GNSS-based high-stability crystal oscillator taming and holding system and method

Abstract

The application discloses a high-stable crystal oscillator taming and keeping system and method based on GNSS, which comprises a GNSS receiver board and an OCXO crystal oscillator FPGA, wherein the second pulse signal output end of the GNSS receiver board and the FPGA is connected to a phase difference measuring module, the output end of the phase difference measuring module is connected to a processor, the output end of the processor is connected to a D / A conversion module, the output end of the D / A conversion module is connected to the OCXO crystal oscillator through a signal conditioning circuit, the second pulse signal of the OCXO crystal oscillator is output after frequency division by the FPGA, and a temperature sensor is connected to the OCXO crystal oscillator. The application can realize automatic keeping of the crystal oscillator frequency.

Description

Technical Field

[0001] This invention belongs to the field of BeiDou timing technology, specifically relating to a GNSS-based high-stability crystal oscillator discipline and maintenance system and method, which is used to discipline BeiDou products to obtain high-precision timing by disciplining fast crystal oscillators, thereby improving the discipline and maintenance accuracy of BeiDou product crystal oscillators. Background Technology

[0002] Yang Shaochen (2016) from the Rocket Force Engineering University established an aging model for crystal oscillators, incorporating temperature as an accelerating stress into the model parameters. He used historical data and the maximum likelihood estimation method to estimate the model's diffusion parameters, and employed Kalman filtering to estimate drift parameters. This allowed him to predict the frequency drift of crystal oscillators that had lost GPS signals, thus compensating for the system frequency. However, this model cannot distinguish between the individual effects of aging and temperature on the crystal oscillator's frequency, and it cannot make accurate predictions when the system temperature is high.

[0003] Ma Yanqing (2011) of Xi'an University of Electronic Science and Technology used a 1PPS signal to lock onto an OCXO. After the GPS signal failed, the OCXO holding algorithm enabled the crystal oscillator to maintain a high frequency accuracy for a certain period of time, with the accuracy remaining at 1×10⁻¹⁰ for 3 hours after the signal failure. However, the frequency accuracy of the system showed a monotonically decreasing trend during the holding period, indicating that the algorithm had limited compensation for crystal oscillator aging.

[0004] Tan Songrong (2014) of South China University of Technology implemented a clock hold algorithm for LTE base stations based on OCXO. The algorithm uses recursive least squares with a forgetting factor to obtain the parameter estimates of the crystal oscillator. When the GPS receiver is in hold mode, the system uses a linear model to obtain the voltage control data of the cryogenic crystal oscillator and continuously calibrates the cryogenic crystal oscillator. After 12 hours of training, the even-second error of the system is 600 ns. However, it does not consider the aging rate-frequency characteristics of the crystal oscillator and does not establish a complete prediction model.

[0005] Primary frequency standards, such as hydrogen clocks and cesium clocks, possess high frequency accuracy and stability; however, they are large, expensive, and have stringent environmental requirements. Conversely, secondary frequency standards are cheaper, have less stringent environmental requirements, and offer good short-term stability, but suffer from poor frequency accuracy and long-term stability. Therefore, it is necessary to combine the advantages of both to improve the frequency accuracy and long-term stability of the secondary frequency standard while minimizing the impact on its short-term stability. Currently, this is mainly achieved by using a standard 1PPS signal output from the receiver after processing satellite signals to lock onto the local crystal oscillator. If the satellite signal is lost, the crystal oscillator is in an uncalibrated state, at which point its frequency accuracy cannot be maintained, and the frequency accuracy error gradually increases due to aging.

[0006] [1] Yang Shaochen, Hu Changhua, Li Hongzeng. Frequency preservation method for GPS calibration crystal oscillator frequency source based on Wiener process [J]. China Measurement & Control, 2016, 42(06): 14-18.

[0007] [2] Ma Yanqing. Research on Adaptive Discipline and Maintenance Technology of OCXO with Oven Temperature [D]. Xi'an University of Electronic Science and Technology, 2011.

