A scale factor calibration method for a large-scale fiber-optic gyroscope used for UT1 measurement

Abstract

The application discloses a scale factor calibration method of a large-scale fiber-optic gyroscope for UT1 measurement; through establishment of a geostationary observation equation, gyro data is denoised, temperature compensated, directional error corrected and polar motion corrected to obtain a third angular velocity value; meanwhile, an earth rotation angular velocity variation model is constructed based on an IERS sequence to perform prediction, the predicted value is fused with the third angular velocity value, a dynamic calibration model is established, high-frequency scale factor calibration is realized and real-time correction is achieved; the application overcomes the defect that a large-scale fiber-optic gyroscope cannot be calibrated by a rotating platform, and improves measurement precision.

Description

Technical Field

[0001] This invention relates to the field of world time measurement methods, and more particularly to a scaling factor calibration method for a large fiber optic gyroscope used for UT1 measurement. Background Technology

[0002] Universal Time (UT1) is a time measurement system that uses the Earth's rotation as a reference. UT1 is one of the Earth Orientation Parameters (EOP), and its value reflects the change in the Earth's rotational angular velocity. This parameter is one of the essential parameters for converting coordinates between the celestial sphere and the Earth's reference frame. UT1 plays an irreplaceable role in science and technology, economic development, national defense, and aerospace.

[0003] UT1 exhibits time-varying characteristics, and continuous UT1 measurements can be achieved using fiber optic gyroscopes. This is advantageous for measuring the high-frequency components of Earth's rotation. The raw measurement data from the fiber optic gyroscope requires noise suppression and various error corrections before UT1 can be calculated. However, due to instrument drift, the measurement data exhibits a slow, trend-like change. After long-term integration and accumulation, low-frequency drift noise gradually accumulates in the calculated UT1 parameters, causing the final UT1 result to deviate from the true value.

[0004] Traditional inertial navigation gyroscope scaling factor calibration is achieved using a precision turntable. This high-precision turntable provides a series of accurate angular velocities covering the gyroscope's normal operating speed range. The output values ​​of the gyroscope at each angular velocity are recorded, and an input-output model of the gyroscope's angular velocity is established and solved to obtain the precise scaling factor. Large fiber optic gyroscopes, due to their large size, cannot be calibrated using a precision turntable. Currently, large fiber optic gyroscopes used for UT1 measurements are calibrated using the following method: Determining the initial calibration value: using measured data from the gyroscope over a period of time. Reference values ​​for Earth's rotational angular velocity published by IERS (International Earth Rotation Service). The initial calibration value is calculated. Calibration value update: The UT1 obtained from the measured data is compared with the UT1 reference value published by IERS. If the deviation exceeds a preset threshold, the scaling factor of the fiber optic gyroscope needs to be recalibrated. The threshold setting is determined by the measurement accuracy of the fiber optic gyroscope used in the experiment.

[0005] Traditional inertial gyroscopes calibrate their scaling factors using a precision turntable. However, large optical gyroscopes, due to their bulk, cannot be calibrated using a turntable, and the theoretical scaling factor values ​​calculated based on the gyroscope's geometric parameters cannot meet the requirements for high-precision measurement of the Earth's rotation angular velocity. Current scaling factor calibration methods for large fiber optic gyroscopes compare the Cosmic Time (UT1) calculated from measured data with the UT1 reference value published by IERS. If the deviation exceeds a preset threshold, the gyroscope's scaling factor needs to be recalibrated. This method can only output one scaling factor calibration value per day, resulting in a low calibration frequency. Summary of the Invention

[0006] This invention provides a scaling factor calibration method for large fiber optic gyroscopes used for UT1 measurements, which solves the problems of existing technologies where large fiber optic gyroscopes cannot be calibrated on a turntable and have low scaling factor calibration frequencies, and realizes dynamic calibration and high-precision UT1 measurements at any time.

