CN110837219B - Virtual atomic clock system for monitoring entity atomic clock and working method - Google Patents
Virtual atomic clock system for monitoring entity atomic clock and working method Download PDFInfo
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Abstract
The invention provides a virtual atomic clock system, belonging to the technical field of atomic clocks, wherein a plurality of entity atomic clocks obtain relative deviation information of each atomic clock relative to a reference TA through a comparison measurement unit to form an original data set, the original data set is analyzed to eliminate abnormal behaviors of the atomic clocks, such as random jump of phase, frequency or frequency drift, forming an atomic clock sample data set, learning the historical behavior of an atomic clock by an algorithm through an atomic clock prediction analysis unit, extrapolating the deviation of the entity atomic clock at preset time relative to a reference to obtain clock error data (TA-T1), taking the deviation of the entity atomic clock and the TA at the same moment (TA-T0), performing data conversion, eliminating an intermediate reference to obtain the relative deviation of the virtual atomic clock and the entity atomic clock (T0-T1), the performance of the atomic clock is close to the measured performance, and the performance is used as a reference to evaluate the performance of the atomic clock and monitor the abnormal behavior of the atomic clock.
Description
Technical Field
The invention belongs to the technical field of atomic clocks, and particularly relates to a virtual atomic clock system for monitoring an entity atomic clock and a working method.
Background
In 1967, the thirteenth international measurement will define the basic time unit "second" as 9,192,631,770 times of the duration of the transition electromagnetic radiation period between two hyperfine sub-energy levels of the atomic ground state of cesium 133Cs, and since this time, when human beings step into the atomic time, the time becomes the physical quantity with the highest measurement precision in nature. The atomic clock as a timing tool enables the operation of the modern information society to become efficient and orderly, and the precise time and frequency standard is indispensable in various fields of national economy. The method is widely applied to astronomical observation, geodetic survey, traffic management, grid-connected power generation and troubleshooting. Accurate time synchronization is not well separated in financial transactions such as capital borrowing, exchange rate calculation, stock trading, etc., because the time is money. It brings huge changes to many industries, such as network appointment, shared bicycle, unmanned automobile, etc. Representative of these are Global Navigation Satellite Systems (GNSS), such as the Global Positioning System (GPS) in the united states, the GLONASS (GLONASS) system in russia, and the GALILEO (GALILEO) system in europe and the Beidou (BDS) system in china. In local wars which occur in recent years, the satellite navigation positioning system provides unprecedented accurate hitting capability for conventional weapons, and plays a great role in determining the success and failure of wars. Meanwhile, the system plays an irreplaceable role in military operations such as weapon platforms, cooperative combat, emergency command and the like. It is also an important tool for scientific research, and can be used for exploring the change of basic physical constants, detecting dark substances, verifying relativity, and the like. The importance of precise time and frequency is increasingly prominent throughout many aspects of national economic construction and national defense modernization, and the establishment, maintenance, measurement and transmission of the precise time and frequency are one of the important marks of national strategic competitiveness.
The time value has a certain particularity compared with other physical quantities, and only the past time can be accurately measured. In order to ensure the accuracy and reliability of atomic time signals, prospective prejudgment needs to be made according to the historical operation behavior of a main clock (atomic clock) in a laboratory, and a prejudgment result is adjusted to a time signal, so that the premeasurement evaluation is a key link of an atomic time generation system. At present, at home and abroad time-keeping laboratories mainly adopt polynomial fitting prediction and Kalman filter prediction to evaluate the prediction capability of an atomic clock, and in addition, a robustness prediction algorithm is also widely concerned by the industry. No matter what technique and method are used, the clock difference of the laboratory atomic clocks compared with each other is the only data source, and the clock difference is the relative deviation of the output phase or frequency signals of any two atomic clocks, and comprises 2 clocks and the information of the measurement noise. However, atomic clocks are physical signals output by 1 main clock, and only when the performance of 1 atomic clock is far higher than that of the other atomic clock, the atomic clock can evaluate the atomic clock worse according to a clock difference signal. In order to guarantee high accuracy and high reliability of atomic time signals, each laboratory adopts an atomic clock with optimal or nearly optimal performance as a main clock generated by atomic time, so that clock difference signals cannot accurately evaluate the main clock signals. In order to obtain reliable reference, the atomic clock group is usually combined to construct the clock group time mark TA, and theoretically, the performance of the clock group time mark TA can exceed that of any one atomic clock in the clock group, but in practical application, the performance of the clock group time mark TA is generally not superior to that of a better clock in the clock group, even far inferior to that of the optimal atomic clock. Research shows that the atomic clock in the same laboratory is influenced by environmental factors, and noise has strong correlation, so that the clock group time scale TA cannot be used as reference to accurately evaluate the performance of the atomic clock. Of course, the most stable and reliable time scale reference is coordinated universal time, UTC, i.e., international standard time. The method is released by the international metering Bureau (BIPM) after about 30-45 days, the time interval is 5 days, so that the performance of the atomic clock with the time interval of 5 days (integral multiple) can only be evaluated in a delayed mode, the UTC cannot be used as a reference to evaluate the performance of the atomic clock in 5 days, the real-time evaluation cannot be carried out, and the requirements for accurately regulating and controlling the main clock or monitoring other watch clocks cannot be met. In conclusion, establishing a real-time reliable reference is the basis for accurately evaluating the performance of the atomic clock and is the best guarantee for all prediction algorithms, clock group algorithms and driving algorithms.