[0008] [3] Tan Songrong. Research on Clock System Hold Algorithm for LTE Base Stations Based on OCXO [D]. South China University of Technology, 2014. Summary of the Invention

[0009] The purpose of this invention is to provide a GNSS-based high-stability crystal oscillator discipline and holding system and method to overcome the shortcomings of the prior art. In the crystal oscillator discipline stage, this invention models the aging frequency characteristics and temperature frequency characteristics of the crystal oscillator; in the crystal oscillator holding stage (when the GNSS signal is lost), it predicts the crystal oscillator frequency error compensation amount based on the model of the discipline stage, thereby improving the accuracy and stability of the crystal oscillator output frequency.

[0010] To achieve the above objectives, the present invention adopts the following technical solution:

[0011] A GNSS-based high-stability crystal oscillator discipline and hold system includes a GNSS receiver board and an OCXO crystal FPGA. The second pulse signal output of the GNSS receiver board and the FPGA is connected to a phase difference measurement module. The output of the phase difference measurement module is connected to a processor. The output of the processor is connected to a D / A conversion module. The output of the D / A conversion module is connected to the OCXO crystal oscillator through a signal conditioning circuit. The second pulse signal of the OCXO crystal oscillator is output after frequency division by the FPGA. A temperature sensor is connected to the OCXO crystal oscillator.

[0012] Furthermore, the processor is an STM32 processor.

[0013] Furthermore, the temperature sensor is a DS18B20.

[0014] Furthermore, the D / A conversion module adopts DAC1220.

[0015] Furthermore, the processor is equipped with two IIR filters, which are used to filter out aging and temperature-related factors in the phase difference, respectively.

[0016] A GNSS-based method for disciplining and holding crystal oscillators includes two working modes: locked disciplining mode and unlocked holding mode.

[0017] When the GNSS receiver board outputs a second pulse signal normally, it is in locked discipline mode. At this time, the phase difference measurement module is used to measure the phase difference between the second pulse signal of the GNSS receiver board and the second pulse signal of the OCXO crystal oscillator. The frequency deviation of the OCXO crystal oscillator is calculated by the phase difference and converted into a digital quantity of the crystal oscillator control voltage. The crystal oscillator control voltage is then obtained through the D / A conversion module to calibrate the output frequency of the OCXO crystal oscillator in real time. At the same time, the working time of the OCXO crystal oscillator and the temperature sensor value are recorded to model the temperature frequency characteristics and aging frequency characteristics of the OCXO crystal oscillator.

[0018] When the GNSS receiver board fails to output the second pulse signal normally, it switches to the unlock-and-hold mode. If the modeling is completed at this time, the model established in the locked-and-disciplined mode is used to predict the OCXO crystal frequency deviation and compensate for the OCXO crystal output frequency to achieve automatic holding of the OCXO crystal frequency. If the modeling is not completed at this time, the moving average of the most recent frequency deviations is calculated and the OCXO crystal output frequency is compensated to achieve automatic holding of the OCXO crystal frequency.

[0019] Furthermore, the step of using a phase difference measurement module to measure the phase difference between the second pulse signal of the GNSS receiver board and the second pulse signal of the OCXO crystal oscillator, and calculating the frequency deviation of the OCXO crystal oscillator based on the phase difference, specifically involves:

[0020] The phase difference measurement module measures the phase difference between the second pulse signal output from the GNSS receiver board and the second pulse signal from the OCXO crystal oscillator obtained by frequency division via the FPGA. The phase difference measurement value is then filtered in the processor, and the OCXO crystal oscillator frequency deviation is calculated using the filtered phase difference.

[0021]

[0022] Where Δf is the OCXO crystal frequency deviation, f0 is the OCXO crystal nominal frequency, ΔT is the filtered phase difference, and τ is the sampling interval of the phase difference measurement module.