[0007] This invention provides a scaling factor calibration method for a large fiber optic gyroscope used for UT1 measurements, comprising: An observation equation based on the Sagnac effect for a fiber optic gyroscope is established. The observation equation is then transformed from the platform Cartesian coordinate system to the ground-fixed coordinate system to obtain the ground-fixed fiber optic gyroscope measurement equation. The original fiber optic gyroscope data, the original level data, and the temperature data of the test environment are also acquired. The instantaneous rotational angular velocity of the Earth is calculated using the original fiber optic gyroscope data, and the instantaneous rotational angular velocity of the Earth is then denoised to obtain the first angular velocity value. The temperature error of the first angular velocity value is compensated using the temperature data of the test environment to obtain the second angular velocity value; Based on the Earth-fixed system fiber optic gyroscope measurement equation, the second angular velocity value is corrected for orientation error by combining the original level data with the tidal model, and the instantaneous polar displacement error of the Earth's rotation axis is corrected to obtain the third angular velocity value. A model of Earth's rotation angular velocity variation is constructed, and the Earth's rotation angular velocity at future times is predicted using the model to obtain the predicted value of Earth's rotation angular velocity. The predicted Earth rotation angular velocity is fused with the third angular velocity value to establish a scaling factor dynamic calibration model. The third angular velocity value is corrected by scaling factor using the scaling factor dynamic calibration model to obtain the corrected angular velocity value.

[0008] One or more technical solutions provided in this invention have at least the following technical effects or advantages: This invention employs an observation equation based on the Sagnac effect for a fiber optic gyroscope, transforming the equation from the platform's Cartesian coordinate system to the Earth-fixed coordinate system (ERC), thus obtaining the ERC measurement equation. It also acquires raw fiber optic gyroscope data, raw level data, and ambient temperature data. This step establishes the theoretical foundation for subsequent error correction and scaling factor correction. The ERC measurement equation directly incorporates parameters such as station latitude and longitude, polar motion, and level tilt, providing a complete mathematical model for high-precision measurement. Simultaneous acquisition of multi-source data ensures the consistency and reliability of subsequent processing. The instantaneous Earth rotation angular velocity is calculated using the raw fiber optic gyroscope data and then denoised to obtain the first angular velocity value. This step utilizes a hybrid denoising method combining Butterworth filtering, empirical mode decomposition, and singular spectrum analysis, effectively separating the signal from high-frequency noise, significantly improving the signal-to-noise ratio, and providing a clean angular velocity signal for subsequent error compensation. Temperature error compensation is applied to the first angular velocity value using temperature data from the test environment to obtain the second angular velocity value. This step employs an extreme learning machine (ELM) model to establish a temperature error compensation model, which has advantages such as fewer optimization parameters, fast training speed, and the ability to describe the temperature nonlinearity of the fiber optic gyroscope. This significantly reduces measurement deviations caused by environmental temperature fluctuations and improves the stability of angular velocity measurements. Based on the Earth-Fixed System (EFS) fiber optic gyroscope measurement equation, the second angular velocity value is corrected for orientation errors using raw level data combined with a tidal model, and the instantaneous polar motion error of the Earth's rotation axis is corrected to obtain the third angular velocity value. This step combines high-precision electronic level data with the vertical line changes simulated by the tidal model to accurately compensate for north-south tilt errors. Simultaneously, IERS polar motion data is converted into angular velocity errors through the EFS observation equation and subtracted, effectively eliminating the influence of the Earth's instantaneous rotation axis changes on the measurement, making the angular velocity value closer to the actual Earth rotation signal. A model for the variation of Earth's rotation angular velocity is constructed to predict the Earth's rotation angular velocity at future times, yielding a predicted value. This step enables high-precision prediction of Earth's rotation angular velocity, particularly by preserving high-frequency variations within a single day, fully leveraging the frequency response advantages of fiber optic gyroscopes. The predicted Earth rotation angular velocity is then fused with the third angular velocity value to establish a scaling factor dynamic calibration model. This step compares the predicted and measured angular velocities hour by hour to calculate the true discrete value of the scaling factor, and uses interpolation methods to construct a dynamic calibration model in the continuous time domain. The model parameters are automatically refreshed based on the IERS update sequence. Compared to existing technologies that output only one scaling factor per day, this model theoretically obtains the scaling factor calibration value at any time, significantly increasing the calibration frequency and enabling real-time tracking of fiber optic gyroscope drift changes. The scaling factor is then used to correct the third angular velocity value using the scaling factor dynamic calibration model, yielding the corrected angular velocity value.This step directly multiplies the true scaling factor output by the dynamic calibration model with the third angular velocity value, completing real-time compensation for scaling factor errors and outputting a high-precision instantaneous Earth rotation angular velocity. This provides a reliable data foundation for the calculation of Universal Time UT1 and effectively eliminates the long-standing accuracy bottleneck of large fiber optic gyroscopes due to the inability to use a turntable for calibration. Attached Figure Description

