High-precision time-frequency synchronization method and device based on constant-temperature crystal oscillator

Abstract

The invention discloses a high-precision time-frequency synchronization method and device based on a constant-temperature crystal oscillator, and belongs to the field of time-frequency synchronization of a collaborative platform, and the method comprises the steps: S1, building a clock error model, and designing a fading adaptive Kalman filter; s2, a time reference platform and a to-be-synchronized platform are arranged in a split platform containing a constant-temperature crystal oscillator, clock difference measurement between the platforms is carried out, and a filter is adopted to process and measure the clock difference; s3, calculating the frequency difference between the platforms according to the frequency difference stability obtained by filtering; and S4, speculating a clock error drift trend according to the clock error obtained by filtering and the calculated frequency difference, obtaining the clock error at any moment, and performing compensation and adjustment according to a synchronization demand to complete high-precision time-frequency synchronization. According to the invention, the time-frequency synchronization error of the constant-temperature crystal oscillator system can be accurately measured, a high-stability atomic clock is replaced by the constant-temperature crystal oscillator, and high-precision time-frequency synchronization of the distributed system containing the constant-temperature crystal oscillator is completed.

Description

Technical Field

[0001] The present invention relates to the field of time-frequency synchronization of collaborative platforms, and more specifically, to a high-precision time-frequency synchronization method and device based on an oven-controlled crystal oscillator. Background Art

[0002] With the rapid development of science and technology and the diverse changes in combat scenarios, improving the collaborative combat ability of distributed platforms has become the focus of current military technology research. Since different frequency sources are used in separated platforms, time and frequency synchronization errors will occur between the platforms. The existence of frequency difference will cause the clock difference to drift. When the frequency difference remains fixed, the clock difference shows a linear drift trend; when the frequency difference changes, the clock difference shows a non-linear drift phenomenon. Therefore, accurately measuring the frequency difference is beneficial to controlling the drift trend of the clock difference and further accurately measuring the clock difference. Time-frequency synchronization is the basis of all collaborative information processing and is crucial for signal-level collaboration. Using high-precision time-frequency synchronization technology can ensure that the time, frequency, and phase of the transceiver platforms are consistent and ensure the strict coherence of the transceiver signals.

[0003] To ensure the stability of the clock difference drift, the clocks generally used in separated platforms in time-frequency synchronization are high-stability atomic clocks. Under such conditions, the clock difference between the platforms is basically linearly drifted and the drift speed is very slow, about 0.2 ns / s. This is because the frequency drift of the high-stability atomic clock is very small, so the frequency difference changes very little and can be basically regarded as a fixed value. Although using high-stability atomic clocks can reduce the clock difference drift and improve the system stability, rubidium clocks are expensive and cannot meet the low-cost requirements of engineering applications. An oven-controlled crystal oscillator (OCXO) uses a thermostatic bath to keep the temperature of the crystal oscillator constant, and has the advantages of small size and low price, which can minimize the space occupied by terminal integration. Therefore, it can be considered to use an oven-controlled crystal oscillator to replace the high-stability atomic clock of the separated platform to achieve the low-cost of the system. Therefore, researching a high-precision time-frequency synchronization method based on an oven-controlled crystal oscillator has important engineering significance.

[0004] Normally, the stability of a high-stability atomic clock can reach 1×10 -11 while the stability of an oven-controlled crystal oscillator can only reach 2×10 -7 , and the frequency difference between the platforms will change over time, resulting in non-linear drift of the clock difference. To use an oven-controlled crystal oscillator to replace a high-stability atomic clock for time-frequency synchronization, what needs to be solved is to accurately measure the frequency difference between the platforms and deduce the non-linear drift trend of the clock difference. Usually, filtering and taming can be adopted to obtain the frequency difference between the platforms, but traditional Kalman filtering will diverge when the system modeling is not accurate enough. Summary of the Invention

[0005] The purpose of the present invention is to overcome the deficiencies of the prior art and provide a high-precision time-frequency synchronization method and device based on a temperature-controlled crystal oscillator. An exponentially fading adaptive Kalman filter is designed to measure the clock error through the data link RTT, filter and calculate the frequency difference between distributed platforms with a temperature-controlled crystal oscillator system, and infer the drift trend of the clock error to maintain high-precision time-frequency synchronization of the distributed system with a temperature-controlled crystal oscillator.

