Beidou satellite-based real-time rapid timing method and system based on multi-factor integration

Abstract

The present invention discloses a multi-factor integrated Beidou satellite-based real-time rapid timing method and system, which first constructs an observation value random model based on the approximate coordinates of the receiver and its vertical ionospheric delay data, and constructs a continuous vertical ionospheric delay field for the entire receiving area, which can accurately obtain the vertical ionospheric delay observation value of any position point. Then, the vertical ionospheric delay of the puncture point is corrected by calculating the satellite-side differential code deviation value, accurately compensating for the influence of the ionosphere on signal propagation, and then, using it as a reference value, the ionospheric random model is constructed based on the observation value and reference value of the vertical ionospheric delay of the reference point, which can more accurately predict the vertical ionospheric delay at any time and any position, thereby improving the positioning and timing accuracy. In addition, the precise ephemeris random model eliminates the problem of inconsistent clock error references through the method of secondary difference, reduces the error caused by hardware deviation, and further improves the timing and positioning accuracy.

Description

Technical Field

[0001] The present invention relates to the field of Beidou satellite-based timing technology, and in particular to a Beidou satellite-based real-time rapid timing method and system integrating multiple elements, electronic equipment, and a computer-readable storage medium. Background Art

[0002] The BeiDou Navigation Satellite System (BDS) has been widely used in global positioning, navigation, and timing. To meet the demands for high precision and high reliability, PPP (Precise Point-to-Point Positioning) technology has been introduced into the BDS. However, in complex environments, such as mountainous areas, urban canyons, and tree-covered areas, satellite signals may be affected by multipath interference, signal obstruction, or other factors, which can compromise the credibility of BeiDou satellite-based PPP solutions and lead to poor timing accuracy. Furthermore, to further improve timing accuracy, it is usually necessary to consider the influence of other error sources, such as the ionosphere and troposphere. The ionosphere, in particular, refracts GPS signals, affecting timing accuracy. Although there are many methods available to correct ionospheric errors, they all rely on data from ground base stations, and the calculation process is very complex. Summary of the Invention

[0003] The present invention provides a multi-factor integrated Beidou satellite-based real-time rapid timing method and system, electronic equipment, and computer-readable storage medium, which can perform accurate timing and positioning under various environmental conditions and have better robustness.

[0004] According to one aspect of the present invention, a multi-factor integrated Beidou satellite-based real-time rapid timing method is provided, comprising the following:

[0005] Using a receiver that supports both BeiDou SBAS and PPP-B2b signals, pseudorange observations on two frequencies are obtained to calculate the vertical ionospheric delay at the receiver. Combined with the receiver's position, the Kriging algorithm is used to interpolate the continuous observation values ​​of each receiver's coverage area to obtain a random model.

[0006] Calculate the satellite-side differential code bias and use it to correct the ionospheric slant delay. Calculate the coordinates of the ionospheric puncture point and combine it with the ionospheric projection function to obtain the vertical ionospheric delay corresponding to the puncture point, which is used as the reference value of the vertical ionospheric delay.

[0007] Based on the observation value random model, the vertical ionospheric delay observation value of the reference point is obtained, the difference between the vertical ionospheric delay observation value of the reference point and the vertical ionospheric delay reference value is calculated, and the distribution of the difference at different latitudes and longitudes is analyzed to establish the ionospheric random model that integrates time, latitude and longitude;

[0008] The satellite-based PPP clock error accuracy is calculated by unifying the reference frame of the satellite-based PPP orbit correction and the IGS post-precision orbit product. The original signal is generated based on the ionospheric random model and the signal is reconstructed using the wavelet analysis method. The precise ephemeris random model is then constructed based on the satellite-based PPP clock error, satellite-based PPP clock error accuracy, the original signal, and the reconstructed signal.

[0009] The observation value random model, ionosphere random model and precise ephemeris random model are integrated and PPP solution is performed.

[0010] Furthermore, the process of calculating the satellite-side differential code bias and correcting the ionospheric slant delay using the satellite-side differential code bias includes the following:

[0011] Obtain the receiver-side differential code deviation value of each satellite;

[0012] Calculate the ionospheric slant delay in the L1 band;

[0013] The satellite-side differential code deviation value is calculated based on the receiver-side differential code deviation value and the ionospheric slant delay of the L1 band;

[0014] The satellite-side differential code deviation value is used to correct the ionospheric slant delay in the L1 frequency band to obtain the corrected ionospheric slant delay.

[0015] Furthermore, the satellite-side differential code deviation value is calculated based on the following formula:

[0016]

[0017] Among them, DCB satellite Indicates the satellite differential code deviation value, DCB receiver represents the differential code deviation value at the receiver end, c represents the speed of light, Indicates the ionospheric slant delay in the L1 band.

