sliding action difference on all the timestamps to obtain time differences, grouping the time differences in sequence, and averaging in groups to obtain average time differences; the number of measured samples is increased by increasing the length of the sliding window, so that statistical errors are reduced; a frequency measurement value, a relative frequency deviation and an Arron variance are calculated using the average time difference. According to the method provided by the invention, the sliding window is increased, and the frequency measurement result is obtained by using the algorithm of grouping and averaging the time difference, so that the method has higher measurement precision and stability.

Description

Technical Field

[0001] The present invention belongs to the technical field of time frequency measurement, and in particular relates to a frequency standard measurement method, device, computer equipment and storage medium. Background Art

[0002] Time and frequency measurement technology has important applications in the field of modern science and engineering, especially in the fields of communication, navigation, metrology and scientific research, which have extremely high requirements for the accuracy and stability of frequency sources. For example, as high-precision frequency sources, source crystal oscillators and oven-controlled crystal oscillators (OCXOs) are increasingly widely used in communication equipment, satellite navigation systems, radar systems and other fields. These devices have extremely high requirements for frequency standard (frequency standard) characteristics such as frequency stability of frequency sources, because frequency stability directly affects the performance and reliability of the system. Therefore, frequency standard measurement is a key technology in the field of time and frequency measurement. It mainly measures key characteristic indicators such as frequency accuracy, frequency stability, frequency drift rate and frequency aging rate of frequency standards, among which frequency accuracy and frequency stability are the basic performance indicators of frequency standards. Frequency accuracy is characterized by the relative frequency deviation between the output frequency (frequency measurement value) of the frequency standard and the nominal frequency (the rated frequency of the oscillator or crystal oscillator device, that is, the ideal operating frequency), while frequency stability is calculated by calculating the Allan variance of the frequency signal to quantify the random fluctuation of the frequency in the form of signal noise, which can evaluate the stability of the frequency standard on different time scales.

[0003] In the prior art, the frequency standard comparator is a conventional test instrument in the traditional method of frequency standard measurement, which is used to measure the time domain characteristics and frequency domain characteristics of the frequency standard. By inputting the measured frequency standard and the reference frequency standard, the frequency and phase deviation values ​​between the two are measured, and then the frequency accuracy, frequency stability and other indicators of the measured frequency standard are calculated. Traditional frequency standard measurement technology mainly adopts frequency difference multiplication method, double mixing time difference method and digital double mixing time difference method, etc. These methods measure the average frequency difference or phase difference of the two frequency standards through a counter, and then calculate the time domain technical indicators by the subsequent processing program, or obtain the phase difference data by digital sampling and digital signal processing of the frequency standard signal. Although it can meet the measurement requirements to a certain extent, there are problems such as complex circuit structure, high hardware cost, and difficulty in meeting the design requirements of miniaturized test devices. In addition, these methods still need to be improved in terms of measurement accuracy and stability. For example, although the frequency difference multiplication method and the beat method can achieve high-precision measurement, the circuit complexity is high and the dependence on hardware equipment is strong. Some simplified methods, such as the combination of direct digital frequency synthesizer (DDS) and phase detector, although they simplify the circuit design to a certain extent, still have shortcomings in measurement accuracy and stability.

[0004] Time-to-digital converter (TDC) technology is a high-precision (time accuracy can reach ps level) time measurement technology, which is used to measure the time interval between two signals, thereby calculating their frequency difference. Specifically, by converting the time interval into a digital signal, high-resolution measurement of time is achieved. It has the characteristics of high precision, high resolution and high stability, and is widely used in frequency standard measurement technology. However, if conventional TDC technology is directly used, the delay time of the delay unit is reduced in order to improve the resolution, resulting in a longer delay chain, causing the linearity of the system to deteriorate due to nonlinear accumulation, resulting in unstable measurement results.