[0006] The purpose of the present invention is achieved through the following solutions:

[0007] A high-precision time-frequency synchronization method based on a temperature-controlled crystal oscillator includes the following steps:

[0008] S1. Establish a clock error model and design an exponentially fading adaptive Kalman filter;

[0009] S2. Set a time reference platform and a platform to be synchronized in distributed platforms with a temperature-controlled crystal oscillator, measure the clock error between the platforms, and process the measured clock error using a filter;

[0010] S3. Calculate the frequency difference between the platforms according to the frequency difference stability obtained by filtering;

[0011] S4. Infer the clock error drift trend according to the clock error obtained by filtering and the calculated frequency difference, obtain the clock error at any time, and perform compensation and adjustment according to the synchronization requirements to complete high-precision time-frequency synchronization.

[0012] Further, in step S1, the establishment of the clock error model and the design of the exponentially fading adaptive Kalman filter specifically include the following sub-steps:

[0013] P1. Assume that the local oscillator frequency of the reference platform is f0 and the local oscillator frequency of the platform to be synchronized is f1, and establish the following clock error model representing the change of the clock error over time:

[0014]

[0015] where ε0 is the initial clock error, and the unit is seconds;

[0016] P2. Use the clock error model to design an exponentially fading adaptive Kalman filter, including the following steps:

[0017] P21. Set the initial conditions;

[0018] P22. Establish a state transition matrix through the clock error model, and perform a priori estimation according to the state transition matrix and the optimal estimation value of the previous moment to obtain the a priori estimation value at this moment;

[0019] P23. Introduce an adaptive fading factor, and combine the optimal estimation covariance matrix of the previous moment to predict the a priori estimation covariance matrix;

[0020] P24, calculate the Kalman gain;

[0021] P25, perform the optimal estimation:

[0022] X k|k = X k|k-1 + K k (Z k - H k X k|k-1 )

[0023] where, X k|k-1 is the optimal estimated value at the previous moment, K k is the Kalman gain, H k is the control matrix, Z k is the clock error measurement value at the Kth moment, X k|k is the optimal estimated value obtained by this Kalman filter;

[0024] P26, perform the mean square error matrix estimation at the Kth moment for the prior estimation of the next moment;

[0025] The iterative filtering is implemented through steps P21 to P26; when the gap between the measurement value and the predicted value is greater than the set value, the measurement value is determined as an outlier and set to 0, and the predicted value is directly used for iterative filtering.

[0026] Furthermore, the separated platform containing the oven-controlled crystal oscillator specifically includes 2 platforms. One of them is set as the time reference platform, and the other is set as the platform to be synchronized.

[0027] Furthermore, in step P21, the setting of the initial conditions specifically includes: setting the initial clock error, setting the frequency stability, setting the frequency drift stability, and setting the initial covariance matrix.

[0028] Furthermore, in step S2, the performing of the clock error measurement between platforms and the processing of the measured clock error by using a filter include the following sub-steps:

[0029] P3: According to the RTT synchronization algorithm, obtain the arrival time TOA1 of the interrogation message and the arrival time TOA2 of the response message, and combine with the time slot length T slot of the RTT operation to calculate the measured clock error. The calculation formula is as follows:

[0030]

[0031] Furthermore, in step S3, the calculating of the frequency difference between platforms according to the frequency stability obtained by filtering specifically includes the following sub-steps:

[0032] P4: The second item output by the filter is the change rate of the clock error, that is, the frequency stability, without unit, expressed as:

[0033]

[0034] P5: There is the following relationship between the frequency difference stability and the frequency difference:

[0035] ε line ·f0≈f1 - f0;

[0036] By multiplying the frequency difference stability by the local oscillator frequency of the reference platform, the frequency difference between platforms can be obtained.