[0018] Furthermore, the process of calculating the coordinates of the ionospheric puncture point includes the following:

[0019] Get the geographic coordinates of the receiver;

[0020] The azimuth and altitude angles are calculated based on the positions of the receiver and the satellite;

[0021] The geographic coordinates of the ionospheric puncture point are calculated based on the geographic coordinates, azimuth, and altitude of the receiver. The calculation formula is:

[0022]

[0023] R′=R E +h

[0024] h=hIPP -h receiver

[0025] Among them, φ IPP ,λ IPP denote the latitude and longitude coordinates of the ionospheric puncture point, φ r ,λ r They represent the latitude and longitude coordinates of the receiver, s represents the distance from the receiver to the puncture point, R′ represents the distance from the puncture point to the center of the earth, El represents the altitude angle, and R E represents the radius of the earth, h represents the height of the ionosphere, h IPP Indicates the reference height of the ionosphere, h receiver Indicates the receiver altitude.

[0026] Furthermore, the satellite-based PPP clock error accuracy is calculated based on the following formula:

[0027] ΔC=(C SBAS -C IGS1 )-(C IGS2 -C IGS1 )

[0028] Where ΔC represents the satellite-based PPP clock error accuracy, C SBAS represents the satellite-based PPP clock error, C IGS1 and C IGS2 Represent the clock differences of two different IGS products.

[0029] Furthermore, the expression of the precise ephemeris random model is:

[0030] C random (t) = C SBAS -ΔC+E d

[0031] Among them, C random (t) represents the precise ephemeris random model, E d =∫d(t) 2 dt, d(t) represents the difference signal between the reconstructed signal and the original signal, E d Represents the energy obtained by integrating the difference signals.

[0032] Furthermore, the process of fusing the observation value random model, the ionosphere random model and the precise ephemeris random model and performing PPP solution includes the following:

[0033] Constructing the state matrix Among them, X obs 、X iono and X orbit They represent the state vectors of the observation random model, ionosphere random model and precise ephemeris random model respectively;

[0034] Constructing the state transition matrix Among them, F obs 、F iono and F orbit Represent the state transition submatrices of the observation random model, ionosphere random model and precise ephemeris random model respectively;

[0035] Construct the observation matrix H = [H obs H iono H orbit ], where H obs 、H iono and H orbit Represent the observation sub-matrices of the observation value random model, ionosphere random model and precise ephemeris random model respectively;

[0036] The extended Kalman filter algorithm is used to solve PPP.

[0037] In addition, the present invention also provides a multi-factor integrated Beidou satellite-based real-time rapid timing system, which adopts the above method and is characterized by comprising:

[0038] The observation value random model construction module is used to use a receiver that supports both Beidou SBAS signals and PPP-B2b signals to obtain pseudorange observations on two frequencies to calculate the vertical ionospheric delay at the receiver. The Kriging algorithm is then used to interpolate the receiver's position to obtain a continuous observation value random model for each receiver coverage area.

[0039] The vertical ionospheric delay correction module is used to calculate the satellite-side differential code bias and use it to correct the ionospheric slant delay. It solves the coordinates of the ionospheric puncture point and combines it with the ionospheric projection function to obtain the vertical ionospheric delay corresponding to the puncture point, and uses it as the vertical ionospheric delay reference value.

[0040] The ionospheric random model construction module is used to obtain the vertical ionospheric delay observation value of the reference point based on the observation value random model, calculate the difference between the vertical ionospheric delay observation value of the reference point and the vertical ionospheric delay reference value, and analyze the distribution of the difference at different latitudes and longitudes to establish an ionospheric random model that integrates time, latitude, and longitude;

[0041] The precise ephemeris random model construction module is used to unify the reference frame of the satellite-based PPP orbit correction and the IGS post-precision orbit product to calculate the satellite-based PPP clock error accuracy. The original signal is generated based on the ionospheric random model and the signal is reconstructed using the wavelet analysis method. The precise ephemeris random model is then constructed based on the satellite-based PPP clock error, satellite-based PPP clock error accuracy, original signal and reconstructed signal.

[0042] The model fusion and PPP solution module is used to fuse the observation value random model, ionosphere random model and precise ephemeris random model and perform PPP solution.

[0043] In addition, the present invention also provides an electronic device, including a processor and a memory, wherein the memory stores a computer program, and the processor is configured to execute the steps of the above method by calling the computer program stored in the memory.

[0044] In addition, the present invention also provides a computer-readable storage medium for storing a computer program for performing multi-factor fusion Beidou satellite-based real-time rapid timing, and the computer program executes the steps of the method described above when running on a computer.