[0005] The technology development based on the field programmable gate array (FPGA) platform provides more options besides the frequency standard comparator for achieving high computational efficiency and high-precision frequency standard measurement. By utilizing the programmable and designable characteristics of FPGA, the TDC technology is improved, and the delay time is designed, and the measurement results are smoothed and averaged by adopting appropriate algorithm design, which can effectively correct the nonlinearity. It is a feasible frequency standard measurement method for the technical goal of improving the frequency standard measurement accuracy and the stability of the measurement system. Summary of the invention

[0006] In order to solve the above problems existing in the prior art, the present invention proposes a frequency standard measurement method, device, computer equipment and storage medium, which effectively improves the measurement accuracy and stability by extending the sliding window length corresponding to the single measurement time, and then performing sliding difference and group averaging on the measurement results. This method can significantly improve the reliability and accuracy of the measurement results while maintaining a simple design, meeting the needs of high-precision frequency standard measurement.

[0007] A frequency standard measurement method, the specific technical solution includes: Step 110, performing frequency division processing on the measurement signal output by the frequency source to obtain a low-frequency pulse signal; the measurement signal is a periodic high-frequency pulse signal; Step 120, using a high-precision time interval counter to perform delay measurement and time interval counting on the low-frequency pulse signal, and converting the counting result into a digital signal, and outputting it in the form of a timestamp at a fixed time interval; Step 130, use a sliding average algorithm to perform sliding average filtering on the timestamps to obtain filtered signal data for suppressing high-frequency noise; the sliding average algorithm sets a sliding window to perform sliding difference on all timestamps to obtain time differences, groups the time differences in order and averages them within the groups to obtain average time differences; the length of the sliding window is the maximum number of timestamps input into the sliding window; by increasing the length of the sliding window, the gate time of a single measurement is extended to increase the number of samples measured and thus reduce statistical errors; Step 140, using the average time difference, calculate the frequency measurement value; using the frequency measurement value and the nominal frequency to calculate the relative frequency deviation, which is used to characterize the accuracy of the frequency standard measurement; using the relative frequency deviation to calculate the Allan variance, which is used to describe the frequency stability.

[0008] Preferably, the high-precision time interval counter adopts a time-to-digital converter, and utilizes the programmable and designable performance of the FPGA platform to implement the steps Step 110 to Step 140.

[0009] The present invention also protects a frequency mark measurement device, which is used to implement the steps of the above-mentioned frequency mark measurement method, and the device includes: A frequency division module is used to perform frequency division processing on the measurement signal output by the frequency source to obtain a low-frequency pulse signal; the measurement signal is a periodic high-frequency pulse signal; A time interval counting module, used for performing delay measurement and time interval counting on the low-frequency pulse signal using a high-precision time interval counter, and converting the counting result into a digital signal, and outputting it in the form of a timestamp at a fixed time interval; The sliding average filtering module is used to perform sliding average filtering on the timestamps using a sliding average algorithm to obtain filtered signal data and suppress high-frequency noise; the sliding average algorithm sets a sliding window to perform sliding difference on all timestamps to obtain time differences, groups the time differences in order and takes the average within the group to obtain the average time difference; the length of the sliding window is the maximum number of timestamps input into the sliding window; the gate time of a single measurement is extended by increasing the length of the sliding window, so as to increase the number of samples measured and thus reduce statistical errors; The calculation module is used to calculate the frequency measurement value using the average time difference; calculate the relative frequency deviation using the frequency measurement value and the nominal frequency to characterize the accuracy of the frequency standard measurement; and calculate the Allan variance using the relative frequency deviation to describe the frequency stability.

[0010] Preferably, the frequency standard measuring device is built on an FPGA platform, the programmable and designable performance of the FPGA is utilized to implement the function of each module of the device, and the time interval counting module is designed as a time-to-digital converter module.

[0011] The present invention provides a computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the above-mentioned frequency standard measurement method when executing the computer program.

[0012] On the other hand, a storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the above-mentioned frequency standard measurement method are implemented.