[0009] Figure 1 A flowchart illustrating the overall steps of a scaling factor calibration method for a large fiber optic gyroscope used for UT1 measurement, as provided in an embodiment of the present invention. Figure 2 A schematic diagram of the hybrid noise reduction and temperature error compensation process provided in an embodiment of the present invention; Figure 3 A flowchart illustrating the method for establishing a scaling factor dynamic calibration model according to an embodiment of the present invention; Figure 4 This is a schematic diagram of the scaling factor correction process for fiber optic gyroscope data provided in an embodiment of the present invention. Detailed Implementation

[0010] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0011] This invention provides a scaling factor calibration method for a large fiber optic gyroscope used for UT1 measurements, see [link to relevant documentation]. Figure 1 The process includes the following steps S101 to S107.

[0012] S101. Establish the observation equation of the fiber optic gyroscope based on the Sagnac effect, transform the observation equation from the platform rectangular coordinate system to the ground-fixed coordinate system, obtain the ground-fixed fiber optic gyroscope measurement equation, and acquire the original fiber optic gyroscope data, the original level data, and the temperature data of the test environment.

[0013] Here, the observation equation is expressed as: ; in, Represents the normal vector of the fiber optic ring plane; This represents the amount of equivalent phase difference change caused by the inherent noise of the fiber optic gyroscope. Indicates the theoretical scaling factor; This indicates the scaling factor deviation of the fiber optic gyroscope; This represents the vector representing the Earth's average angular velocity of rotation. This represents the change in the Earth's angular velocity of rotation; This indicates the phase difference.

[0014] The measurement equation for a ground-fixed fiber optic gyroscope is expressed as follows: ; in, , This is the Earth's average angular velocity of rotation. Indicates the actual scaling factor; and Reflecting the instantaneous polar shift of the Earth's axis of rotation; Indicates the latitude of the location where the fiber optic gyroscope is placed; Indicates the longitude of the location where the fiber optic gyroscope is placed; This represents the change in the Earth's instantaneous angular rate of rotation; Indicates the change in latitude of the station; This represents the amount of equivalent phase difference change caused by the inherent noise of the fiber optic gyroscope. This indicates the phase difference.

[0015] For example, the raw phase difference data output by a large fiber optic gyroscope is collected as the raw fiber optic gyroscope data; the real-time tilt reading of a high-precision electronic level installed near the gyroscope is collected as the raw level data; multiple temperature sensors are deployed near the gyroscope casing and fiber optic ring to continuously record the ambient temperature, with the sampling frequency synchronized with the gyroscope data. Since the fiber optic gyroscope used in the experiment is installed in a mid-latitude region, the east-west tilt change has a much smaller impact on the measurement of the Earth's rotation angular velocity than the north-south tilt change, therefore the east-west tilt change is ignored.

[0016] S102, the instantaneous rotational angular velocity of the Earth is calculated using the original fiber optic gyroscope data, and the instantaneous rotational angular velocity of the Earth is denoised to obtain the first angular velocity value; Specifically, in step S102, the instantaneous rotational angular velocity value of the Earth is calculated using the original fiber optic gyroscope data, and the instantaneous rotational angular velocity value of the Earth is denoised to obtain the first angular velocity value, including the following steps S1021 to S1025.

[0017] S1021, perform power spectral density analysis on the instantaneous rotational angular velocity of the Earth, and use a Butterworth filter to remove high-frequency noise to obtain the filtered signal; S1022, Empirical mode decomposition is performed on the filtered signal to obtain multiple intrinsic mode function components and trend terms; S1023, using the cumulative standardized mean method, multiple intrinsic mode function components are divided into mixed terms and information terms, resulting in a set of mixed terms and a set of information terms; S1024, Singular spectrum analysis is performed on each mixture term in the mixture term set to obtain multiple singular spectrum components. The main secondary components are selected from the multiple singular spectrum components by Hurst exponent. The selected main secondary components are summed to obtain the reconstructed mixture term signal corresponding to each mixture term. S1025, the reconstructed mixed term signal is superimposed with the information term set and the trend term to obtain the first angular velocity value.