[0045] The present invention has the following beneficial effects:

[0046] The multi-factor fusion Beidou satellite-based real-time rapid timing method of the present invention first constructs an observation value random model based on the approximate coordinates of the receiver and its vertical ionospheric delay data, and predicts the vertical ionospheric delay data of the unknown position from the known data points. A continuous vertical ionospheric delay field can be constructed for the entire receiving area, so that the vertical ionospheric delay observation value of any position point can be accurately obtained. The vertical ionospheric delay of the puncture point is then corrected by calculating the satellite-side differential code deviation value, and the influence of the ionosphere on signal propagation is more accurately compensated. Then, the vertical ionospheric delay of the corrected puncture point is used as a reference value, and the ionospheric random model is constructed based on the observed value and reference value of the vertical ionospheric delay of the reference point, which greatly improves the accuracy of the ionospheric random model and can more accurately predict the vertical ionospheric delay at any time and any position, thereby improving the positioning and timing accuracy. In addition, the precise ephemeris random model eliminates the problem of inconsistent clock error references through a secondary difference method, reduces the error caused by hardware deviation, and further improves the timing and positioning accuracy. Therefore, the present invention integrates the observation value random model, the ionosphere random model and the precise ephemeris random model, and uses the Kalman filter technology to dynamically adjust the state vector and weight of each model, so that accurate timing and positioning can be performed under various environmental conditions with better robustness.

[0047] In addition, the multi-factor fusion Beidou satellite-based real-time rapid timing system of the present invention also has the above advantages.

[0048] In addition to the above-described objects, features and advantages, the present invention has other objects, features and advantages. The present invention will be further described in detail below with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] The accompanying drawings, which constitute part of this application, are intended to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are intended to explain the present invention and do not constitute an undue limitation of the present invention. In the accompanying drawings:

[0050] Figure 1 It is a flow chart of the Beidou satellite-based real-time rapid timing method with multi-factor fusion in the preferred embodiment of the present application.

[0051] Figure 2 yes Figure 1 Schematic diagram of the sub-process of step S2 in FIG.

[0052] Figure 3 yes Figure 1 Another sub-process diagram of step S2 in FIG.

[0053] Figure 4 This is a schematic diagram of the module structure of the Beidou satellite-based real-time rapid timing system with multi-factor integration in another embodiment of the present application. DETAILED DESCRIPTION

[0054] It should be noted that, in the absence of conflict, the embodiments and features of the embodiments in this application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0055] Reference Figure 1 The preferred embodiment of the present application provides a multi-factor integrated Beidou satellite-based real-time rapid timing method, including the following contents:

[0056] Step S1: Using a receiver that supports both BeiDou SBAS and PPP-B2b signals, obtain pseudorange observations on two frequencies to calculate the vertical ionospheric delay at the receiver. Combined with the receiver's position, the Kriging algorithm is used to interpolate the continuous observation value stochastic model for each receiver coverage area.

[0057] Step S2: Calculate the satellite-side differential code bias and use it to correct the ionospheric slant delay. Calculate the coordinates of the ionospheric puncture point and combine it with the ionospheric projection function to obtain the vertical ionospheric delay corresponding to the puncture point, and use it as the vertical ionospheric delay reference value.

[0058] Step S3: obtaining the vertical ionospheric delay observation value of the reference point based on the observation value random model, calculating the difference between the vertical ionospheric delay observation value of the reference point and the vertical ionospheric delay reference value, and analyzing the distribution of the difference at different latitudes and longitudes to establish an ionospheric random model that integrates time, latitude, and longitude;

[0059] Step S4: After unifying the reference frames of the satellite-based PPP orbit correction and the IGS post-precision orbit product, the satellite-based PPP clock error accuracy is calculated. An original signal is generated based on the ionospheric random model and the signal is reconstructed using the wavelet analysis method. A precise ephemeris random model is then constructed based on the satellite-based PPP clock error, satellite-based PPP clock error accuracy, the original signal, and the reconstructed signal.

[0060] Step S5: Fusing the observation value random model, the ionosphere random model and the precise ephemeris random model and performing PPP solution.