[0037] Furthermore, in step S4, according to the clock difference obtained by filtering and the calculated frequency difference, the clock difference drift trend is speculated, the clock difference at any time is obtained, and compensation and adjustment are performed according to the synchronization requirements to complete high-precision time-frequency synchronization, which specifically includes the following sub-steps:

[0038] P6: After iterative filtering by the fading adaptive Kalman filter, random time synchronization errors are filtered out;

[0039] P7: At the kth update node, the clock difference obtained by filtering is ε k , then the calculation formula for the clock difference at any time between clock difference update nodes is as follows:

[0040]

[0041] P8: The real-time frequency difference and the real-time clock difference are obtained. The frequency difference is realized by adjusting the clock, and online digital compensation is performed on the clock difference to achieve high-precision time-frequency synchronization of a distributed system containing a crystal oscillator with temperature control.

[0042] A high-precision time-frequency synchronization device based on a crystal oscillator with temperature control, comprising a processor and a memory, wherein a computer program is stored in the memory, and when the computer program is loaded and executed by the processor, the method described in any one of the above is performed.

[0043] The beneficial effects of the present invention include:

[0044] (1) The present invention designs a fading adaptive Kalman filter using a clock difference model to accurately measure the frequency difference between platforms of crystal oscillators with temperature control, eliminate outliers in measurement data, and speculate the clock difference drift trend, realizing high-precision time-frequency synchronization of a distributed system containing crystal oscillators with temperature control.

[0045] (2) The present invention can provide a high-precision time-frequency synchronization method based on a temperature-compensated crystal oscillator without changing the existing hardware and waveform software. In the inventive concept, a fading adaptive Kalman filter is designed according to the established clock error model, the data link RTT algorithm is used to obtain the clock error between distributed platforms, the measured clock error is passed through the filter to reduce the random error of the clock error, the real-time frequency difference between platforms is calculated according to the obtained frequency difference stability, and the clock error at any time is inferred. The clock error and frequency difference between platforms are compensated and adjusted according to the synchronization requirements, thereby realizing the replacement of a high-stability atomic clock with a temperature-compensated crystal oscillator and completing the high-precision time-frequency synchronization of a distributed system containing a temperature-compensated crystal oscillator.

[0046] (3) The present invention can accurately measure the time-frequency synchronization error of a temperature-compensated crystal oscillator system, realize the replacement of a high-stability atomic clock with a temperature-compensated crystal oscillator, and complete the high-precision time-frequency synchronization of a distributed system containing a temperature-compensated crystal oscillator. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0048] Figure 1 It is a schematic flowchart of a high-precision time-frequency synchronization method based on a temperature-compensated crystal oscillator in an embodiment of the present invention;

[0049] Figure 2 It is a schematic flowchart of laboratory test verification in an embodiment of the present invention;

[0050] Figure 3 It is a RTT measured clock error graph in laboratory tests in an embodiment of the present invention;

[0051] Figure 4 It is a linear fitting residual graph of the RTT measured clock error in an embodiment of the present invention;

[0052] Figure 5 It is a comparison graph of the measured frequency and the true frequency of the platform to be synchronized in an embodiment of the present invention;

[0053] Figure 6 It is a frequency difference graph between separated platforms at a 100 MHz fundamental frequency in an embodiment of the present invention;

[0054] Figure 7 It is a step flowchart of the method in an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0055] All features disclosed in all embodiments in this specification, or steps in all methods or processes implicitly disclosed, except for mutually exclusive features and / or steps, can be combined and / or extended, replaced in any way.

[0056] The specific implementation process of the present invention is as follows:

[0057] In a preferred embodiment, a high-precision time-frequency synchronization scheme based on fading adaptive Kalman filtering is specifically provided. By establishing a clock error model, a fading adaptive Kalman filter is designed. The data link RTT algorithm is used to measure the clock error between distributed platforms with an oven-controlled crystal oscillator. The measured clock error is used to accurately estimate the system frequency difference through the fading adaptive Kalman filter, and the drift trend of the predicted clock error is estimated. Specifically, as Figure 1 and Figure 7 shown, a high-precision time-frequency synchronization method based on an oven-controlled crystal oscillator provided by the present invention performs the following steps:

[0058] S1, establish a clock error model and design a fading adaptive Kalman filter;

[0059] In the specific implementation, it specifically includes sub-steps:

[0060] P1: Let the local oscillator frequency of the reference platform be f0, and the local oscillator frequency of the platform to be synchronized be f1. A clock error model representing the change of the clock error over time can be established as shown in the following formula, where ε0 is the initial clock error, and the unit is seconds.