[0023] Furthermore, the process of converting the frequency deviation of the OCXO crystal oscillator into a digital value of the crystal oscillator control voltage, and then obtaining the crystal oscillator control voltage through a D / A conversion module to calibrate the OCXO crystal oscillator output frequency in real time, specifically involves:

[0024] Based on the frequency deviation of the OCXO crystal oscillator, the digital quantity of the crystal oscillator control voltage is calculated using the voltage control sensitivity coefficient K of the OCXO crystal oscillator. Then, it is converted into the crystal oscillator control voltage U=U0+Δf / K through the D / A conversion module to achieve real-time calibration of the OCXO crystal oscillator output frequency.

[0025] Furthermore, the recording of the OCXO crystal oscillator's operating time and temperature sensor values, and the modeling of the OCXO crystal oscillator's temperature-frequency characteristics and aging-frequency characteristics, specifically involve:

[0026] Establish mathematical models for the relationship between crystal oscillator operating time and frequency deviation, as well as mathematical models for the relationship between crystal oscillator temperature and frequency deviation;

[0027] The mathematical model between the crystal oscillator's operating time and frequency deviation is as follows:

[0028] f t (t)=a0+a1t+ε(t)

[0029] Where t is the crystal oscillator operating time, f t (t) represents the crystal oscillator frequency deviation caused by aging, ε(t) represents the aging effect part of the random deviation of the crystal oscillator frequency and the measurement error, a0 represents the initial frequency offset of the aging part, and a1 represents the aging coefficient.

[0030] The mathematical model between the crystal oscillator temperature and frequency error is as follows:

[0031] f T (T)=b0+b1T+υ(T)

[0032] Where T is the crystal oscillator temperature, f T (T) represents the temperature-induced frequency deviation of the crystal oscillator, υ(T) represents the temperature-dependent random frequency deviation and measurement error of the crystal oscillator, b0 represents the initial frequency shift due to temperature, and b1 represents the temperature coefficient.

[0033] The phase difference data is separated by two IIR filters configured in the processor to isolate the aging-related components of the random deviation and measurement error of the crystal oscillator frequency, as well as the temperature-related components. The frequency deviation f is then calculated. T (T) and f t (t), by fitting the frequency deviation with temperature and time information respectively, the parameters a0 and a1 and parameters b0 and b1 are obtained, thereby establishing the temperature frequency characteristic model and the aging frequency characteristic model.

[0034] Furthermore, the process of fitting the frequency deviation with temperature and time information to obtain parameters a0 and a1 and parameters b0 and b1, respectively, is as follows:

[0035] The parameters a0 and a1 of the temperature frequency characteristic model and the parameters b0 and b1 of the aging frequency characteristic model are fitted using the recursive least squares method with a forgetting factor, respectively. The recursive least squares formula with forgetting factor is as follows:

[0036]

[0037]

[0038]

[0039] Where k represents the k-th recursion. Let y(k) represent the estimated model parameters at time k, and y(k) be the frequency error observation. Let K(k) be the temperature or crystal oscillator time observation at time k-1, K(k) be the gain vector, P(k) be the covariance matrix, and λ∈(0,1) be the forgetting factor.

[0040] For the aging frequency characteristic model:

[0041] y(k)=f t (k),

[0042] For the temperature-frequency characteristic model:

[0043] y(k)=f T (k),

[0044] The parameters a0 and a1 of the temperature frequency characteristic model and the parameters b0 and b1 of the aging frequency characteristic model are fitted using the above formulas.

[0045] Compared with the prior art, the present invention has the following beneficial technical effects:

[0046] This invention uses the second pulse signal from GNSS to tame the crystal oscillator and records the crystal oscillator's operating time and temperature. It uses a recursive least squares method with a forgetting factor to calculate and predict the temperature coefficient and aging coefficient. When there is no second pulse signal (GNSS signal failure), the predicted aging coefficient and temperature coefficient are used to calculate the crystal oscillator frequency offset compensation, thereby achieving automatic maintenance of the crystal oscillator frequency.