[0061] It can be understood that the multi-factor fusion Beidou satellite-based real-time rapid timing method of this embodiment first constructs an observation value stochastic model based on the approximate coordinates of the receiver and its vertical ionospheric delay data. The vertical ionospheric delay data at an unknown location is predicted from known data points. This constructs a continuous vertical ionospheric delay field for the entire receiving area, thereby accurately obtaining the vertical ionospheric delay observation value at any location. The vertical ionospheric delay at the puncture point is then corrected by calculating the satellite-side differential code deviation value, more accurately compensating for the impact of the ionosphere on signal propagation. The corrected vertical ionospheric delay at the puncture point is then used as a reference value, and the ionospheric stochastic model is constructed based on the observed value and reference value of the vertical ionospheric delay at the reference point. This greatly improves the accuracy of the ionospheric stochastic model and can more accurately predict the vertical ionospheric delay at any time and any location, thereby improving positioning and timing accuracy. In addition, the precise ephemeris stochastic model eliminates the problem of inconsistent clock references through a secondary difference method, reducing errors caused by hardware bias and further improving timing and positioning accuracy. Therefore, the present invention integrates the observation value random model, the ionosphere random model and the precise ephemeris random model, and uses the Kalman filter technology to dynamically adjust the state vector and weight of each model, so that accurate timing and positioning can be performed under various environmental conditions with better robustness.

[0062] It can be understood that in step S1, a dual-frequency receiver that supports both Beidou SBAS (Satellite-Based Augmentation System) signals and PPP-B2b signals is used to obtain pseudorange observations on two frequencies, and then the vertical ionospheric delay at the receiver is calculated based on the following formula:

[0063]

[0064] Where VTEC represents the vertical ionospheric delay at the receiver, P1 and P2 represent pseudorange observations at two different frequencies, and f1 and f2 represent the two frequencies of a dual-frequency receiver. The designated area is then gridded. The approximate coordinates of the receivers and the vertical ionospheric delay at those coordinates are interpolated using the kriging algorithm to establish a continuous random model of observations for each receiver's coverage area. This random model can generate the vertical ionospheric delay for any point within the receiver's coverage area. The kriging algorithm is an existing algorithm, and the specific interpolation process is not detailed here.

[0065] It can be understood that the observation value random model of the present invention is based on the approximate coordinates of the receiver and its vertical ionospheric delay data, and predicts the vertical ionospheric delay data of an unknown location from known data points. It can construct a continuous vertical ionospheric delay field for the entire receiving area, thereby more accurately predicting and compensating for the ionospheric delay, especially in different geographical locations and different ionospheric conditions, thereby improving positioning and timing accuracy.

[0066] It is understandable that Figure 2 As shown, in step S2, the process of calculating the satellite-side differential code bias and correcting the ionospheric slant delay using the satellite-side differential code bias includes the following:

[0067] Step S21a: Obtain the receiver-side differential code deviation value of each satellite;

[0068] Step S22a: Calculate the ionospheric slant delay in the L1 frequency band;

[0069] Step S23a: Calculating the satellite-side differential code deviation value based on the receiver-side differential code deviation value and the ionospheric slant delay of the L1 frequency band;

[0070] Step S24a: correcting the ionospheric slant delay of the L1 frequency band using the satellite-side differential code deviation value to obtain a corrected ionospheric slant delay.

[0071] Specifically, first obtain the integer clock product from the CNES analysis center, and then obtain the receiver-side differential code deviation value DCB of each satellite from the integer clock product receiver Then, the ionospheric slant delay in the L1 band is calculated based on the following formula: in, represents the ionospheric slant delay in the L1 band, R E represents the radius of the earth, h represents the height of the ionosphere, h=h IPP -h receiver , h IPP Indicates the reference height of the ionosphere, h receiver represents the receiver height, El represents the satellite altitude angle, I υRepresents the vertical ionospheric delay. The satellite differential code deviation value is calculated based on the following formula:

[0072]

[0073] Among them, DCB satellite Indicates the satellite differential code deviation value, DCB receiver represents the differential code deviation value at the receiver end, and c represents the speed of light. Then, the ionospheric slant delay in the L1 band is corrected based on the following formula to obtain the corrected ionospheric slant delay: in, represents the corrected ionospheric slant delay.

[0074] It can be understood that in the present invention, by calculating the satellite-side differential code deviation value to correct the ionospheric slant delay, the influence of the ionosphere on signal propagation can be compensated more accurately, the error caused by the ionosphere can be reduced, and the accuracy of the subsequent ionospheric random model can be improved. A more accurate ionospheric random model means that the influence of the ionosphere on the signal propagation path from the satellite to the receiver can be more accurately estimated and compensated, thereby improving the timing and positioning accuracy.