[0018] For example, see Figure 2 The hybrid denoising method and temperature error compensation method are as follows: Power spectral density analysis was performed on the instantaneous rotational angular velocity of the Earth. Based on the analysis results, a Butterworth filter was used to preliminarily process the data to remove high-frequency noise and obtain the filtered signal. The filtered signal was then divided into multiple intrinsic mode function components (IMFs) and trend terms through empirical mode decomposition. The IMF is divided into two categories using the cumulative standardized mean method: one category is a mixture of signal and noise, and the other category is information, thus obtaining a set of mixture items and a set of information items.

[0019] Singular spectrum analysis was performed on the mixed terms in the mixed term set, and the main sub-components were screened out by the Hurst exponent for reconstruction. The information term and trend term directly participated in the signal reconstruction. The relationship between the output data of the fiber optic gyroscope and the temperature was analyzed, and the extreme learning machine model was used to compensate for the error caused by the temperature.

[0020] S103, use the temperature data of the test environment to compensate for the temperature error of the first angular velocity value to obtain the second angular velocity value.

[0021] Specifically, in step S103, the temperature error of the first angular velocity value is compensated using the temperature data of the test environment to obtain the second angular velocity value, including the following steps S1031 and S1032.

[0022] S1031, Analyze the relationship between the output data of the fiber optic gyroscope and the temperature data, and establish a temperature error compensation model using the extreme learning machine model; S1032, input the first angular velocity value and the temperature data of the test environment into the temperature error compensation model, and output the second angular velocity value.

[0023] For example, the output data of the fiber optic gyroscope at different ambient temperatures is collected. The first angular velocity value and the corresponding temperature data are used as inputs, and the high-precision reference angular velocity value is used as output to train the extreme learning machine model. After training, the temperature data of the first angular velocity value of 25.6℃ obtained in real time is input into the model, and the model outputs the compensated second angular velocity value to complete the temperature error compensation.

[0024] S104. Based on the Earth-fixed system fiber optic gyroscope measurement equation, the second angular velocity value is corrected for orientation error by combining the original level instrument data with the tidal model, and the instantaneous polar displacement error of the Earth's rotation axis is corrected to obtain the third angular velocity value.

[0025] Specifically, in step S104, the orientation error is corrected by combining the original level data with the tidal model, and the instantaneous polar displacement error of the Earth's rotation axis is corrected to obtain the third angular velocity value, including the following steps S1041 to S1045.

[0026] S1041, using the original level data, the tilt error of the second angular velocity value in the north-south direction is corrected to obtain the tilt-corrected data; S1042, using a tidal model to simulate the local plumb line change at the station location, and extracting the north-south component of the local plumb line change. S1043, the north-south component is used to compensate for the tilt-corrected data to obtain the orientation error-corrected data; S1044: Obtain polar motion data of the celestial intermediate pole published by IERS, convert the polar motion data of the celestial intermediate pole into the polar motion change of the Earth's instantaneous rotation axis, and convert the polar motion change into angular velocity error according to the measurement equation of the Earth-fixed fiber optic gyroscope. S1045, subtract the angular velocity error from the data after orientation error correction to obtain the third angular velocity value.

[0027] For example, the raw data from the fiber optic gyroscope is converted into a measurement of the Earth's rotation angular velocity, and the data is preprocessed. The preprocessing mainly includes denoising using a hybrid denoising method and temperature error compensation using an extreme learning machine model in conjunction with temperature data.

[0028] Orientation error correction of fiber optic gyroscopes: The measurement data of a level includes changes in the plumb line and geometric deformation of the ground surface, while the fiber optic gyroscope is only sensitive to geometric deformation of the ground surface during the measurement process.

[0029] The tilt error in the north-south direction was corrected using the data from the level instrument to obtain the tilt-corrected data. The tidal model is used to simulate the local plumb line changes at the station location, and the north-south component of the local plumb line changes is extracted. The north-south component is compensated for the tilt-corrected data to obtain the orientation error-corrected data.

[0030] The north-south component of the local plumb line at the station location is expressed as: ; in, Indicates the tidal potential. It is a spherical harmonic function , , Let represent the order and degree of the spherical harmonic function, respectively; The longitude of the station. The covariant latitude of the station location. It is the radius of the Earth's surface. It is the average gravity value at the equator. The Love number represents the spherically symmetric approximation of a rotating inelastic Earth model. This represents the Love number under the spherically symmetric approximation of the microelliptic inelastic Earth model.