[0013] In summary, the present invention proposes a frequency mark measurement method, device, equipment and storage medium. Compared with the prior art, the frequency mark measurement method of the present invention has the following advantages and beneficial effects: (1) The method of the present invention prolongs the gate time of frequency measurement by increasing the length of the sliding window, increases the number of measurement samples, and thus reduces statistical errors, which not only improves the reliability of the measurement results, but also improves the measurement resolution and measurement accuracy.

[0014] (2) The present invention performs sliding average filtering on the timestamp, groups and averages the time difference data obtained using the sliding window to obtain the average time difference, then uses the average time difference to calculate the frequency measurement value, and evaluates the accuracy and stability of the frequency standard measurement by calculating the relative frequency deviation and Allan variance value. Experimental results show that when the sliding window is increased, the frequency measurement result calculated using the grouping and averaging algorithm has higher accuracy and stability. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 This is a flow chart of a frequency mark measurement method in the first embodiment of the present invention; Figure 2 A schematic diagram of a process framework of a frequency mark measurement method in a second embodiment of the present invention; Figure 3 It is a time difference curve diagram of Experiment 1 when the third embodiment of the present invention is experimentally verified; Figure 4 It is a frequency measurement value curve diagram of Experiment 1 when the third embodiment of the present invention is experimentally verified; Figure 5 The Allan variance curve of Experiment 1 is a graph of the experimental verification of the third embodiment of the present invention; Figure 6 It is a time difference curve diagram of Experiment 2 when the third embodiment of the present invention is experimentally verified; Figure 7 This is a graph showing the average time difference of Experiment 2 when the third embodiment of the present invention is experimentally verified; Figure 8 The relative frequency deviation curve diagram of Experiment 2 when the third embodiment of the present invention is experimentally verified; Fig. 9 The Allan variance curve of Experiment 2 is a graph of the experimental verification of the third embodiment of the present invention; Fig.10 It is a time difference curve diagram of Experiment 3 when the third embodiment of the present invention is experimentally verified; Fig.11 This is a graph showing the average time difference of Experiment 3 when the third embodiment of the present invention is experimentally verified; Fig.12 The relative frequency deviation curve diagram of Experiment 3 when the third embodiment of the present invention is experimentally verified; Fig.13 The Allan variance curve of Experiment 3 is shown when the third embodiment of the present invention is experimentally verified; Fig.14 A structural framework diagram of a frequency standard measurement device in a fourth embodiment of the present invention; Fig.15 A structural framework diagram of a frequency standard measurement device in a fifth embodiment of the present invention, wherein the TDC module is a time-to-digital converter module. DETAILED DESCRIPTION

[0016] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0017] In order to solve the problem of frequency mark measurement of frequency source, the present invention provides a frequency mark measurement method. By designing a sliding window that describes a single measurement time and suppressing noise in the measurement result through a sliding average algorithm, the method has good measurement real-time performance and can effectively correct the nonlinearity of the system, thereby improving the frequency mark measurement accuracy and the stability of the measurement system.

[0018] In the first embodiment, referring to Figure 1 As shown, the present invention provides a frequency mark measurement method, which specifically includes the following steps: Step 110, performing frequency division processing on the measurement signal output by the frequency source to obtain a low-frequency pulse signal; the measurement signal is a periodic high-frequency pulse signal; Step 120, using a high-precision time interval counter to perform delay measurement and time interval counting on the low-frequency pulse signal, and converting the counting result into a digital signal, and outputting it in the form of a timestamp at a fixed time interval; Step 130, use a sliding average algorithm to perform sliding average filtering on the timestamps to obtain filtered signal data for suppressing high-frequency noise; the sliding average algorithm sets a sliding window to perform sliding difference on all timestamps to obtain time differences, groups the time differences in order and averages them within the groups to obtain average time differences; the length of the sliding window is the maximum number of timestamps input into the sliding window; by increasing the length of the sliding window, the gate time of a single measurement is extended to increase the number of samples measured and thus reduce statistical errors; Step 140, using the average time difference, calculate the frequency measurement value; using the frequency measurement value and the nominal frequency to calculate the relative frequency deviation, which is used to characterize the accuracy of the frequency standard measurement; using the relative frequency deviation to calculate the Allan variance, which is used to describe the frequency stability.