[0075] It is understandable that Figure 3 As shown, in step S2, the process of calculating the coordinates of the ionospheric puncture point includes the following:

[0076] Step S21b: Obtaining the geographic coordinates of the receiver;

[0077] Step S22b: Calculate the azimuth and altitude angles based on the positions of the receiver and the satellite;

[0078] Step S23b: Calculate the geographic coordinates of the ionospheric puncture point based on the geographic coordinates, azimuth, and altitude of the receiver. The calculation formula is:

[0079]

[0080] Specifically, the position of the receiver is obtained from the observation data of the receiver, including the geographic latitude coordinates and the geographic longitude coordinates, and then the azimuth angle Az and the altitude angle El are calculated according to the positions of the receiver and the satellite. The position of the satellite can be obtained through the ephemeris data provided by the satellite navigation system. The calculation formulas of the azimuth angle and the altitude angle belong to the existing technology and will not be repeated here. Then determine the reference height h of the ionosphere IPP , usually 350 km or 400 km is used, and the geographical coordinates of the ionospheric puncture point are calculated based on the following formula:

[0081]

[0082] R′=R E +h

[0083] h=h IPP -h receiver

[0084] Among them, φ IPP ,λ IPP denote the latitude and longitude coordinates of the ionospheric puncture point, φ r ,λ r They represent the latitude and longitude coordinates of the receiver, s represents the distance from the receiver to the puncture point, R′ represents the distance from the puncture point to the center of the earth, El represents the altitude angle, RE represents the radius of the earth, h represents the ionosphere height, hIPP represents the reference height of the ionosphere, and h receiver Indicates the receiver altitude.

[0085] It can be understood that in step S2, after the corrected ionospheric slant delay and the geographical coordinates of the ionospheric puncture point are calculated, the vertical ionospheric delay corresponding to the puncture point can be obtained in combination with the ionospheric projection function, and used as the vertical ionospheric delay reference value. The specific calculation formula is:

[0086]

[0087] Among them, I pv represents the vertical ionospheric delay corresponding to the puncture point.

[0088] It can be understood that in step S3, the satellite-based ionospheric grid correction number is first obtained, and then the vertical ionospheric delay observation value of the reference point is interpolated using the Kriging algorithm according to the position of the receiver. The specific interpolation process belongs to the existing technology and will not be repeated here. That is, the vertical ionospheric delay observation value of the reference point is obtained by the observation value random model constructed in step S1. Among them, the reference point refers to the specific position point obtained by interpolation through the Kriging algorithm, and its vertical ionospheric delay observation value is obtained by interpolation, and the vertical ionospheric delay reference value is the vertical ionospheric delay reference value corresponding to the puncture point obtained in step S2. Assume that the vertical ionospheric delay observation value of the i-th reference point obtained by interpolation is I pv,bos,i The vertical ionospheric delay reference value of the i-th reference point calculated in step S2 is I pv,ref,i , then the difference between the vertical ionospheric delay observation value and the vertical ionospheric delay reference value at the i-th reference point is: ΔI pv,i =I pv,ref,i -I pv,obs,i Then select multiple reference points at different latitudes on the same longitude and multiple reference points at different longitudes on the same latitude to calculate the average and standard deviation of the difference. The calculation formula is: Where N represents the number of reference points at different latitudes on the same longitude or the number of reference points at different longitudes on the same latitude. represents the mean value, σpv Represents the standard deviation, so that the distribution of this difference at different latitudes and longitudes can be analyzed, and thus an ionospheric random model that integrates time, latitude, and longitude can be established. For example, the distribution of vertical ionospheric delay differences at different latitudes and longitudes can be analyzed, and ionospheric activity patterns can be identified. The statistical analysis results are used to define the parameters of the ionospheric random model, such as the mean and variance. The specific process belongs to the existing technology and will not be repeated here. Among them, the ionospheric random model can predict the ionospheric delay at different times and different geographical locations, and thus dynamically adjust the compensation of the GNSS equipment through the ionospheric delay predicted by the model to reduce the impact of the ionospheric effect on the signal, thereby improving positioning accuracy and timing accuracy.

[0089] It can be understood that the present invention first constructs an observation value random model based on the approximate coordinates of the receiver and its vertical ionospheric delay data, and predicts the vertical ionospheric delay data of an unknown position from known data points. A continuous vertical ionospheric delay field can be constructed for the entire receiving area, so that the vertical ionospheric delay observation value of any position point can be accurately obtained, and then the vertical ionospheric delay reference value is corrected by calculating the satellite-side differential code deviation value, and then the vertical ionospheric delay observation value of the reference point is accurately predicted by the observation value random model, and the ionospheric random model is constructed based on the difference between the observation value and the reference value, which greatly improves the accuracy of the ionospheric random model, thereby improving the prediction accuracy of the vertical ionospheric delay, and can accurately predict the vertical ionospheric delay at any time and any position, thereby improving the positioning and timing accuracy.