In combination with the actual requirements generated by the atomic time scale of the time-keeping laboratory, the invention provides a method for constructing 1 virtualized atomic clock, the performance of which is close to the tested performance, and the performance is used as a reference to evaluate the performance of the entity atomic clock and monitor the abnormal behavior of the entity atomic clock. The virtualized atomic clock meets the real-time requirement by learning a large amount of historical behaviors of the entity atomic clock and extending the noise characteristic of preset time and depending on the calculated density.
As is well known, an atomic clock is a timing device, and the principle thereof is based on the physics of atoms, wherein atoms absorb or release electromagnetic energy according to the energy difference of different electron arrangement sequences, that is, the energy difference of different electron layers surrounding the atomic nucleus, wherein the electromagnetic energy is discontinuous, when the atoms transition from an "energy state" to a low "energy state", the atoms release electromagnetic waves, the characteristic frequency of the electromagnetic waves is discontinuous, that is, the resonance frequency of the same atom is constant, so that the atoms can be used as a metronome to maintain high-precision time, and when the physical atomic clock is influenced by the environment, abnormal conditions such as data deviation and the like occur, and a means for assisting in monitoring the physical atomic clock is needed. Research shows that the atomic clock in the same laboratory is influenced by environmental factors, and noise has strong correlation, so that the clock group time scale TA cannot be used as reference to accurately evaluate the performance of the atomic clock.
Disclosure of Invention
In view of the problems in the background, an object of the present invention is to provide a virtual atomic clock system, characterized by comprising: the device comprises a comparison measuring unit, a virtual atomic clock generating unit and a clock error calculating unit.
The virtual atomic clock system comprises the comparison measurement unit, and relative deviation information of at least one atomic clock relative to a reference TA is obtained.
In the virtual atomic clock system, the reference is an actual signal or a post-processed virtual signal.
According to the virtual atomic clock system, the virtual atomic clock generating unit learns the behavior of the atomic clock according to the deviation information acquired based on the comparison measuring unit.
In the virtual atomic clock system, the measurement information generated by the virtual atomic clock generation unit maintains the noise characteristics of the atomic clock.
According to the virtual atomic clock system, the clock error calculation unit extrapolates the deviation of the entity atomic clock with preset time relative to the reference through the measurement information generated by the virtual atomic clock generation unit to obtain the clock error data TA-T1.
The invention aims to provide a working method of a virtual atomic clock system for monitoring a physical atomic clock, which comprises the following working processes:
A. obtaining data of an atomic clock group as TA, obtaining data of an entity atomic clock as T0, and obtaining data of a virtual atomic clock as T1;
B. and obtaining the data comparison (TA-T0) of the atomic clock group and the entity atomic clock, obtaining the data comparison (TA-T1) of the atomic clock group and the virtual atomic clock, and obtaining the clock difference data between the entity atomic clock data T0 and the virtual atomic clock data T1 by carrying out subtraction on the two results of the step so as to judge the abnormal condition of the entity atomic clock.
The working method of the virtual atomic clock system for monitoring the entity atomic clock has an intermediate reference quantity which is obtained by utilizing the real-time weighted average of the atomic clock group.
The working method of the virtual atomic clock system for monitoring the entity atomic clock is characterized in that the deviation of the entity atomic clock with preset time relative to a reference is extrapolated to obtain clock error data (TA-T1), the deviation (TA-T0) of the entity atomic clock and the TA at the same moment is obtained, data conversion is carried out, the middle reference is eliminated, and the relative deviation (T0-T1) of the virtual clock and the entity clock is obtained.