[0047] The crystal oscillator's discipline and hold modes were tested using a test platform. The results showed that after rapid discipline, the crystal oscillator's frequency accuracy improved from 2.2 × 10⁻⁸ to 5.5 × 10⁻¹¹, an improvement of nearly three orders of magnitude. After disconnecting the GNSS signal, the crystal oscillator's phase drift over 24 hours was approximately 4 ms, compared to 1900 ms during free drift, representing a performance improvement of about three orders of magnitude. Attached Figure Description

[0048] The accompanying drawings are provided to further understand the invention and constitute a part of this invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an improper limitation of the invention.

[0049] Figure 1This is a schematic diagram of the GNSS-based high-stability crystal oscillator discipline and hold system structure of the present invention;

[0050] Figure 2 This is a schematic diagram of the GNSS-based high-stability crystal oscillator discipline and maintenance method of the present invention;

[0051] Figure 3 This is a connection diagram for the 1PPS accuracy test of the Beidou timing terminal in an embodiment of the present invention. Detailed Implementation

[0052] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0053] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0054] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0055] This invention models the aging frequency characteristics and temperature frequency characteristics of a crystal oscillator using a recursive least squares method with a forgetting factor, and uses two IIR filters to separate the aging and temperature influencing factors. During the crystal oscillator training phase, the aging and temperature frequency characteristics are modeled; during the crystal oscillator holding phase (when the GNSS signal is lost), the crystal oscillator frequency error compensation is predicted based on the model from the training phase, thereby improving the accuracy and stability of the crystal oscillator output frequency.

[0056] When the GNSS receiver locks onto a satellite signal and outputs a 1PPS signal through the GNSS receiver board, the OCXO crystal oscillator is in the lock-and-training phase. At this time, the phase difference measurement module uses a counter to measure the phase difference between the 1PPS signal from the GNSS receiver board and the second pulse signal from the OCXO crystal oscillator to calculate the frequency deviation of the OCXO crystal oscillator. This frequency deviation is converted into a digital value for the crystal oscillator control voltage, which is then converted to digital value via D / A conversion to calibrate the crystal oscillator output frequency in real time. Simultaneously, the crystal oscillator operating time and temperature sensor values ​​are recorded. A recursive least squares method with a forgetting factor is used to model the temperature-frequency characteristics and aging-frequency characteristics of the crystal oscillator. When the GNSS receiver is affected by interference or other factors and cannot output a 1PPS signal normally, the crystal oscillator enters the hold phase. The model established in the training phase is used to predict the crystal oscillator frequency deviation and compensate for the crystal oscillator output frequency, thereby achieving automatic frequency hold.

[0057] Crystal oscillator discipline and hold hardware block diagram as follows Figure 1 As shown, the counter in the phase difference measurement module measures the phase difference between the 1PPS second pulse signal output by the GNSS timing and positioning receiver and the crystal oscillator second pulse signal obtained by frequency division via the FPGA. Then, a Kalman filter algorithm is run in the STM32 to filter the phase difference measurement value, eliminating jitter in the GNSS second pulse signal. The formula for calculating the frequency deviation based on the phase difference is as follows:

[0058]

[0059] Where Δf is the OCXO crystal frequency deviation, f0 is the OCXO crystal nominal frequency, ΔT is the filtered phase difference, and τ is the sampling interval of the phase difference measurement module.

[0060] The frequency deviation of the crystal oscillator can be obtained based on the phase difference and nominal frequency. The digital quantity of the crystal oscillator control voltage is calculated using the voltage-controlled sensitivity coefficient K, and then converted into a crystal oscillator control voltage U = U0 + Δf / K via a DAC1220, thus achieving real-time adjustment of the crystal oscillator frequency. Crystal oscillators age relatively slowly; aging indicators are typically expressed as annual aging rate, such as ±0.05ppm (Parts per Million), while the daily aging rate is approximately constant. A mathematical model can be established between the crystal oscillator's operating time and frequency error.