[0090] In addition, a geographic information system or other spatial analysis tools can be used to map the distribution of the above differences to geographic coordinates to obtain a difference distribution map, so as to quickly determine the latitude or longitude range with the largest average difference value and analyze whether there is an obvious trend. For example, the ionospheric characteristics of different geographical locations (latitude and longitude) may vary significantly. The ionospheric activity near the equator is more complicated due to the equatorial ionospheric anomaly (EIA) phenomenon, while the polar regions are greatly affected by geomagnetic activity.

[0091] It is understood that in step S3, due to the large number of reference stations, in order to ensure the accuracy of the ionospheric data, some reference stations need to be screened for satellite-based ionospheric solution. Specifically, the geographical distribution of all reference stations is first evaluated. Then, the ionospheric effect of each reference station is analyzed using historical data. The reference stations that show the most obvious ionospheric effect are selected. The average ionospheric delay and rate of change of each station are then calculated to analyze the data quality of each reference station. The reference station locations are selected based on the principle of ensuring that the selected reference stations are evenly distributed in space and can provide stable, high-quality ionospheric data for the entire region.

[0092] It can be understood that in step S4, the reference frames of the satellite-based PPP orbit correction and the IGS post-precision orbit product are first unified based on the following formula: IGS =r PPP +t+R×r PPP +s×r PPP , where r PPP represents the original PPP orbital coordinates, r IGS represents the transformed PPP orbital coordinates, t represents the translation vector, R represents the rotation matrix, and s represents the scale factor. Then, the satellite-based PPP clock error accuracy is calculated based on the following formula:

[0093] ΔC=(C SBAS -C IGS1 )-(C IGS2 -C IGS1 )

[0094] Where ΔC represents the satellite-based PPP clock error accuracy, C SBAS represents the satellite-based PPP clock error, C IGS1 and C IGS2 Represent the clock differences of two different IGS products.

[0095] It can be understood that the present invention eliminates the problem of inconsistent references between precise clock errors by using a quadratic difference method, and can accurately calculate the satellite-based PPP clock error accuracy, thereby improving the accuracy of the precise ephemeris random model.

[0096] Next, the original signal, i.e., a time series of data, is generated based on the ionospheric stochastic model, and wavelet analysis is used to reconstruct the signal. Specifically, a wavelet basis function is first selected that matches the data characteristics. Data characteristics primarily refer to features such as patterns, trends, periodic changes, and mutation points. Different wavelet basis functions have different sensitivities and abilities to capture local signal features. Correctly selecting a wavelet basis function can improve the ability to detect these features, leading to more accurate signal analysis and reconstruction. For example, if the signal is relatively smooth, a smoother wavelet basis function, such as the Daubechies wavelet, can be selected. If the signal contains mutations or sharp features, a wavelet with a shorter support length, such as the Haar wavelet, can be selected. If the signal contains multiple frequency components, a wavelet basis with multi-resolution analysis capabilities, such as Symlets or Coiflets, can be selected. If it is necessary to accurately capture signals with edges or mutation points, a wavelet basis function with better time localization properties, such as the Mexican hat wavelet or the Morlet wavelet, can be selected. Next, the time series data is subjected to wavelet decomposition to obtain detail coefficients and approximation coefficients at various scales. Approximation coefficients describe the low-frequency portion of the signal, while detail coefficients describe the high-frequency portion. By observing the results of the wavelet decomposition, scales or frequencies with significant energy can be identified. For example, by analyzing detail coefficients at different levels, periodic components or specific frequencies in the signal can be identified. The wavelet coefficients are then used to reconstruct the signal, and deviations are calculated between the reconstructed and original signals to quantify the strength and range of periodic deviations. The strength of periodic deviations can be quantified by analyzing the energy of detail coefficients at specific scales. In wavelet analysis, the energy at a scale level can be calculated as the sum of the squares of the detail coefficients, which can be considered the importance or strength of that frequency component in the signal. The range of the deviations can be determined by analyzing the affected frequency bandwidth and temporal persistence. In wavelet analysis, each scale corresponds to a specific frequency range. By identifying scales with significant energy, the affected frequency range in the signal can be determined. Furthermore, by observing the temporal evolution of these frequency components, the temporal range of the deviations can be assessed.

[0097] Finally, the precise ephemeris random model is constructed based on the following formula:

[0098] C random (t) = C SBAS -ΔC+E d

[0099] Among them, C random (t) represents the precise ephemeris random model, E d =∫d(t) 2 dt, d(t) represents the difference signal between the reconstructed signal and the original signal, E dRepresents the energy obtained by integrating the difference signals.

[0100] It can be understood that the precise ephemeris random model of the present invention eliminates the problem of inconsistent clock references by means of quadratic difference calculation, reduces the error caused by hardware deviation, and significantly improves timing and positioning accuracy.