The invention relates to a working method of a virtual atomic clock system for monitoring an entity atomic clock, which comprises at least one of the following clock error data:
a. clock error data of atomic clock mutual comparison, which is used for reflecting short-term operation characteristics of the entity atomic clock;
b. clock error data of the entity atomic clock relative to the atomic clock group is used for reflecting the middle-term operation characteristic of the entity atomic clock;
c. the function of the entity atomic clock is to reflect the long-term operation characteristic of the entity atomic clock relative to the clock error data of the coordinated world time.
Compared with the prior art, the performance of the virtual atomic clock system approaches to be measured, the performance of the entity atomic clock is evaluated as a reference, the abnormal behavior of the entity atomic clock is monitored, the virtual atomic clock meets the real-time requirement by learning a large amount of historical behaviors of the entity atomic clock and extending the noise characteristic of preset time, and the calculation density is relied on.
Drawings
FIG. 1 is a schematic diagram of the virtual clock assisted time keeping principle of the present invention.
Fig. 2 is a schematic diagram of sample set establishment in accordance with the present invention.
Fig. 3 is a schematic diagram of the neural network learning structure of the present invention.
Fig. 4 is a schematic diagram of the virtual clock system apparatus of the present invention.
FIG. 5 is a schematic structural diagram of a stochastic tracking strategy prediction process according to the present invention.
FIG. 6 is a schematic diagram of the comparison of the predicted results (frequency predicted value and error) of the simulated atomic clock of the present invention.
FIG. 7 is a graphical representation of the comparison of the predicted results (root mean square error) of the simulated atomic clock of the present invention.
Fig. 8 is a schematic diagram of the comparison of the actual atomic clock prediction results (frequency prediction values and errors of cesium clock and hydrogen clock) of the present invention.
Fig. 9 is a graphical representation of a comparison of actual atomic clock predictions (root mean square error of cesium clock and hydrogen clock) in accordance with the present invention.
Fig. 10 is a schematic diagram showing a comparison of results (frequency deviation) of two prediction methods of 10 hydrogen clocks according to the present invention.
FIG. 11 is a graphical representation of a comparison of the results of the two prediction methods of the invention 10 hydrogen clocks.
Detailed Description
The technical solutions in the embodiments of the present invention will be described in detail below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all embodiments. All other embodiments, which can be obtained by a person skilled in the art without any inventive step based on the embodiments of the present invention, are within the scope of the present invention.
In order that the technical solutions of the present invention will be more apparent, the present invention is further described in detail with reference to the following examples, it should be understood that the specific embodiments described herein are only for the purpose of illustrating the present invention, and are not to be construed as limiting the present invention.
In the description herein, unless otherwise specified, "a plurality" means two or more; the terms "upper", "lower", "left", "right", "inner", "outer", "front", "rear", "head", "tail", and the like, indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, are only for convenience in describing and simplifying the description, and do not indicate or imply that the device or element referred to must have a particular orientation, be constructed in a particular orientation, and be operated, and thus, should not be construed as limiting the invention. In the description herein, it is to be noted that, unless expressly stated or limited otherwise, the terms "connected" and "connected" are to be construed broadly, e.g., as meaning either a fixed connection, a removable connection, or an integral connection; the connection may be mechanical or electrical, and may be direct or indirect via an intermediate. The specific meanings of the above terms in the present invention can be understood in specific cases to those skilled in the art.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
In the present invention, fig. 1 is a schematic diagram of the virtual clock auxiliary time keeping principle of the present invention. Fig. 2 is a schematic diagram of sample set establishment in accordance with the present invention. Fig. 3 is a schematic diagram of the neural network learning structure of the present invention. Fig. 4 is a schematic diagram of the virtual clock system apparatus of the present invention. FIG. 5 is a schematic structural diagram of a stochastic tracking strategy prediction process according to the present invention. FIG. 6 is a schematic diagram of the comparison of the predicted results (frequency predicted value and error) of the simulated atomic clock of the present invention. FIG. 7 is a graphical representation of the comparison of the predicted results (root mean square error) of the simulated atomic clock of the present invention. Fig. 8 is a schematic diagram of the comparison of the actual atomic clock prediction results (frequency prediction values and errors of cesium clock and hydrogen clock) of the present invention. Fig. 9 is a graphical representation of a comparison of actual atomic clock predictions (root mean square error of cesium clock and hydrogen clock) in accordance with the present invention. Fig. 10 is a schematic diagram showing a comparison of results (frequency deviation) of two prediction methods of 10 hydrogen clocks according to the present invention. FIG. 11 is a graphical representation of a comparison of the results of the two prediction methods of the invention 10 hydrogen clocks.