[0061]

[0062] P2: Use the clock error model to design a fading adaptive Kalman filter, including the following steps:

[0063] (1) Set the initial conditions, including: the initial clock error, frequency difference stability, frequency drift stability, and the initial covariance matrix;

[0064] (2) Establish a state transition matrix through the clock error model, and perform a priori estimation based on the state transition matrix and the optimal estimation value at the previous moment to obtain the a priori estimation value at this moment;

[0065] (3) Introduce an adaptive fading factor, and combine the optimal estimation covariance matrix at the previous moment to predict the a priori estimation covariance matrix;

[0066] (4) Calculate the Kalman gain;

[0067] (5) Perform optimal estimation:

[0068] X k|k =X k|k-1 +K k (Z k -Hk X k|k-1 );

[0069] Among them, X k|k-1 is the optimal estimated value at the previous moment, and K k is the Kalman gain, and H k is the control matrix, and Z k is the clock error measurement value at the Kth moment, and X k|k is the optimal estimated value obtained by this Kalman filter;

[0070] (6) Perform the mean square error matrix estimation at the Kth moment for the prior estimation of the next moment.

[0071] Iterative filtering is achieved through the above steps. When the gap between the measurement value and the predicted value is too large, the measurement value is determined to be an outlier and set to 0, and the predicted value is directly used for iterative filtering.

[0072] S2. Set one of the distributed platforms with an oven-controlled crystal oscillator as the time reference platform and the other as the platform to be synchronized, and use the data link RTT algorithm to measure the clock error between the platforms and use a filter to process the measured clock error;

[0073] In the specific implementation, using the data link RTT algorithm to measure the clock error between the platforms specifically includes the following sub-steps:

[0074] P3: According to the RTT synchronization algorithm, obtain the arrival time TOA1 of the query message and the arrival time TOA2 of the response message, and combine the time slot length T slot of the RTT operation to calculate the measured clock error, and the calculation formula is as follows:

[0075]

[0076] S3. Calculate the frequency difference between the platforms according to the frequency difference stability obtained by filtering;

[0077] In the specific implementation, calculating the frequency difference between the platforms according to the frequency difference stability obtained by filtering specifically includes the following sub-steps:

[0078] P4: The second item output by the filter is the change rate of the clock error, that is, the frequency difference stability, which has no unit and can be expressed as:

[0079]

[0080] P5: Since there is the following relationship between the frequency difference stability and the frequency difference:

[0081] ε line ·f0≈f1 - f0;

[0082] Therefore, multiplying the frequency difference stability by the local oscillator frequency of the reference platform can obtain the frequency difference between the platforms.

[0083] S4. Infer the clock drift trend based on the clock offset obtained by filtering and the calculated frequency offset, obtain the clock offset at any time, and perform compensation and adjustment according to the synchronization requirements to achieve high-precision time-frequency synchronization.

[0084] In specific implementation, infer the clock drift trend based on the clock offset obtained by filtering and the calculated frequency offset, obtain the clock offset at any time, and perform compensation and adjustment according to the synchronization requirements to achieve high-precision time-frequency synchronization, which specifically includes sub-steps:

[0085] P6: After iterative filtering by the fading adaptive Kalman filter, compared with the measured clock offset, the output clock offset filters out the random time synchronization error, and the accuracy of the clock offset is effectively improved.

[0086] P7: When the frequency offset is fixed, the clock offset drifts linearly; when the frequency offset changes, the clock offset drifts non-linearly according to the change law of the frequency offset. Assume that at the k-th update node, the clock offset obtained by filtering is ε k , then the calculation formula for the clock offset at any time between clock offset update nodes is as follows:

[0087]

[0088] P8: Obtain the real-time frequency offset and real-time clock offset. The frequency offset can be achieved by adjusting the clock, and the clock offset can be compensated digitally online, then high-precision time-frequency synchronization of the distributed system with an oven-controlled crystal oscillator can be achieved.