[0101] It can be understood that in step S5, the process of fusing the observation value random model, the ionosphere random model and the precise ephemeris random model and performing PPP solution includes the following:

[0102] Constructing the state matrix Among them, X obs 、X iono and X orbit They represent the state vectors of the observation random model, ionosphere random model and precise ephemeris random model respectively;

[0103] Constructing the state transition matrix Among them, F obs 、F iono and F orbit Represent the state transition submatrices of the observation random model, ionosphere random model and precise ephemeris random model respectively;

[0104] Construct the observation matrix H = [H obs H iono H orbit ], where H obs 、H iono and H orbit Represent the observation sub-matrices of the observation value random model, ionosphere random model and precise ephemeris random model respectively;

[0105] The extended Kalman filter algorithm is used to solve the PPP, wherein the extended Kalman filter algorithm is an existing algorithm, and the specific solution process belongs to the existing technology and will not be described in detail here.

[0106] In addition, if Figure 4 As shown, another embodiment of the present invention further provides a Beidou satellite-based real-time rapid timing system integrating multiple factors, preferably using the above-mentioned method, including:

[0107] The observation value random model construction module is used to use a receiver that supports both Beidou SBAS signals and PPP-B2b signals to obtain pseudorange observations on two frequencies to calculate the vertical ionospheric delay at the receiver. The Kriging algorithm is then used to interpolate the receiver's position to obtain a continuous observation value random model for each receiver coverage area.

[0108] The vertical ionospheric delay correction module is used to calculate the satellite-side differential code bias and use it to correct the ionospheric slant delay. It solves the coordinates of the ionospheric puncture point and combines it with the ionospheric projection function to obtain the vertical ionospheric delay corresponding to the puncture point, and uses it as the vertical ionospheric delay reference value.

[0109] The ionospheric random model construction module is used to obtain the vertical ionospheric delay observation value of the reference point based on the observation value random model, calculate the difference between the vertical ionospheric delay observation value of the reference point and the vertical ionospheric delay reference value, and analyze the distribution of the difference at different latitudes and longitudes to establish an ionospheric random model that integrates time, latitude, and longitude;

[0110] The precise ephemeris random model construction module is used to unify the reference frame of the satellite-based PPP orbit correction and the IGS post-precision orbit product to calculate the satellite-based PPP clock error accuracy. The original signal is generated based on the ionospheric random model and the signal is reconstructed using the wavelet analysis method. The precise ephemeris random model is then constructed based on the satellite-based PPP clock error, satellite-based PPP clock error accuracy, original signal and reconstructed signal.

[0111] The model fusion and PPP solution module is used to fuse the observation value random model, ionosphere random model and precise ephemeris random model and perform PPP solution.

[0112] It can be understood that the multi-factor fusion Beidou satellite-based real-time rapid timing system of this embodiment first constructs an observation value random model based on the approximate coordinates of the receiver and its vertical ionospheric delay data. The vertical ionospheric delay data at an unknown location is predicted from known data points. This allows a continuous vertical ionospheric delay field to be constructed for the entire receiving area, thereby accurately obtaining the vertical ionospheric delay observation value at any location. The vertical ionospheric delay at the puncture point is then corrected by calculating the satellite-side differential code deviation value, more accurately compensating for the impact of the ionosphere on signal propagation. The corrected vertical ionospheric delay at the puncture point is then used as a reference value, and the ionospheric random model is constructed based on the observed value and reference value of the vertical ionospheric delay at the reference point. This greatly improves the accuracy of the ionospheric random model and can more accurately predict the vertical ionospheric delay at any time and any location, thereby improving positioning and timing accuracy. In addition, the precise ephemeris random model eliminates the problem of inconsistent clock references through a secondary difference method, reducing errors caused by hardware bias and further improving timing and positioning accuracy. Therefore, the present invention integrates the observation value random model, the ionosphere random model and the precise ephemeris random model, and uses the Kalman filter technology to dynamically adjust the state vector and weight of each model, so that accurate timing and positioning can be performed under various environmental conditions with better robustness.

[0113] In addition, another embodiment of the present invention further provides an electronic device, including a processor and a memory, wherein the memory stores a computer program, and the processor is configured to execute the steps of the above method by calling the computer program stored in the memory.

[0114] In addition, another embodiment of the present invention further provides a computer-readable storage medium for storing a computer program for performing Beidou satellite-based real-time rapid timing with multi-factor fusion, wherein the computer program executes the steps of the method described above when running on a computer.