The invention provides a virtual atomic clock system and a working method for monitoring an entity atomic clock, the virtual atomic clock system focuses on real-time diagnosis and monitoring of abnormal behaviors of a time-keeping entity atomic clock, constructs a virtualized atomic clock, assists in improving the time keeping capability of the entity atomic clock, the entity atomic clock is easily influenced by other factors of environmental change, so that the output frequency is jittered, in order to truly depict the actual behavior characteristics of the entity atomic clock under normal working conditions, historical data of the entity atomic clock is firstly cleaned and outliers are eliminated, and a historical data set mainly comprises: clock error data of mutual comparison of entity atomic clocks is used for representing short-term operation characteristics of the entity atomic clocks, clock error data of the atomic clocks relative to an atomic clock group is used for representing medium-term operation characteristics of the entity atomic clocks, clock error data of the entity atomic clocks relative to coordinated world time is used for representing long-term operation characteristics of the entity atomic clocks, deterministic behavior characteristics of the entity atomic clocks are analyzed according to clock error data of virtual atomic clocks, the entity atomic clocks and the atomic clock group respectively, relative phase deviation, relative frequency deviation and relative frequency drift of the entity atomic clocks are evaluated, deterministic behavior items are removed from original data, residual noise items are cut off to form a standard sample set, the standard sample set is randomly divided into two groups to form a standard sample training set and a standard sample testing set, the two groups can be used interactively and are respectively used for behavior prediction analysis and optimization check prediction analysis methods of the entity atomic clocks, the virtual atomic clock is characterized in that the behavior characteristics of the entity atomic clock are analyzed according to actual comparison and measurement historical data of the entity atomic clock and a sample set of the entity atomic clock, a model is established to predict the output signal value of the entity atomic clock at preset time, and the main prediction model and the method comprise (but are not limited to): a method for predicting output frequency of entity clock includes using numerical method to extrapolate measured value of preset time, using atomic clock group as average value of multiple atomic clocks weighted in real time as intermediate reference of entity atomic clock and virtual atomic clock, using virtual atomic clock without interference as auxiliary monitoring means when output frequency is changed by influence of environment, comparing two results separately in atomic clock group to obtain atomic clock group data (TA-T0) and (TA-T1) in real time, obtaining comparison clock difference data between entity atomic clock T0 and virtual atomic clock T1 by difference of two results.
In the present invention, the virtual atomic clock system optionally includes: 1 or more physical atomic clocks; the device comprises a comparison measuring unit, a virtual atomic clock generating unit and a deviation calculating unit.
In the invention, the virtual atomic clock system comprises the comparison measurement unit, and relative deviation information of each atomic clock relative to a reference is obtained to form an original data set.
In the invention, the comparison measurement unit of the virtual atomic clock system is a frequency signal of 5MHz, 10MHz, 100MHz or 1PPS second signal.
In the virtual atomic clock system, the reference is an actual signal or a post-processed virtual signal.
In the invention, the virtual atomic clock system can extrapolate the deviation of the entity atomic clock with preset time relative to the reference to obtain clock error data.
In the invention, the working method of the virtual atomic clock system for monitoring the entity atomic clock comprises the following working processes:
A. obtaining data of an atomic clock group as TA, obtaining data of an entity atomic clock as T0, and obtaining data of a virtual atomic clock as T1;
B. and obtaining the data comparison (TA-T0) of the atomic clock group and the entity atomic clock, obtaining the data comparison (TA-T1) of the atomic clock group and the virtual atomic clock, and obtaining the clock difference data between the entity atomic clock data T0 and the virtual atomic clock data T1 by carrying out subtraction on the two results of the step so as to judge the abnormal condition of the entity atomic clock.
In the invention, the virtual atomic clock learns the historical behavior of the atomic clock by using an algorithm, extrapolates the deviation of the entity atomic clock at preset time relative to a reference to obtain clock error data (TA-T1), and takes the deviation (TA-T0) of the entity atomic clock and the TA at the same time to perform data conversion and eliminate intermediate reference to obtain the relative deviation (T0-T1) of the virtual atomic clock and the entity clock.
The working method also comprises the following optional steps of firstly cleaning the historical data of the entity atomic clock and proposing an outlier, and then establishing a sample data set, wherein the optional steps comprise:
a. clock error data of atomic clock mutual comparison, which is used for reflecting short-term operation characteristics of the entity atomic clock;
b. clock error data of the entity atomic clock relative to the atomic clock group is used for reflecting the middle-term operation characteristic of the entity atomic clock;
c. the function of the entity atomic clock is to reflect the long-term operation characteristic of the entity atomic clock relative to the clock error data of the coordinated world time.