[0089] In further other specific implementations, in particular, a high-precision time-frequency synchronization scheme based on the fading adaptive Kalman filter is provided, which specifically includes the following steps:

[0090] P1: Assume that the local oscillator frequency of the reference platform is f0 and the local oscillator frequency of the platform to be synchronized is f1. A clock offset model representing the change of the clock offset with time can be established as shown in the following formula, where ε0 is the initial clock offset and the unit is seconds.

[0091]

[0092] P2: Design a fading adaptive Kalman filter using the clock offset model, which includes the following steps:

[0093] (1) Set the initial conditions, including: the initial clock offset, the frequency offset stability, the frequency drift stability, and the initial covariance matrix;

[0094] (2) Establish a state transition matrix through the clock offset model, and perform a priori estimation based on the state transition matrix and the optimal estimation value of the previous moment to obtain the a priori estimation value at this moment;

[0095] (3) Introduce an adaptive fading factor, and combine it with the optimal estimation covariance matrix at the previous moment to predict the prior estimation covariance matrix;

[0096] (4) Calculate the Kalman gain;

[0097] (5) Perform optimal estimation:

[0098] X k|k = X k|k-1 + K k (Z k - H k X k|k-1 );

[0099] where X k|k-1 is the optimal estimation value at the previous moment, K k is the Kalman gain, H k is the control matrix, Z k is the clock difference measurement value at time K, and X k|k is the optimal estimation value obtained by this Kalman filter;

[0100] (6) Perform the mean square error matrix estimation at time K for the prior estimation of the next moment.

[0101] Iterative filtering is achieved through the above steps. When the gap between the measurement value and the predicted value is too large, the measurement value is determined to be an outlier and set to 0, and the predicted value is directly used for iterative filtering.

[0102] P3: According to the RTT synchronization algorithm, obtain the arrival time TOA1 of the interrogation message and the arrival time TOA2 of the response message, and combine the time slot length T slot of the RTT operation to calculate the measured clock difference. The calculation formula is as follows:

[0103] P4: The second item output by the filter is the rate of change of the clock difference, that is, the frequency difference stability, which has no unit and can be expressed as:

[0104]

[0105] P5: Since there is the following relationship between the frequency difference stability and the frequency difference:

[0106] ε line ·f0 ≈ f1 - f0;

[0107] Therefore, multiplying the frequency difference stability by the local oscillator frequency of the reference platform can obtain the frequency difference between platforms.

[0108] P6: After iterative filtering by the fading adaptive Kalman filter, the output clock difference filters out the random time synchronization error compared with the measured clock difference, and the accuracy of the clock difference is effectively improved.

[0109] P7: When the frequency difference is fixed, the clock error shows a linear drift; when the frequency difference changes, the clock error shows a non-linear drift according to the change law of the frequency difference. Let the clock error obtained by filtering at the k-th update node be ε k , then the calculation formula for the clock error value at any time between the clock error update nodes is as follows:

[0110]

[0111] P8: By obtaining the real-time frequency difference and real-time clock error, the frequency difference can be adjusted by the clock, and the clock error can be compensated digitally online, thus achieving high-precision time-frequency synchronization for a distributed system containing an oven-controlled crystal oscillator.

[0112] The technical effects of the present invention are verified as follows:

[0113] Test scenario: Collect RTT clock error data of the data link (including data collected in a laboratory scenario). The update period of RTT is 12 s. The reference platform uses a rubidium clock with a local oscillator frequency of 100 MHz, and the platform to be synchronized uses an oven-controlled crystal oscillator. The RS spectrum analyzer with a frequency measurement accuracy of 0.1 Hz is calibrated with the 100 MHz rubidium clock as the reference, and the frequency of the platform to be synchronized is measured with the spectrum analyzer. The frequency difference between the two nodes is the difference between 100 MHz and the frequency of the platform to be synchronized measured by the spectrum analyzer, with an accuracy of 0.1 Hz.

[0114] Perform adaptive Kalman filtering on the clock error data to obtain the frequency difference stability, and multiply it by 100 MHz to obtain the real-time frequency difference between the platforms. By comparing it with the true value of the frequency difference, the accuracy of the adaptive Kalman filtering algorithm for calculating the frequency difference of the distributed platforms can be verified.