[0061] f t (t)=a0+a1t+ε(t) (2)

[0062] Where t is the crystal oscillator operating time, f t (t) represents the crystal oscillator frequency error caused by aging, ε(t) represents the aging effect part of the random deviation and measurement error of the crystal oscillator frequency, a0 represents the initial frequency offset of the aging part, and a1 represents the aging coefficient.

[0063] The mathematical model between crystal oscillator temperature and frequency error is as follows:

[0064] f T (T)=b0+b1T+υ(T) (3)

[0065] Where T is the crystal oscillator temperature, f T (T) represents the crystal oscillator frequency error caused by temperature, υ(T) represents the temperature-dependent random deviation and measurement error of the crystal oscillator frequency, b0 represents the initial frequency offset due to temperature, and b1 represents the temperature coefficient.

[0066] When the crystal oscillator is in a disciplined state, the system automatically records the crystal oscillator's operating time and ambient temperature. Using an IIR filter, it separates the temperature-induced and aging-induced variations in the phase difference data, and calculates the frequency difference f. T (T) and f t (t). The frequency difference is fitted with temperature and time information to obtain the parameters a0 and a1 in equation (2) and the parameters b0 and b1 in equation (3), thereby establishing the temperature model and the aging model. This invention uses a recursive least squares method with a forgetting factor to fit the temperature model parameters and the aging model parameters respectively. The recursive least squares formula with the forgetting factor is as follows:

[0067]

[0068] Where k represents the k-th recursion. Let y(k) represent the estimated model parameters at time k, and y(k) be the frequency error observation. Let K(k) be the temperature or crystal oscillator time observation at time k-1, K(k) be the gain vector, P(k) be the covariance matrix, and λ∈(0,1) be the forgetting factor.

[0069] For the aging frequency characteristic model:

[0070] y(k)=f t (k),

[0071] For the temperature-frequency characteristic model:

[0072] y(k)=f T (k),

[0073] When the 1PPS signal from the GNSS receiver is lost, the crystal oscillator remains in a hold state. Combining the temperature measurement value and the crystal oscillator's working time, the frequency error is calculated by fitting the aging model (2) and the temperature model (3) obtained by the recursive least squares method with forgetting factor. The sum of these equations is used as the crystal oscillator offset compensation amount, so that the output frequency of the crystal oscillator can still maintain a certain accuracy within a certain period of time.

[0074] The specific process is as follows: Figure 2 As shown, the entire crystal oscillator discipline and hold system is initialized upon power-up. First, the STM32 microcontroller is initialized, mainly including the clock, serial port, and I / O port working modes. Then, the DAC1220 is reset and its registers are configured to work in 20-bit self-calibration mode. After initialization, the crystal oscillator output frequency needs to be stabilized. At this time, the output power of the crystal oscillator is about 1.5W. The STM32 receives the phase difference data from serial port 1 at 1s intervals and performs Kalman filtering on it. At the same time, the phase difference data needs to be sent to IIR1 and IIR2 digital filters. IIR1 is used to separate the high-frequency change part of the phase difference data caused by temperature change, and the bandwidth is designed to be 3mHz. IIR2 is used to separate the low-frequency change part of the phase difference data caused by aging, and the bandwidth is designed to be 0.03mHz. Temperature model training and aging model training are performed on the data after filtering by IIR1 and IIR2 respectively. When there is a GNSS signal, the phase difference after Kalman filtering is converted into frequency deviation by equation (1), and then converted into voltage control word input DA to convert into crystal oscillator control voltage. Simultaneously, a 100-point moving average value is calculated for the frequency deviation. When the entire training model is not yet stable but the GNSS signal fails, this value is used as the final crystal oscillator frequency compensation value.

[0075] Once training is complete, if the GNSS signal is not lost, training continues; if the GNSS signal is lost, the system enters hold mode. Based on the model obtained from training, the system predicts the crystal oscillator frequency drift trend, calculates the crystal oscillator frequency deviation compensation amount, converts it into control voltage, and adjusts the crystal oscillator output frequency in real time.