According to the data of the atomic clock group, the data of the entity atomic clock and the data of the virtual atomic clock, the deterministic behavior characteristics of the entity atomic clock are analyzed, and the relative phase deviation, the relative frequency deviation and the relative frequency drift of the entity atomic clock are obtained.
In the invention, deterministic behavior items are removed from original data of an entity atomic clock, residual noise items are truncated to obtain a standard sample set, and then the standard sample set is randomly divided into a standard sample training set and a standard sample testing set.
In the invention, the measured historical data is compared according to the real-time data of the entity atomic clock, and the data of the preset time is extrapolated by adopting a numerical method.
In the invention, the atomic clock group comprises a plurality of entity atomic clocks, and the real-time weighted average value of the atomic clock group is used as the intermediate reference quantity of the entity atomic clocks and the virtual atomic clocks.
In the present invention, the data of the atomic clock group is TA, the data of the physical atomic clock is T0, and the data of the virtual atomic clock is T1.
In the invention, the deviation of the entity atomic clock with preset time relative to the reference is extrapolated to obtain clock error data (TA-T1), the deviation of the entity atomic clock and the TA at the same moment is taken (TA-T0), data conversion is carried out, the middle reference is eliminated, and the relative deviation of the virtual clock and the entity clock is obtained (T0-T1).
The working method of the virtual atomic clock system for monitoring the entity atomic clock further comprises the steps of predicting the behavior of the entity atomic clock, analyzing the behavior characteristics of the atomic clock according to the sample set of the entity atomic clock, and establishing a model to predict the output signal value of the atomic clock in the preset time.
In the invention, the working method of the virtual atomic clock system for monitoring the entity atomic clock comprises polynomial fitting prediction, prediction based on a neural network and Kalman filter prediction.
In the working method of the virtual atomic clock system for monitoring the entity atomic clocks, a plurality of entity atomic clocks pass through a comparison measurement unit to obtain the relative deviation information of each entity atomic clock relative to the data of an atomic clock group, and an original data set is formed.
The method focuses on real-time diagnosis and monitoring of abnormal behaviors of the atomic clock in time keeping, constructs a virtualized atomic clock, and assists in improving the time keeping capability of the atomic clock in entity.
As shown in fig. 1, an entity atomic clock is susceptible to environmental changes and other factors, which causes output frequency jitter; the virtual clock extrapolates the measured value of the preset time by adopting a numerical method according to the actual comparison and measurement historical data of the entity atomic clock; the clock group TA is the average value of real-time weighting of a plurality of clocks, and can be used as the intermediate reference quantity of the physical clock and the virtual clock, and other real-time signals can be used for substitution. Therefore, when the physical clock is influenced by the environment and the output frequency changes, the undisturbed virtual clock can be used as an auxiliary monitoring means, in practical application, the two are respectively compared and measured in a clock group TA in real time to obtain clock group data (TA-T0) and (TA-T1), and the difference between the two results is obtained to obtain comparison clock difference data between the physical clock T0 and the virtual clock T1, so that the abnormal condition of the output frequency of the physical clock is judged.
The invention provides a virtual atomic clock, belonging to the technical field of atomic clocks, a plurality of entity atomic clocks obtain the relative deviation information of each atomic clock relative to a reference TA through a comparison measurement unit to form an original data set, the original data set is analyzed to eliminate the abnormal behavior of the atomic clock, such as random jump of phase, frequency or frequency drift, forming an atomic clock sample data set, learning the historical behavior of an atomic clock by an algorithm through an atomic clock prediction analysis unit, extrapolating the deviation of the entity atomic clock at preset time relative to a reference to obtain clock error data (TA-T1), taking the deviation of the entity atomic clock and the TA at the same moment (TA-T0), performing data conversion, eliminating an intermediate reference to obtain the relative deviation of the virtual atomic clock and the entity atomic clock (T0-T1), the performance of the atomic clock is close to the measured performance, and the performance is used as a reference to evaluate the performance of the atomic clock and monitor the abnormal behavior of the atomic clock.
In the invention, the step of establishing the sample data set is that in order to truly depict the actual behavior characteristics of the atomic clock under the normal working condition, the historical data of the atomic clock is cleaned and outliers are removed. The historical data set mainly comprises: 1) clock error data of atomic clocks are compared with each other, so that the short-term operation characteristic of the atomic clocks is reflected; 2) clock difference data of the atomic clock relative to the clock group TA reflects the middle-term operating characteristics of the atomic clock; 3) the atomic clock relatively coordinates clock error data of the Universal Time Coordinated (UTC) and reflects the long-term operation characteristic of the atomic clock. And analyzing the deterministic behavior characteristics of the atomic clock according to the 3 atomic clock difference data respectively, and evaluating the relative phase deviation, the relative frequency deviation and the relative frequency drift of the atomic clock. And then removing a deterministic behavior item from the original data, truncating a residual noise item to form a standard sample set, randomly dividing the standard sample set into two groups to form a standard sample training set and a standard sample testing set, wherein the two sets can be used interactively and are respectively used for atomic clock behavior prediction analysis and an optimized check prediction analysis method.