[0115] Experimental analysis of the technical solution of the present invention: Figure 2 is the workflow diagram of this experiment. Using the 100 MHz rubidium clock as the reference platform and calibrating it with the RS spectrum analyzer, measuring the frequency of the oven-controlled crystal oscillator with the calibrated spectrum analyzer, calculating the true value of the frequency difference, and at the same time collecting the clock error between the rubidium clock and the oven-controlled crystal oscillator using the data link RTT. Pass the measured clock error through the fading adaptive Kalman filter to obtain the frequency difference between the platforms, and compare the measured frequency difference with the true frequency difference to verify the accuracy of the fading adaptive Kalman filter for measuring the frequency difference.

[0116] Figure 3 is to measure the clock error between the rubidium clock and the oven-controlled crystal oscillator platform using the data link RTT. The measurement time is 3000 s, and the clock error between the platforms drifts by 4500 μs.

[0117] Figure 4 is the residual diagram of the clock error after linearly fitting the measured clock error curve. It can be seen from the residual diagram the non-linear drift of the clock error caused by the change of the frequency difference between the platforms. The residual range is between 0 - 200 ns, and outliers appear in the measured clock error curve.

[0118] Figure 5 It is a comparison chart of the frequency of the oven-controlled crystal oscillator calculated by the fading adaptive Kalman filter and the frequency of the oven-controlled crystal oscillator measured by the spectrum analyzer. The results of the filter are: 99.99980980 - 99.9998092 MHz, with a drift of approximately 0.2 Hz in 2000 s. Limited by the accuracy of the spectrum analyzer at 0.1 Hz, the frequency difference error after filtering is within 0.1 Hz.

[0119] Therefore, in the technical solution of the present invention, the adaptive Kalman filter can accurately measure the frequency difference between platforms and eliminate outliers.

[0120] It should be noted that within the scope of protection defined in the claims of the present invention, the following embodiments can be combined and / or extended, replaced in any logical manner from the above specific embodiments, such as the disclosed technical principles, disclosed technical features or implicitly disclosed technical features.

[0121] Embodiment 1

[0122] A high-precision time-frequency synchronization method based on an oven-controlled crystal oscillator includes the following steps:

[0123] S1. Establish a clock difference model and design a fading adaptive Kalman filter;

[0124] S2. Set a time reference platform and a platform to be synchronized in the distributed platforms containing oven-controlled crystal oscillators, measure the clock difference between the platforms, and process the measured clock difference using the filter;

[0125] S3. Calculate the frequency difference between the platforms according to the frequency difference stability obtained by filtering;

[0126] S4. Infer the clock difference drift trend based on the clock difference obtained by filtering and the calculated frequency difference, obtain the clock difference at any time, and perform compensation and adjustment according to the synchronization requirements to complete high-precision time-frequency synchronization.

[0127] Embodiment 2

[0128] Based on Embodiment 1, in step S1, the establishment of the clock difference model and the design of the fading adaptive Kalman filter specifically include the following sub-steps:

[0129] P1: Assume that the local oscillator frequency of the reference platform is f0 and the local oscillator frequency of the platform to be synchronized is f1, and establish the following clock difference model representing the change of the clock difference with time:

[0130]

[0131] where ε0 is the initial clock difference, and the unit is seconds;

[0132] P2: Use the clock difference model to design a fading adaptive Kalman filter, including the following steps:

[0133] P21, Set initial conditions;

[0134] P22, Establish a state transition matrix through the clock error model, perform a priori estimation based on the state transition matrix and the optimal estimated value at the previous moment, and obtain the a priori estimated value at this moment;

[0135] P23, Introduce an adaptive fading factor, and combine with the optimal estimated covariance matrix at the previous moment to predict the a priori estimated covariance matrix;

[0136] P24, Calculate the Kalman gain;

[0137] P25, Perform optimal estimation:

[0138] X k|k = X k|k-1 + K k (Z k - H k X k|k-1 )

[0139] where, X k|k-1 is the optimal estimated value at the previous moment, K k is the Kalman gain, H k is the control matrix, Z k is the clock error measurement value at time K, and X k|k is the optimal estimated value obtained by this Kalman filter;

[0140] P26, Perform the mean square error matrix estimation at time K for the a priori estimation at the next moment;

[0141] The iterative filtering is realized through steps P21 to P26; when the gap between the measured value and the predicted value is greater than the set value, the measured value is determined as an outlier and set to 0, and the predicted value is directly used for iterative filtering.