[0019] Specifically, in Step 110, the process of dividing the measured signal output by the frequency source includes setting the frequency division coefficient. , divide the measured signal into frequencies of A low frequency pulse signal, is the nominal frequency of the measurement signal. The low-frequency pulse signal is obtained by frequency division processing to meet the requirements of high-precision time interval counters for time resolution and measurement accuracy. Suppose the unit time for frequency standard measurement is , the nominal frequency The frequency measurement method with equal precision can be used, that is, by obtaining the unit time It is measured by the number of measurement signal pulses that pass through the time interval counter (coarse measurement).

[0020] Further, in Step 120, the high-precision time interval counter is set to Within, with time interval Output timestamp, then the number of timestamps output ,use Indicates the timestamp, .

[0021] Specifically, in Step 130, if the length of the sliding window is , then the gate time (sampling interval) for a single measurement is , is the time span corresponding to the sliding window ; For all Timestamp Perform sliding subtraction and obtain Time difference , , the time difference is given by: (1) The time difference Group in order, all time differences are divided into group, so each The time differences are grouped into Indicates floor operation, for example .

[0022] In the design of sliding average algorithm, if all The time difference can be evenly divided into groups, so we can select the appropriate and the length of the sliding window , so that is an integer. For example, when the time span corresponding to the sliding window is exactly the same as the unit time When the calculation is consistent, we can deduce: (2) Therefore, when the sliding window length does not meet When it is an integer, the time difference needs to be grouped in order by rounding off. The time difference is calculated by each group Divide After grouping, the remaining The time difference is discarded.

[0023] The average of each group of time differences is Average time difference , which is given by the following formula: (3) Further, in Step 140, the average time difference is used to calculate the continuous time Inside Unit time Frequency measurement value , , which is given by the following formula: (4) in, is the nominal frequency; The frequency measurement and the nominal frequency are used to calculate the time per unit Relative frequency deviation (relative frequency difference) within , is given by: , (5) Then use the following formula to calculate the Allan variance: (6) in, Indicates the sampling interval.

[0024] The second embodiment of the present invention, as Figure 2 As shown, the programmable and designable performance of the FPGA platform is used to implement the process of Step 110-Step 140 in the first embodiment, and the high-precision time interval counter uses a time digital converter (TDC). The method of this embodiment is an improvement on the TDC frequency standard measurement technology using the FPGA platform.

[0025] Specifically, by performing frequency division processing on the measurement signal output by the frequency source based on the FPGA platform, precise control of the signal frequency can be achieved so that the generated low-frequency pulse signal can better adapt to the operating frequency of the TDC and reduce the demand for circuit design.

[0026] Since the TDC includes a delay chain composed of multiple delay units connected in series, and multiple counters for realizing coarse counting or fine counting, when the low-frequency pulse signal obtained by frequency division processing is input into the delay chain of the TDC and the signal propagates in the delay chain, the TDC will use the counter to run the measurement time interval based on the system clock frequency inside the FPGA to obtain a coarse count; on the basis of the coarse count, obtain a fine count by measuring the position of the signal in the delay chain; read the current coarse count or fine count of the TDC module and store it as a timestamp. This method can obtain delay measurement and time interval counting results with higher resolution.

[0027] In addition, by utilizing the parallel computing capability and configurability of FPGA, it is possible to achieve high-speed parallel computing in the acquisition of timestamps, sliding window, sliding average processing of multiple sample data, and subsequent calculation processes, thereby improving the efficiency of frequency standard measurement.

[0028] Based on the FPGA platform and TDC of the second embodiment, in the third embodiment of the present invention, the frequency source is a constant temperature crystal oscillator, and the output The measurement signal of 5MHz, 10MHz or 100MHz is processed by frequency division to obtain a low-frequency pulse signal with a frequency of 100Hz. The low-frequency pulse signal of 100Hz is input into the delay chain in the TDC to count the time interval, and the time interval is calculated as Output timestamp (including coarse count and fine count), select continuous time All timestamps, get the number of timestamps ,use Indicates the timestamp, .