In the invention, the atomic clock behavior prediction means that a model is established to predict the output signal value (time or frequency) of the atomic clock at a preset time by analyzing the behavior characteristics of the atomic clock according to an atomic clock sample set. The main predictive models and methods include (but are not limited to): polynomial fit prediction, Kalman filter prediction, neural network based prediction, and other types of prediction methods. Taking a prediction method based on a neural network as an example, as shown in fig. 3, the number n of elements of an input layer is mainly determined according to the characteristics of 3 types of clock difference data, the number m of neurons of a hidden layer is planned to be determined by local optimization according to the data types of the input layer, and an output layer is basically determined as three types of phase information (p), frequency information (f) and frequency drift information (d) of an atomic clock. In the overall design idea, the neural network learning unit is responsible for repeatedly strengthening and learning the target characteristics from a large number of input samples and mapping the characteristics of the samples into a function distribution. Considering that the atomic clock error data has a typical time sequence result and the front and back data have long-range correlation in the time dimension, a long-range and short-range memory model LSTM in the recurrent neural network can be adopted to construct a neural network learning unit with global memory.
In the present invention, the structure of the virtual clock system device is schematically shown in fig. 4, and 1 or more physical atomic clocks pass through a comparison measurement unit (usually, a frequency signal is 5MHz, 10MHz, 100MHz, or 1PPS second signal), and relative deviation information of each atomic clock with respect to a reference TA (actual signal or post-processed virtual signal) is obtained, so as to form an original data set. The original data set is analyzed, abnormal behaviors of the atomic clock, such as random jump of phase, frequency or frequency drift, are eliminated, and an atomic clock sample data set is formed. And then, an atomic clock prediction analysis unit learns the historical behavior of the atomic clock by using an algorithm, and extrapolates the deviation of the entity atomic clock with preset time relative to a reference to obtain clock error data (TA-T1). And taking the deviation (TA-T0) of the physical clock and the TA at the same moment, performing data conversion, eliminating the middle reference, and obtaining the relative deviation (T0-T1) of the virtual clock and the physical clock.
Example 1: the stochastic tracking strategy predicts atomic clock behavior:
this embodiment 1 includes a predictor group, where each predictor works in an independent subspace, and the weighted average of all predictors for future predictions as the final prediction result is composed of the following parts:
(1) history data:
let X be the measurement vector of the atomic clock phase or frequency data and T be the interval time between each data point.
X＝(x1x2…xn) (1)
Wherein X represents a historical data sample, namely a phase difference or a frequency difference measured by an atomic clock relative to a reference clock or a time scale; xt represents the phase or frequency difference at time t, and vector X serves as historical data of atomic clock measurements for predicting future phase or frequency changes of the atomic clock.
(2) Random grouping
A random grouping scheme without putting back is applied, the historical data X is divided into p subsets, each subset contains m sample data, and n is p · m, the number p of subsets is typically chosen to be equal to the amount m of sample data per subset, i.e.
The specific design of the two parameters also requires consideration of the predicted targets and atomic clock characteristics.
(3) Fitting function
Using a function for each packet
A low order polynomial is applied to fit m sample data points (typically no more than 3) within the set, where
Representing the predictor j, t represents the time,
a set of parameters representing a polynomial fit, including all or part of phase, frequency and frequency drift.
(4) Defining weights
Each predictor
Depending on the specific objective, some statistics, such as mean absolute error, root mean square error, etc., may be used to evaluate the generalization capability of the predictor, i.e., the predictor weights.
(5) Weighted average
Merging predictors of all predictors using weighted averaging
Thus the predicted value xn +1 can be expressed as:
random pursuitPredictor for each random grouping in trace policy
Is taken as a posterior distribution, where wj represents the predictor
Normalized weights, so the combined predictor xn +1 is the weighted average of all posterior distributions.
(6) Outputting the predicted value
Weighted average
And the next-time predicted value is obtained as a final random tracking strategy according to the historical data vector.
In summary, the stochastic tracking strategy is a weighted average prediction method constructed based on a predictor group, which requires a prerequisite that the historical data vector X can represent the characteristics of the output frequency or phase of an atomic clock, and most data in the vector X has high reliability.