[0142] Example 3

[0143] Based on Example 1, the separated platform containing the oven-controlled crystal oscillator specifically includes 2 platforms. One of them is set as the time reference platform, and the other is set as the platform to be synchronized.

[0144] Example 4

[0145] Based on Example 2, in step P21, the setting of the initial conditions specifically includes: setting the initial clock error, setting the frequency stability, setting the frequency drift stability, and setting the initial covariance matrix.

[0146] Example 5

[0147] Based on Embodiment 1, in step S2, the inter-platform clock difference measurement and the filtering processing of the measured clock difference include the following sub-steps:

[0148] P3: According to the RTT synchronization algorithm, obtain the time of arrival TOA1 of the interrogation message and the time of arrival TOA2 of the response message, and combine the time slot length T of the RTT operation slot , and calculate the measured clock difference. The calculation formula is as follows:

[0149]

[0150] Embodiment 6

[0151] Based on Embodiment 1, in step S3, calculating the inter-platform frequency difference according to the frequency difference stability obtained by filtering specifically includes the following sub-steps:

[0152] P4: The second item output by the filter is the change rate of the clock difference, that is, the frequency difference stability, which has no unit and is expressed as:

[0153]

[0154] P5: There is the following relationship between the frequency difference stability and the frequency difference:

[0155] ε line ·f0≈f1 - f0;

[0156] Multiply the frequency difference stability by the local oscillator frequency of the reference platform to obtain the inter-platform frequency difference.

[0157] Embodiment 7

[0158] Based on Embodiment 2, in step S4, infer the clock difference drift trend according to the clock difference obtained by filtering and the calculated frequency difference, obtain the clock difference at any time, and perform compensation and adjustment according to the synchronization requirements to complete high-precision time-frequency synchronization. Specifically, it includes the following sub-steps:

[0159] P6: After iterative filtering by the fading adaptive Kalman filter, filter out the random time synchronization error;

[0160] P7: Assume that at the kth update node, the clock difference obtained by filtering is ε k , then the calculation formula for the clock difference at any time between the clock difference update nodes is as follows:

[0161]

[0162] P8: Obtain the real-time frequency difference and the real-time clock difference. The frequency difference is achieved by adjusting the clock, and online digital compensation is performed on the clock difference to achieve high-precision time-frequency synchronization of the distributed system containing the oven-controlled crystal oscillator.

[0163] Embodiment 8

[0164] A high-precision time-frequency synchronization device based on a crystal oscillator with temperature compensation, comprising a processor and a memory, wherein a computer program is stored in the memory, and when the computer program is loaded and executed by the processor, the method described in any one of Embodiments 1 to 7 is performed.

[0165] The units involved in the embodiments of the present invention can be implemented in software or in hardware, and the described units can also be provided in the processor. Among them, the names of these units do not constitute a limitation to the units themselves in some cases.

[0166] According to one aspect of the embodiments of the present invention, there is provided a computer program product or a computer program, which includes computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes the methods provided in the above various alternative implementation manners.

[0167] As another aspect, the embodiments of the present invention further provide a computer-readable medium, which may be included in the electronic device described in the above embodiments; or may exist separately without being assembled into the electronic device. The above computer-readable medium carries one or more programs, and when the one or more programs are executed by an electronic device, the electronic device implements the methods described in the above embodiments.

Claims

1. A high-precision time-frequency synchronization method based on a constant temperature crystal oscillator, characterized in that: The following steps are involved: S1, establish clock error model and design fading adaptive Kalman filter; S2, setting a time reference platform and a platform to be synchronized in a separate platform containing a constant temperature crystal oscillator, measuring the clock difference between the platforms and using a filter to process the measured clock difference; S3, calculating the frequency difference between platforms according to the frequency difference stability obtained by filtering; S4, infer the clock error drift trend based on the clock error obtained by filtering and the calculated frequency error, obtain the clock error at any time, and compensate and adjust according to the synchronization requirements to complete high-precision time and frequency synchronization.