[0029] Set the length of the sliding window , then the gate time for a single measurement, that is, the time span corresponding to the sliding window ; The unit time for frequency standard measurement is also set to .

[0030] For all Timestamp Perform sliding subtraction and obtain Time difference , , and use formula (1) to calculate the 900 time differences .

[0031] In unit time Within, the time difference Group in order, all time differences are divided into Group, each Divide them into a group and use formula (3) to calculate the average time difference of each group of time differences .

[0032] Then, the frequency measurement value is calculated according to formula (4) using the average time difference: , , and use formula (5) and formula (6) to calculate the relative frequency deviation and Allan variance respectively.

[0033] In order to verify the effectiveness of the frequency standard measurement method of the present invention in improving measurement accuracy and stability, an experiment is conducted on the third embodiment. In the experiment, the time interval of the TDC timestamp output remains unchanged, and the time interval is Output timestamps, lengthening the continuous time of timestamp acquisition , the number of timestamps , the amount of sampled data is increased by adjusting the size of the sliding window, and it is further verified that by increasing the length of the sliding window in the sliding average algorithm, that is, increasing the measurement gate time accordingly, the frequency standard measurement accuracy and frequency stability can be improved.

[0034] Experiment 1: No sliding average filtering, that is, the length of the sliding window ; Directly to the timestamps, the number of intervals is calculated as Time difference: , (7) The time difference result is as follows Figure 3 shown.

[0035] The time difference is then used to calculate the frequency measurement: , (8) in, is the nominal frequency.

[0036] Unit time The relative frequency deviation within is given by: , , The frequency measurement results are as follows: Figure 4 shown.

[0037] Finally, the Allan variance is calculated using formula (6). The Allan variance curve is as follows: Figure 5As shown, the mean value of the Allan variance is .

[0038] Experiment 2: Setting the length of the sliding window , perform sliding average filtering; According to formula (1), 9990 time differences are obtained. The time difference image is as follows: Figure 6 As shown; Unit time In the example, the 9990 time differences are divided into Group, each The remaining 90 are discarded and the average time difference is calculated according to formula (3). , The average time difference curve is as follows: Figure 7 As shown; then use formula (4) to calculate the frequency measurement value , and use formula (5) and formula (6) to calculate the relative frequency deviation and Allan variance respectively, and the average value of Allan variance is The relative frequency deviation curve in this experiment is as follows: Figure 8 As shown, the Allan variance curve is Fig. 9 shown.

[0039] Experiment 3: Setting the length of the sliding window , perform sliding average filtering; According to formula (1), 9900 time differences are obtained. The time difference image is as follows: Fig.10 As shown; Unit time In the example, the 9900 time differences are divided into Group, each The average time difference is calculated according to formula (3). , The average time difference curve is as follows: Fig.11 As shown; then use formula (4) to calculate the frequency measurement value , and use formula (5) and formula (6) to calculate the relative frequency deviation and Allan variance respectively, and the average value of Allan variance is The relative frequency deviation curve in this experiment is as follows: Fig.12 As shown, the Allan variance curve is Fig.13 shown.

[0040] Through the above experiments, it can be seen from the experimental results of relative frequency deviation and Allan variance curve that when the sliding window is increased, the amplitude of the relative frequency deviation ( Figure 4 , Figure 8 and Fig.12 ) and the amplitude and mean of the Allan variance ( Figure 5 , Fig. 9 and Fig.13 ) are getting smaller, indicating that the frequency measurement results obtained by using the group averaging method have higher accuracy and stability.