The workflow of the scheme and the comparison with the results of the conventional kalman filter prediction are shown in fig. 1 to 5.
Example 2: the long-range and short-range memory neural network predicts the atomic clock behavior:
in this embodiment 2, a long-range and short-range memory neural network unit is designed, the output frequency information of the atomic clock with the preset time is predicted by learning the historical data of the atomic clock, and the experimental results compared with the conventional kalman filter prediction method are shown in fig. 5 to 6.
The electrical components presented in the document are all electrically connected with an external master controller and 220V mains, and the master controller can be a conventional known device controlled by a computer or the like.
Compared with the prior art, the invention provides a virtual atomic clock which is constructed, the performance of the virtual atomic clock is close to the performance to be measured, the performance of the entity atomic clock is evaluated as a reference, the abnormal behavior of the entity atomic clock is monitored, the virtual atomic clock meets the real-time requirement by learning a large amount of historical behaviors of the entity atomic clock and extending the noise characteristic of preset time, and the calculation density is relied on.
The invention discloses a virtual atomic clock system which comprises a comparison measuring unit, a virtual atomic clock generating unit and a clock error calculating unit. The virtual atomic clock system is suitable for accurate time synchronization in financial businesses such as capital borrowing, exchange rate calculation, stock trading and the like. In addition, the virtual atomic clock system is also suitable for aspects such as network appointment, shared bicycle, unmanned automobile and the like, and brings great changes to life. The virtual atomic clock system is suitable for a Global Navigation Satellite System (GNSS). The virtual atomic clock system is suitable for exploring the change of basic physical constants, detecting dark substances, verifying relativity theory and the like.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
The above description is only an embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes performed by the present specification and drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (4)
1. A virtual atomic clock system, comprising: 1 or more entity atomic clocks, a comparison measuring unit, a virtual atomic clock generating unit and a clock error calculating unit; the measurement information generated by the virtual atomic clock generating unit maintains the noise characteristic of the atomic clock;
the comparison measuring unit is used for obtaining the relative deviation information of at least one atomic clock relative to the reference TA;
the reference is an actual signal or a post-processed virtual signal;
the virtual atomic clock generating unit learns the behavior of the atomic clock according to the deviation information acquired based on the comparison measuring unit;
and the clock error calculation unit extrapolates the deviation of the entity atomic clock with preset time relative to the reference through the measurement information generated by the virtual atomic clock generation unit to obtain clock error data TA-T1, wherein TA is the data of the atomic clock group, and T1 is the data of the virtual atomic clock.
2. An operation method of a virtual atomic clock system for monitoring a physical atomic clock, using the virtual atomic clock system of claim 1, comprising the following operation processes:
A. obtaining data of an atomic clock group as TA, obtaining data of an entity atomic clock as T0, and obtaining data of a virtual atomic clock as T1;
B. and obtaining the data comparison (TA-T0) of the atomic clock group and the entity atomic clock, obtaining the data comparison (TA-T1) of the atomic clock group and the virtual atomic clock, and obtaining the clock difference data between the entity atomic clock data T0 and the virtual atomic clock data T1 by carrying out subtraction on the two results of the step so as to judge the abnormal condition of the entity atomic clock.
3. The method of claim 2, wherein there is an intermediate reference quantity obtained using a real-time weighted average of the atomic clock set.
4. A method of operating a virtual atomic clock system for monitoring physical atomic clocks as recited in claim 3, including at least one of the following clock difference data:
a. clock error data of atomic clock mutual comparison, which is used for reflecting short-term operation characteristics of the entity atomic clock;
b. clock error data of the entity atomic clock relative to the atomic clock group is used for reflecting the middle-term operation characteristic of the entity atomic clock;
c. the function of the entity atomic clock is to reflect the long-term operation characteristic of the entity atomic clock relative to the clock error data of the coordinated world time.