[0076] Example

[0077] A Beidou positioning and timing terminal with timing function has 1PPS output with adjustable rising and falling edges, adjustable pulse width, and an accuracy better than 50ns (1σ).

[0078] according to Figure 3Connect the 1PPS accuracy testing equipment. The atomic clock provides a 10MHz frequency standard signal to the navigation signal simulator, which simulates satellite signals. Set the output signal power level of the satellite signal simulator to -125dBm. Connect the simulated satellite signal to the positioning and timing terminal under test via an RF cable. Set the observation altitude cutoff angle of the positioning and timing terminal to 10° to ensure that the number of observable effective satellites is greater than 8. Simulate that the positioning and timing terminal is stationary at a known point.

[0079] The navigation signal simulator and the positioning and timing terminal simultaneously output 1PPS to the time interval counter, obtaining no less than 1000 time intervals. The difference in the rising edge of the 1PPS output by the navigation signal simulator and the positioning and timing terminal is counted, sorted from smallest to largest, and the M×66.7% value is taken as the 1PPS accuracy test result, where M is the total number of time intervals.

[0080] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0081] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0082] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0083] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0084] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit its scope of protection. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that after reading the present invention, they can still make various changes, modifications or equivalent substitutions to the specific implementation of the invention, but these changes, modifications or equivalent substitutions are all within the scope of protection of the pending claims of the invention.

Claims

1. A GNSS-based high-stability crystal oscillator discipline and hold method, comprising a GNSS-based high-stability crystal oscillator discipline and hold system, including a GNSS receiver board and an OCXO crystal oscillator FPGA. The second pulse signal output terminals of the GNSS receiver board and the FPGA are connected to a phase difference measurement module. The output terminal of the phase difference measurement module is connected to a processor. The output terminal of the processor is connected to a D / A conversion module. The output terminal of the D / A conversion module is connected to the OCXO crystal oscillator through a signal conditioning circuit. The second pulse signal of the OCXO crystal oscillator is output after frequency division by the FPGA. A temperature sensor is connected to the OCXO crystal oscillator. The processor is equipped with two IIR filters, which are used to filter out aging and temperature-related factors in the phase difference, respectively. Its features are, It includes two operating modes: locked and tamed mode and unlocked and held mode; When the GNSS receiver board outputs a second pulse signal normally, it is in locked discipline mode. At this time, the phase difference measurement module is used to measure the phase difference between the second pulse signal of the GNSS receiver board and the second pulse signal of the OCXO crystal oscillator. The frequency deviation of the OCXO crystal oscillator is calculated by the phase difference and converted into a digital quantity of the crystal oscillator control voltage. The crystal oscillator control voltage is then obtained through the D / A conversion module to calibrate the output frequency of the OCXO crystal oscillator in real time. At the same time, the working time of the OCXO crystal oscillator and the temperature sensor value are recorded to model the temperature frequency characteristics and aging frequency characteristics of the OCXO crystal oscillator. When the GNSS receiver board fails to output the second pulse signal normally, it switches to the unlock hold mode. If the modeling is completed at this time, the model established by the lock discipline mode is used to predict the OCXO crystal frequency deviation and compensate the OCXO crystal output frequency to achieve automatic holding of the OCXO crystal frequency. If the modeling is not completed at this time, the moving average of the most recent frequency deviations of the output is calculated to compensate for the OCXO crystal oscillator output frequency, so as to achieve automatic maintenance of the OCXO crystal oscillator frequency. The phase difference measurement module measures the phase difference between the second pulse signal of the GNSS receiver board and the second pulse signal of the OCXO crystal oscillator, and calculates the frequency deviation of the OCXO crystal oscillator based on the phase difference. Specifically: The phase difference measurement module measures the phase difference between the second pulse signal output from the GNSS receiver board and the second pulse signal from the OCXO crystal oscillator obtained by frequency division via the FPGA. The phase difference measurement value is then filtered in the processor, and the OCXO crystal oscillator frequency deviation is calculated using the filtered phase difference. in, For OCXO crystal oscillator frequency deviation, This refers to the nominal frequency of the OCXO crystal oscillator. The filtered phase difference This refers to the sampling interval of the phase difference measurement module; The process of converting the frequency deviation of the OCXO crystal oscillator into a digital value of the crystal oscillator control voltage, and then obtaining the crystal oscillator control voltage through a D / A conversion module to calibrate the OCXO crystal oscillator output frequency in real time, specifically involves: Based on the frequency deviation of the OCXO crystal, the voltage-controlled sensitivity coefficient of the OCXO crystal is used. The digital value of the crystal oscillator control voltage is calculated and then converted into the crystal oscillator control voltage via a D / A converter module. This enables real-time calibration of the OCXO crystal oscillator output frequency.