[0041] A fourth embodiment of the present invention provides a frequency standard measuring device, such as Fig.14 As shown, the steps of the frequency mark measurement method in the above embodiment are implemented by using the device, and the device includes the following modules: A frequency division module is used to perform frequency division processing on the measurement signal output by the frequency source to obtain a low-frequency pulse signal; the measurement signal is a periodic high-frequency pulse signal; A time interval counting module, used for performing delay measurement and time interval counting on the low-frequency pulse signal using a high-precision time interval counter, and converting the counting result into a digital signal, and outputting it in the form of a timestamp at a fixed time interval; The sliding average filtering module is used to perform sliding average filtering on the timestamps using a sliding average algorithm to obtain filtered signal data and suppress high-frequency noise; the sliding average algorithm sets a sliding window to perform sliding difference on all timestamps to obtain time differences, groups the time differences in order and takes the average within the group to obtain the average time difference; the length of the sliding window is the maximum number of timestamps input into the sliding window; the gate time of a single measurement is extended by increasing the length of the sliding window, so as to increase the number of samples measured and thus reduce statistical errors; The calculation module is used to calculate the frequency measurement value using the average time difference; calculate the relative frequency deviation using the frequency measurement value and the nominal frequency to characterize the accuracy of the frequency standard measurement; and calculate the Allan variance using the relative frequency deviation to describe the frequency stability.

[0042] In the fifth embodiment, if Fig.15 As shown, the frequency mark measurement device is built on an FPGA platform, and the programmable design performance of the FPGA is used to implement the steps of the above-mentioned frequency mark measurement method, and the time interval counting module is designed using a TDC module.

[0043] In the above-mentioned embodiment, the platform that implements the frequency mark measurement using the frequency mark measurement method or device may be other parallel computing measurement system platforms having similar performance to the FPGA platform, and the programmable and designable performance of this measurement platform is utilized to implement the steps of the above-mentioned frequency mark measurement method.

[0044] On the other hand, in one embodiment of the present invention, there is provided a computer device, which may be a server, and the device includes a processor, a memory, a network interface and a database connected via a system bus. The processor of the device is used to provide computing and control capabilities. The memory of the device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the device is used to store frequency standard measurement data. The network interface of the device is used to communicate with an external terminal via a network connection. When the computer program is executed by the processor, the frequency standard measurement method is implemented.

[0045] Those skilled in the art will appreciate that the description of the technical features of the devices in the above embodiments does not constitute a limitation on all devices to which the present invention is applied, and a specific device may include more or fewer components, or combine certain components, or have a different arrangement of components.

[0046] In another embodiment, a storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the above-mentioned frequency standard measurement method are implemented.

[0047] Those of ordinary skill in the art will appreciate that all or part of the processes for implementing the above-mentioned embodiments can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0048] Matters not covered by the present invention are known technologies.

[0049] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0050] The above-mentioned embodiments only express several implementation modes of the present invention, and the description thereof is relatively specific and detailed, but it cannot be understood as limiting the scope of the invention. It should be pointed out that, for a person of ordinary skill in the art, several modifications and improvements can be made without departing from the concept of the present invention, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the attached claims.

Claims

1. A frequency standard measurement method, characterized in that: include: Step 110, performing frequency division processing on the measurement signal output by the frequency source to obtain a low-frequency pulse signal; the measurement signal is a periodic high-frequency pulse signal; Step 120, using a high-precision time interval counter to perform delay measurement and time interval counting on the low-frequency pulse signal, and converting the counting result into a digital signal, and outputting it in the form of a timestamp at a fixed time interval; Step 130, using a sliding average algorithm to perform sliding average filtering on the timestamps to obtain filtered signal data for suppressing high-frequency noise; the sliding average algorithm sets a sliding window to perform sliding subtraction on all timestamps to obtain time differences, groups the time differences in order, and then takes the average within the group to obtain an average time difference; The length of the sliding window is the maximum number of timestamps input into the sliding window; by increasing the length of the sliding window, the gate time of a single measurement is extended to increase the number of samples measured and thus reduce statistical errors; Step 140, using the average time difference to calculate the frequency measurement value; using the frequency measurement value and the nominal frequency to calculate the relative frequency deviation, which is used to characterize the accuracy of the frequency standard measurement; The relative frequency deviation is used to calculate the Allan variance, which is used to describe the frequency stability.