[0031] Based on the measurement equation of the Earth-fixed system fiber optic gyroscope, the level measurement data and the local plumb line change data simulated by the tidal model are converted into the corresponding Earth rotation angular velocity, and then error correction is performed.

[0032] Earth's instantaneous rotation axis polar shift error correction: Changes in the polar shift of the Earth's instantaneous rotation axis can cause errors in the measurements of fiber optic gyroscopes, and these errors need to be corrected.

[0033] IERS provides the polar shift of the celestial midpole, which can be converted into the polar shift of the Earth's instantaneous axis of rotation: ; in, This is represented by the six fundamental astronomical parameters in Tables 4.1 and 4.2 of the IERS 2010 resolution. Composed of linear combinations, Indicates the mean aperimeter angle of the Moon; Indicates the level aperitoneal angle of the sun; This represents the difference between the lunar mean ecliptic longitude and the mean ecliptic longitude of the ascending node of the lunar orbit; This represents the average angular moment of the Moon and the Sun; Indicates the ecliptic longitude of the ascending node of the moon's orbit; for ,in, Using Greenwich Mean Sidereal Time; coefficients A, B, C, and D can be calculated by using the coefficients in columns 10-13 of Tabs 8.2a and Tabs 8.2b of the IERS 2010 resolution, and combining them with the conversion relationship between the Celestial Intermediate Pole (CIP) and the Earth's instantaneous rotation axis. The conversion relationship between CIP and the Earth's instantaneous rotation axis is as follows: ; in, , This is the Earth's average angular velocity of rotation. Polar shift representing CIP express The first derivative with respect to time, It can be represented as: ; in, This represents the polar displacement of CIP along the x-axis. Represents the polar displacement of CIP in the y-axis direction; coefficient b, c, and d correspond to columns 10 to 13 of Tabs 8.2a and Tabs 8.2b in the IERS 2010 resolution, respectively.

[0034] After calculating the polar motion error of the Earth's instantaneous rotation axis, the error is converted into the corresponding Earth's rotation angular velocity according to the observation equation, and then the error is corrected to obtain the third angular velocity value.

[0035] S105, Construct a model of the Earth's rotation angular velocity variation, use the model of the Earth's rotation angular velocity variation to predict the Earth's rotation angular velocity at future times, and obtain the predicted value of the Earth's rotation angular velocity. Specifically, in step S105, a model of the Earth's rotational angular velocity variation is constructed, including the following steps S1051 to S1054.

[0036] S1051, obtained the Earth rotation day length variation data from the 14C04 sequence published by IERS, and removed the solid tide effect from the day length variation data to obtain the first day length data; S1052, various historical data lengths are used to make trial forecasts of the change in day length, the average absolute error between the forecast value and the actual value corresponding to each historical data length is calculated, and the historical data length with the smallest average absolute error is selected as the optimal length. S1053, the first day's length data is truncated according to the optimal length to obtain the basic sequence data; S1054 uses a combination of least squares and autoregression to establish a prediction model for the basic sequence data, thus obtaining a model of the Earth's rotational angular velocity variation.

[0037] Specifically, in step S105, the predicted value of the Earth's rotation angular velocity is obtained using the Earth's rotation angular velocity variation model, including: (1) Based on the Earth's rotation angular velocity variation model, the basic sequence data is predicted, and the predicted values ​​of the day length variation at multiple future times are output, which are denoted as the first day length value. (2) Interpolate and encrypt the first day length value, and add the daily and semi-daily changes caused by ocean tides to obtain the second day length value; (3) Convert the second day length value into the predicted value of Earth's rotation angular velocity according to the conversion formula.

[0038] For example, solid tides are removed from the diurnal variation data in the IERS 14C04 sequence to obtain the first diurnal data; The main period of the first day length data is determined using FFT (Fast Fourier Transform). The prediction accuracy of different sequence lengths is compared. The mean absolute error (MAE) between the predicted and actual values ​​is used as the evaluation index, and the sequence with the smallest MAE is selected as the optimal length.