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| CN111399366B (en) * | 2020-03-30 | 2021-06-22 | 中国电子科技集团公司第五十四研究所 | Multi-clock comprehensive time keeping method and multi-rubidium clock time keeping device |
| CN111711448B (en) * | 2020-08-07 | 2023-03-21 | 电信科学技术第五研究所有限公司 | Rubidium atomic clock taming system and method |
| CN112230532A (en) * | 2020-11-24 | 2021-01-15 | 中国计量科学研究院 | New atomic clock signal prediction method, device and system |
| CN112445120B (en) * | 2020-11-27 | 2022-04-22 | 西安空间无线电技术研究所 | Distributed center-free space-based time reference establishing and maintaining system |
| CN114415488B (en) * | 2021-12-31 | 2024-04-02 | 北京无线电计量测试研究所 | Method and system for detecting and correcting clock error data abnormality of atomic clock |
| CN115685128B (en) * | 2022-11-14 | 2023-04-11 | 中国人民解放军空军预警学院 | Radar target tracking algorithm and electronic equipment under maneuvering target scene |
| CN115933356B (en) * | 2023-01-09 | 2023-08-22 | 北京航空航天大学 | High-precision time synchronization system and method for virtual atomic clock |
| CN115955270B (en) * | 2023-03-14 | 2023-05-16 | 仁通融合(南京)信息技术有限公司 | Data acquisition monitoring and data analysis system |
| CN117111434B (en) * | 2023-08-17 | 2024-03-29 | 湖南时空信安科技有限公司 | Clock performance evaluation method and device and terminal equipment |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101082663A (en) * | 2006-05-31 | 2007-12-05 | 中国科学院国家授时中心 | Virtual atomic clock method in repeater satellite navigation |
| CN101917760A (en) * | 2010-08-02 | 2010-12-15 | 中国科学院国家授时中心 | Common view principle-based unilateral time transmission method |
| CN101975956A (en) * | 2010-10-10 | 2011-02-16 | 桂林电子科技大学 | CAPS (China Area Position System) satellite analog signal generator |
| CN203148570U (en) * | 2013-02-04 | 2013-08-21 | 江汉大学 | Light speed anisotropy measuring device |
| CN105974777A (en) * | 2016-07-19 | 2016-09-28 | 北京工业大学 | Method for generating atomic time scale through Algos and Kalman combination |
| CN106647223A (en) * | 2016-10-13 | 2017-05-10 | 中国电子科技集团公司第二十研究所 | Quick stable real-time adjustment method for atomic clock timing |
| CN109508510A (en) * | 2018-12-20 | 2019-03-22 | 国网河南省电力公司焦作供电公司 | A kind of rubidium atomic clock parameter estimation algorithm based on improved Kalman filtering |
| CN109902882A (en) * | 2019-03-21 | 2019-06-18 | 北京工业大学 | Atomic clock clock deviation prediction model training method and device |
Family Cites Families (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104238352B (en) * | 2014-09-24 | 2017-07-21 | 北京市计量检测科学研究院 | The local time standard generation system and method that a kind of National primary standard is controlled |
| CN105137751A (en) * | 2015-09-06 | 2015-12-09 | 中国电力科学研究院 | Calibration system for measuring production scheduling platform time value and calibration method thereof |
| US20170281102A1 (en) * | 2016-03-31 | 2017-10-05 | Weng-Dah Ken | Non-contact angle measuring apparatus, mission critical inspection apparatus, non-invasive diagnosis/treatment apparatus, method for filtering matter wave from a composite particle beam, non-invasive measuring apparatus, apparatus for generating a virtual space-time lattice, and fine atomic clock |
| CN108809463B (en) * | 2017-04-28 | 2019-12-27 | 工业和信息化部电信研究院 | Multi-reference time clock weighting synthesis method |
| CN109765582A (en) * | 2019-02-13 | 2019-05-17 | 重庆市计量质量检测研究院 | A kind of temporal frequency calibration system based on GNSS |
-
2019
- 2019-10-06 CN CN201910946572.1A patent/CN110837219B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101082663A (en) * | 2006-05-31 | 2007-12-05 | 中国科学院国家授时中心 | Virtual atomic clock method in repeater satellite navigation |
| CN101917760A (en) * | 2010-08-02 | 2010-12-15 | 中国科学院国家授时中心 | Common view principle-based unilateral time transmission method |
| CN101975956A (en) * | 2010-10-10 | 2011-02-16 | 桂林电子科技大学 | CAPS (China Area Position System) satellite analog signal generator |
| CN203148570U (en) * | 2013-02-04 | 2013-08-21 | 江汉大学 | Light speed anisotropy measuring device |
| CN105974777A (en) * | 2016-07-19 | 2016-09-28 | 北京工业大学 | Method for generating atomic time scale through Algos and Kalman combination |
| CN106647223A (en) * | 2016-10-13 | 2017-05-10 | 中国电子科技集团公司第二十研究所 | Quick stable real-time adjustment method for atomic clock timing |
| CN109508510A (en) * | 2018-12-20 | 2019-03-22 | 国网河南省电力公司焦作供电公司 | A kind of rubidium atomic clock parameter estimation algorithm based on improved Kalman filtering |
| CN109902882A (en) * | 2019-03-21 | 2019-06-18 | 北京工业大学 | Atomic clock clock deviation prediction model training method and device |
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