2. The GNSS-based high-stability crystal oscillator discipline and maintenance method according to claim 1, characterized in that, The recording of OCXO crystal oscillator operating time and temperature sensor values, and the modeling of the temperature-frequency characteristics and aging-frequency characteristics of the OCXO crystal oscillator, specifically involves: Establish mathematical models for the relationship between crystal oscillator operating time and frequency deviation, as well as mathematical models for the relationship between crystal oscillator temperature and frequency deviation; The mathematical model between the crystal oscillator's operating time and frequency deviation is as follows: Where t is the crystal oscillator operating time. This is due to the crystal oscillator frequency deviation caused by aging. This includes the aging effect on random deviations in crystal oscillator frequency and measurement errors. This represents the initial frequency offset of the aging portion. The aging coefficient; The mathematical model between the crystal oscillator temperature and frequency error is as follows: Where T is the crystal oscillator temperature. This refers to the temperature-induced deviation in crystal oscillator frequency. This section covers the temperature-dependent effects of random deviations in crystal oscillator frequency and measurement errors. This represents the initial frequency offset for the temperature component. Temperature coefficient; The phase difference data is separated by two IIR filters configured in the processor, which separate the aging-related components of the random deviation and measurement error of the crystal oscillator frequency from the temperature-related components. The frequency deviation is then calculated. and The parameters were obtained by fitting the frequency deviation with temperature and time information, respectively. a 0 and a 1 and parameters b 0 and b 1. Thus, a temperature-frequency characteristic model and an aging-frequency characteristic model are established.

3. The GNSS-based high-stability crystal oscillator discipline and maintenance method according to claim 2, characterized in that, The parameters are obtained by fitting the frequency deviation with temperature and time information, respectively. a 0 and a 1 and parameters b 0 and b 1. Specifically: The parameters of the temperature-frequency characteristic model were fitted using a recursive least squares method with a forgetting factor. a 0 and a 1. Parameters of the aging frequency characteristic model b 0 and b 1. The recursive least squares formula with a forgetting factor is as follows: in, The time indicates the first Next iteration, express Time-based model parameter estimates For frequency error observation, for Time-temperature or crystal oscillator time observation, For the gain vector, Let covariance matrix be the variance matrix. Forgetting factor; For the aging frequency characteristic model: ， ， For the temperature-frequency characteristic model: ， ， The parameters of the temperature-frequency characteristic model are fitted using the above formula. a 0 and a 1. Parameters of the aging frequency characteristic model b 0 and b 1.

4. The method for controlling and maintaining a high-stability crystal oscillator based on GNSS according to claim 1, characterized in that, The processor used is an STM32 processor.

5. The GNSS-based high-stability crystal oscillator discipline and maintenance method according to claim 1, characterized in that, The temperature sensor used is a DS18B20.

6. The GNSS-based high-stability crystal oscillator discipline and maintenance method according to claim 1, characterized in that, The D / A conversion module uses DAC1220.

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