2. The high-precision time-frequency synchronization method based on a constant temperature crystal oscillator according to claim 1, characterized in that: In step S1, the clock error model is established and the fading adaptive Kalman filter is designed, which specifically includes the following sub-steps: P1: Assume that the local oscillator frequency of the reference platform is f0, and the local oscillator frequency of the platform to be synchronized is f1. The following clock error model is established to represent the change of clock error over time: Among them, ε0 is the initial clock difference, in seconds; P2: Designing a fading adaptive Kalman filter using a clock error model includes the following steps: P21, set initial conditions; P22, establish a state transfer matrix through the clock error model, perform a priori estimation based on the state transfer matrix and the optimal estimate at the previous moment, and obtain the a priori estimate at this moment; P23, introduces an adaptive fading factor, combines the optimal estimated covariance matrix at the previous moment, and predicts the prior estimated covariance matrix; P24, calculate Kalman gain; P25, make the optimal estimate: X k|k =X k|k-1 +K k (Z k -H k X k|k-1 ) Among them, X k|k-1 is the optimal estimate of the previous moment, K k is the Kalman gain, H k is the control matrix, Z k is the clock difference measurement value at time K, X k|k is the optimal estimate obtained by this Kalman filter; P26, estimate the mean square error matrix at time K, which is used for the prior estimation at the next time; Iterative filtering is implemented through steps P21 to P26; when the difference between the measured value and the predicted value is greater than the set value, the measured value is determined to be a wild value and is set to 0, and iterative filtering is performed directly using the predicted value.

3. The high-precision time-frequency synchronization method based on a constant temperature crystal oscillator according to claim 1, characterized in that: The split platform containing the constant temperature crystal oscillator specifically includes two platforms, one of which is set as the time reference platform, and the other is set as the platform to be synchronized.

4. The high-precision time-frequency synchronization method based on a constant temperature crystal oscillator according to claim 2, characterized in that: In step P21, the setting of initial conditions specifically includes: setting an initial clock difference, setting a frequency difference stability, setting a frequency drift stability, and setting an initial covariance matrix.

5. The high-precision time-frequency synchronization method based on a constant temperature crystal oscillator according to claim 1, characterized in that: In step S2, the clock difference measurement between platforms and the use of filters to process the measured clock difference include the following sub-steps: P3: According to the RTT synchronization algorithm, the arrival time TOA1 of the inquiry message and the arrival time TOA2 of the response message are obtained, combined with the time slot length T of the RTT operation. slot , calculate the measured clock error, the calculation formula is as follows:

6. The high-precision time-frequency synchronization method based on a constant temperature crystal oscillator according to claim 1, characterized in that: In step S3, the frequency difference between platforms is calculated according to the frequency difference stability obtained by filtering, which specifically includes the following sub-steps: P4: The second item of the filter output is the rate of change of the clock error, that is, the frequency error stability, which has no unit and is expressed as: P5: There is the following relationship between frequency difference stability and frequency difference: ε line ·f0≈f1-f0; The frequency difference between platforms can be obtained by multiplying the frequency difference stability by the local oscillator frequency of the reference platform.

7. The high-precision time-frequency synchronization method based on a constant temperature crystal oscillator according to claim 2, characterized in that: In step S4, the clock error drift trend is estimated based on the clock error obtained by filtering and the calculated frequency error, the clock error at any time is obtained, and compensation and adjustment are performed according to the synchronization requirements to complete high-precision time and frequency synchronization, which specifically includes the following sub-steps: P6: Iterative filtering by fading adaptive Kalman filter to remove random time synchronization errors; P7: Assume that at the kth update node, the clock error obtained by filtering is ε k , then the calculation formula for the clock difference value at any time between the clock difference update nodes is as follows: P8: Get the real-time frequency difference and real-time clock difference. The frequency difference is achieved by adjusting the clock. The clock difference is compensated online digitally to achieve high-precision time and frequency synchronization of distributed systems containing constant temperature crystal oscillators.

8. A high-precision time-frequency synchronization device based on a constant temperature crystal oscillator, characterized in that: The method comprises a processor and a memory, wherein a computer program is stored in the memory, and when the computer program is loaded by the processor, the method according to any one of claims 1 to 7 is executed.

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