[0039] The prediction is made by combining least squares and autoregression, i.e., LS+AR. The predicted value of LS+AR (unrestored solid tide) is interpolated, and the first day length data is encrypted to obtain the second day length value, i.e., the encrypted angular velocity prediction value sequence. Here, the interpolation at a preset time interval of 1 hour is taken as an example. Then, solid tides are restored; since measuring high-frequency variations in period over a day is an advantage of fiber optic gyroscopes, the encrypted angular velocity prediction sequence is supplemented with the influence of ocean tides, i.e., the periodic variations of diurnal and semi-diurnal terms are added.

[0040] The predicted Earth's rotation angular velocity for the forecast period can be obtained by converting the obtained second-day length value to an OMEGA value using the following formula. The specific formula is: ; in, It is the Earth's average angular velocity of rotation, measured in mas / ms. It is the conversion factor. ; This indicates the length of the second day.

[0041] S106, integrates the predicted value of Earth's rotation angular velocity with the value of the third angular velocity to establish a scaling factor dynamic calibration model; Specifically, in step S106, the predicted value of Earth's rotation angular velocity is fused with the value of the third angular velocity to establish a scaling factor dynamic calibration model, including the following steps S1031 to S1063.

[0042] S1061, Obtain the predicted value of Earth's rotation angular velocity as a sequence of angular velocity forecast values. Each forecast value in the angular velocity forecast value sequence corresponds to a discrete time point. S1062, the true scaling factor for each discrete time point is calculated by combining the predicted angular velocity value at each discrete time point with the triangular velocity value at the same time. S1063 utilizes the true scaling factor at discrete time points and employs an interpolation method to construct a dynamic scaling factor calibration model.

[0043] Here, a dynamic calibration model for the scaling factor is constructed using the real scaling factor at discrete time points and an interpolation method, including the following steps S1063-1 to S1063-3.

[0044] S1063-1 uses the true scaling factor at discrete time points as discrete sample points, performs interpolation on the discrete sample points to generate a scaling factor function in the continuous time domain, and uses the scaling factor function as the initial dynamic calibration model. S1063-2, When IERS releases an updated 14C04 sequence, the updated 14C04 sequence is used to obtain an updated predicted value of Earth's rotation angular velocity. S1063-3: Based on the updated predicted Earth rotation angular velocity, the updated true scaling factor is obtained, the discrete sample points are updated, and interpolation is performed again to update the scaling factor dynamic calibration model.

[0045] For example, see Figure 3 In the technical solution provided in the embodiments, the method for establishing the scaling factor dynamic calibration model is as follows: Based on the true scaling factor The relationship between the actual scaling factor and the theoretical scaling factor can be used to obtain the true scaling factor. The specific formula for this relationship is as follows: ; in, Indicates the theoretical scaling factor; This represents the third angular velocity value, which is the value after the original output data of the gyroscope is converted into angular velocity through a theoretical scaling factor, and then after noise reduction, removal of temperature effects, and error correction. This represents the predicted value of the Earth's rotational angular velocity, which is the forecast value obtained through the preceding steps.

[0046] After conversion using relational formulas, a true scaling factor is obtained that predicts every 1 hour within the measurement time period of the fiber optic gyroscope. value.

[0047] It should be noted that the predicted values ​​of LS+AR were interpolated at 1-hour intervals, so a scaling factor calibration value can be obtained every hour. If the interpolation is more frequent, theoretically a scaling factor calibration value at any time can be obtained.

[0048] Utilize The value corrects for the angular velocity of the fiber optic gyroscope. After the IERS 14C04 sequence is updated, the above steps are repeated using the new data to complete the update of the scaling factor dynamic calibration model.

[0049] S107, the third angular velocity value is corrected by scaling factor using the scaling factor dynamic calibration model to obtain the corrected angular velocity value.

[0050] Specifically, in S107, the third angular velocity value is corrected by scaling factor using a scaling factor dynamic calibration model to obtain the corrected angular velocity value, including the following steps S1071 and S1072.

[0051] S1071, using the scaling factor dynamic calibration model, calculates the true scaling factor based on the third angular velocity value; S1071, multiply the third angular velocity value by the true scaling factor to obtain the corrected angular velocity value.