2. The frequency standard measurement method according to claim 1, characterized in that: In the Step 110, the process of dividing the measured signal output by the frequency source includes setting the frequency division coefficient , divide the measured signal into frequencies of A low frequency pulse signal, is the nominal frequency of the measured signal.

3. The frequency standard measurement method according to claim 2, characterized in that: Assume that the high-precision time interval counter is Output timestamp, then in continuous time The number of timestamps output internally ,use Indicates the timestamp, , suppose the unit time for frequency standard measurement is ; In Step 130, the process of using the sliding average algorithm to perform sliding average filtering on the timestamp includes: The length of use is The sliding window of Timestamp Perform sliding subtraction and obtain Time difference , , the time difference is given by: ; The time difference Group in order, all time differences are divided into Group, each The time differences are grouped into Indicates the rounding down operation, the remaining The time difference is discarded; Take the average of each group of time differences and get Average time difference , is given by: 。 4. The frequency standard measurement method according to claim 3, characterized in that: In Step 140, The process of calculating the frequency measurement value using the average time difference includes calculating the continuous time Inside Unit time Frequency measurement value , , is given by: ， in, is the nominal frequency; The process of calculating the relative frequency deviation using the measured frequency and the nominal frequency, including calculating the frequency per unit time Relative frequency deviation within , is given by: ， ； The Allan variance is calculated using the relative frequency deviation and is given by: , in, Indicates the sampling interval.

5. The frequency standard measurement method according to claim 4, characterized in that: The high-precision time interval counter adopts a time-to-digital converter and utilizes the programmable and designable performance of the FPGA platform to implement the steps Step 110 to Step 140.

6. The frequency standard measurement method according to claim 5, characterized in that: The frequency source is a constant temperature crystal oscillator, which is used to output The measurement signal of 5MHz, 10MHz or 100MHz is processed by frequency division to obtain a low-frequency pulse signal with a frequency of 100Hz, and the low-frequency pulse signal of 100Hz is input into the delay chain in the time-to-digital converter to count the time interval, and the time interval is used as Output timestamp; Select continuous time All timestamps, get the number of timestamps , set the length of the sliding window , the unit time for frequency standard measurement is set to ,but, In Step 130, the process of using the sliding average algorithm to perform sliding average filtering on the timestamp includes: For all The timestamps are slidingly subtracted to obtain Time difference , ; The 900 time differences are grouped into Group, each into a group; calculate the average time difference ; In Step 140, the frequency measurement value is calculated using the average time difference. , , relative frequency deviation and Allan variance.

7. A frequency standard measuring device, characterized in that: The device is used to implement the steps of the frequency mark measurement method as claimed in claim 1, and the device comprises: A frequency division module is used to perform frequency division processing on the measurement signal output by the frequency source to obtain a low-frequency pulse signal; the measurement signal is a periodic high-frequency pulse signal; A time interval counting module, used for performing delay measurement and time interval counting on the low-frequency pulse signal using a high-precision time interval counter, and converting the counting result into a digital signal, and outputting it in the form of a timestamp at a fixed time interval; The sliding average filtering module is used to perform sliding average filtering on the timestamps using a sliding average algorithm to obtain filtered signal data and suppress high-frequency noise; the sliding average algorithm sets a sliding window to perform sliding difference on all timestamps to obtain time differences, groups the time differences in order and takes the average within the group to obtain the average time difference; the length of the sliding window is the maximum number of timestamps input into the sliding window; the gate time of a single measurement is extended by increasing the length of the sliding window, so as to increase the number of samples measured and thus reduce statistical errors; The calculation module is used to calculate the frequency measurement value using the average time difference; calculate the relative frequency deviation using the frequency measurement value and the nominal frequency to characterize the accuracy of the frequency standard measurement; and calculate the Allan variance using the relative frequency deviation to describe the frequency stability.

8. The frequency standard measuring device according to claim 7, characterized in that: The frequency standard measuring device is built on an FPGA platform, and the programmable design performance of the FPGA is used to realize the function of each module of the device, and the time interval counting module is designed as a time-to-digital converter module.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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