[0052] For example, according to the scaling factor dynamic calibration model, for the third triangular velocity value at the current moment... The model outputs the corresponding true scaling factor. The calculation formula is: ,in, This represents the predicted angular velocity of Earth's rotation at the same moment. and Multiply them to obtain the corrected angular velocity value.

[0053] For example, at a certain moment Model output The corrected angular velocity value is: .

[0054] In this invention, a hybrid denoising method combining low-pass filter, EMD (Empirical Mode Decomposition), and SSA (Singular Spectrum Analysis) is used to denoise the instantaneous angular velocity data of Earth's rotation. This method performs intrinsic separation of the signal and high-frequency noise, resulting in more targeted denoising and a higher signal-to-noise ratio. Furthermore, it compensates for the temperature error of the fiber optic gyroscope. This method has the advantages of requiring fewer optimization parameters and having a fast training speed, and it can effectively describe the nonlinear characteristics of the temperature properties of the fiber optic gyroscope.

[0055] In this invention, the established scaling factor dynamic calibration model can theoretically obtain the scaling factor calibration value at any time, which can eliminate the influence of drift caused by fiber optic gyroscopes during long-term observation and give full play to the advantage of high observation frequency of fiber optic gyroscopes.

[0056] The various embodiments described in this specification are presented in a progressive manner. Similar or identical parts between embodiments can be referred to interchangeably. Each embodiment focuses on its differences from other embodiments. All or part of this invention can be used in numerous general-purpose or special-purpose computer system environments or configurations. Examples include: personal computers, server computers, handheld or portable devices, tablet devices, mobile communication terminals, multiprocessor systems, microprocessor-based systems, programmable electronic devices, network PCs, minicomputers, mainframe computers, and distributed computing environments including any of the above systems or devices, etc.

[0057] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the present invention.

Claims

1. A method for scaling factor calibration of a large fiber optic gyroscope used for UT1 measurements, characterized in that, include: An observation equation based on the Sagnac effect for a fiber optic gyroscope is established. The observation equation is then transformed from the platform Cartesian coordinate system to the ground-fixed coordinate system to obtain the ground-fixed fiber optic gyroscope measurement equation. The original fiber optic gyroscope data, the original level data, and the temperature data of the test environment are also acquired. The instantaneous rotational angular velocity of the Earth is calculated using the original fiber optic gyroscope data, and the instantaneous rotational angular velocity of the Earth is then denoised to obtain the first angular velocity value. The temperature error of the first angular velocity value is compensated using the temperature data of the test environment to obtain the second angular velocity value; Based on the Earth-fixed system fiber optic gyroscope measurement equation, the second angular velocity value is corrected for orientation error by combining the original level data with the tidal model, and the instantaneous polar displacement error of the Earth's rotation axis is corrected to obtain the third angular velocity value. A model of Earth's rotation angular velocity variation is constructed, and the Earth's rotation angular velocity at future times is predicted using the model to obtain the predicted value of Earth's rotation angular velocity. The predicted Earth rotation angular velocity is fused with the third angular velocity value to establish a scaling factor dynamic calibration model. This process includes: obtaining the predicted Earth rotation angular velocity as a sequence of angular velocity forecasts, where each forecast value in the sequence corresponds to a discrete time point; calculating the true scaling factor for each discrete time point by combining the forecasted angular velocity value with the third angular velocity value at the same time; and constructing a scaling factor dynamic calibration model using an interpolation method based on the true scaling factor for each discrete time point. The method describes constructing a scaling factor dynamic calibration model using the true scaling factors at each discrete time point and an interpolation method. This includes: using the true scaling factors at discrete time points as discrete sample points; performing interpolation on the discrete sample points to generate a scaling factor function in the continuous time domain; using the scaling factor function as the initial dynamic calibration model; when IERS releases an updated 14C04 sequence, using the updated 14C04 sequence to obtain an updated predicted value of Earth's rotation angular velocity; obtaining an updated true scaling factor based on the updated predicted value of Earth's rotation angular velocity; updating the discrete sample points; and re-performing the interpolation operation to update the scaling factor dynamic calibration model. The third angular velocity value is corrected by scaling factor using the scaling factor dynamic calibration model to obtain the corrected angular velocity value.

2. The scaling factor calibration method for a large fiber optic gyroscope used for UT1 measurement according to claim 1, characterized in that, The process of calculating the Earth's instantaneous rotation angular velocity using the original fiber optic gyroscope data, and then denoising the Earth's instantaneous rotation angular velocity to obtain a first angular velocity value, includes: Power spectral density analysis was performed on the instantaneous rotational angular velocity value of the Earth, and high-frequency noise was removed using a Butterworth filter to obtain the filtered signal; Empirical mode decomposition is performed on the filtered signal to obtain multiple intrinsic mode function components and trend terms; The multiple intrinsic mode function components are divided into mixture terms and information terms using the cumulative standardized mean method, resulting in a mixture term set and an information term set. Singular spectrum analysis is performed on each mixture in the mixture set to obtain multiple singular spectrum components. The Hurst exponent is used to select the main secondary components from the multiple singular spectrum components. The selected main secondary components are summed to obtain the reconstructed mixture signal corresponding to each mixture. The reconstructed hybrid signal is superimposed with the information item set and the trend item to obtain the first angular velocity value.

3. The scaling factor calibration method for a large fiber optic gyroscope used for UT1 measurement according to claim 1, characterized in that, The step of using the temperature data of the test environment to compensate for the temperature error of the first angular velocity value to obtain the second angular velocity value includes: The relationship between the output data of the fiber optic gyroscope and the temperature data was analyzed, and a temperature error compensation model was established using an extreme learning machine model. The first angular velocity value and the temperature data of the test environment are input into the temperature error compensation model, and the second angular velocity value is output.

4. The scaling factor calibration method for a large fiber optic gyroscope used for UT1 measurement according to claim 1, characterized in that, The method, based on the Earth-fixed system fiber optic gyroscope measurement equation, uses the original level data combined with the tidal model to correct the orientation error of the second angular velocity value and corrects the instantaneous polar motion error of the Earth's rotation axis, to obtain the third angular velocity value, including: The tilt error in the north-south direction is corrected using the original level data to obtain the tilt-corrected data. The local plumb line variation at the station location is simulated using a tidal model, and the north-south component of the local plumb line variation is extracted. The tilt-corrected data is compensated using the north-south component to obtain the orientation error-corrected data. Acquire the polar motion data of the celestial intermediate pole published by IERS, convert the polar motion data of the celestial intermediate pole into the polar motion change of the Earth's instantaneous rotation axis, and convert the polar motion change into angular velocity error according to the Earth-fixed fiber optic gyroscope measurement equation; The third angular velocity value is obtained by subtracting the angular velocity error from the data after the orientation error correction.

5. The scaling factor calibration method for a large fiber optic gyroscope used for UT1 measurement according to claim 1, characterized in that, The construction of the Earth's rotation angular velocity variation model includes: Data on the variation of Earth's rotation day length were obtained from the 14C04 sequence published by IERS, and the influence of solid tides in the day length variation data was removed to obtain the first day length data; Trial forecasts of day length variation were made using various historical data lengths, and the average absolute error between the forecast and the actual value was calculated for each historical data length. The historical data length with the smallest average absolute error was selected as the optimal length. The first day length data is extracted based on the optimal length to obtain the basic sequence data; A prediction model for the basic sequence data was established using a combination of least squares and autoregression methods, resulting in the Earth's rotational angular velocity variation model.

6. The scaling factor calibration method for a large fiber optic gyroscope used for UT1 measurement according to claim 5, characterized in that, The process of using the Earth's rotation angular velocity variation model to predict the Earth's rotation angular velocity at future times, and obtaining predicted values ​​of the Earth's rotation angular velocity, includes: Based on the Earth's rotation angular velocity variation model, the basic sequence data is predicted, and the predicted values ​​of the day length variation at multiple future moments are output, which are denoted as the first day length value. The first day length value is interpolated and encrypted, and the daily and semi-daily variations caused by ocean tides are added to obtain the second day length value; The second day length value is converted into the predicted Earth rotation angular velocity value according to the conversion formula.

7. The scaling factor calibration method for a large fiber optic gyroscope used for UT1 measurement according to claim 1, characterized in that, The step of using the scaling factor dynamic calibration model to perform scaling factor correction on the third angular velocity value to obtain the corrected angular velocity value includes: The true scaling factor is calculated based on the third angular velocity value using the scaling factor dynamic calibration model. The corrected angular velocity value is obtained by multiplying the third angular velocity value by the true scaling factor.

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