[0115] Common computer-readable storage media include: floppy disks, flexible disks, hard disks, magnetic tape, any other magnetic media, CD-ROMs, any other optical media, punch cards, paper tape, any other physical medium with a pattern of holes, random access memory (RAM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), flash-erasable programmable read-only memory (FLASH-EPROM), any other memory chip or cartridge, or any other medium that can be read by a computer. Instructions can further be transmitted or received via a transmission medium. The term transmission medium may include any tangible or intangible medium that can be used to store, encode, or carry instructions for execution by a machine, and includes digital or analog communication signals or other intangible media that facilitate communication of such instructions. Transmission media include coaxial cables, copper wire, and fiber optics, including the wires of a bus used to transmit a computer data signal.

[0116] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code. The scheme in the embodiment of the present application can be implemented in various computer languages, for example, object-oriented programming language Java and literal translation scripting language JavaScript, etc.

[0117] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the steps in the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0118] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0119] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 The steps for the function specified in one or more boxes.

[0120] Although the preferred embodiments of the present application have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present application.

[0121] Obviously, those skilled in the art may make various changes and modifications to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is intended to include these modifications and variations.

[0122] The foregoing description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Those skilled in the art will readily appreciate that various modifications and variations of the present invention are possible. Any modifications, equivalent substitutions, or improvements made within the principles of the present invention are intended to be within the scope of protection of the present invention.

Claims

1. A multi-factor integrated Beidou satellite-based real-time rapid timing method, characterized in that: Includes the following: Using a receiver that supports both BeiDou SBAS and PPP-B2b signals, pseudorange observations on two frequencies are obtained to calculate the vertical ionospheric delay at the receiver. Combined with the receiver's position, the Kriging algorithm is used to interpolate the continuous observation values ​​of each receiver's coverage area to obtain a random model. Calculate the satellite-side differential code bias and use it to correct the ionospheric slant delay. Calculate the coordinates of the ionospheric puncture point and combine it with the ionospheric projection function to obtain the vertical ionospheric delay corresponding to the puncture point, which is used as the reference value of the vertical ionospheric delay. Based on the observation value random model, the vertical ionospheric delay observation value of the reference point is obtained, the difference between the vertical ionospheric delay observation value of the reference point and the vertical ionospheric delay reference value is calculated, and the distribution of the difference at different latitudes and longitudes is analyzed to establish the ionospheric random model that integrates time, latitude and longitude; The satellite-based PPP clock error accuracy is calculated by unifying the reference frame of the satellite-based PPP orbit correction and the IGS post-precision orbit product. The original signal is generated based on the ionospheric random model and the signal is reconstructed using the wavelet analysis method. The precise ephemeris random model is then constructed based on the satellite-based PPP clock error, satellite-based PPP clock error accuracy, the original signal, and the reconstructed signal. The observation random model, ionosphere random model and precise ephemeris random model are integrated and PPP solution is performed; The process of fusing the observation value random model, the ionosphere random model and the precise ephemeris random model and performing PPP solution includes the following: Constructing the state matrix ,in, 、 and They represent the state vectors of the observation random model, ionosphere random model and precise ephemeris random model respectively; Constructing the state transition matrix ,in, 、 and Represent the state transition submatrices of the observation random model, ionosphere random model and precise ephemeris random model respectively; Constructing the observation matrix ,in, 、 and Represent the observation sub-matrices of the observation value random model, ionosphere random model and precise ephemeris random model respectively; The extended Kalman filter algorithm is used to solve PPP.

2. The Beidou satellite-based real-time rapid timing method based on multi-factor fusion as claimed in claim 1, characterized in that: The process of calculating the satellite-side differential code bias and correcting the ionospheric slant delay using the satellite-side differential code bias includes the following: Obtain the receiver-side differential code deviation value of each satellite; Calculate the ionospheric slant delay in the L1 band; The satellite-side differential code deviation value is calculated based on the receiver-side differential code deviation value and the ionospheric slant delay of the L1 band; The satellite-side differential code deviation value is used to correct the ionospheric slant delay in the L1 frequency band to obtain the corrected ionospheric slant delay.

3. The Beidou satellite-based real-time rapid timing method based on multi-factor fusion as claimed in claim 2, characterized in that: The satellite differential code deviation value is calculated based on the following formula: ； in, Indicates the satellite differential code deviation value, represents the differential code deviation value at the receiver end, c represents the speed of light, Indicates the ionospheric slant delay in the L1 band.

4. The Beidou satellite-based real-time rapid timing method based on multi-factor fusion as claimed in claim 1, characterized in that: The process of calculating the coordinates of the ionospheric piercing point includes the following: Get the geographic coordinates of the receiver; The azimuth and altitude angles are calculated based on the positions of the receiver and the satellite; The geographic coordinates of the ionospheric puncture point are calculated based on the geographic coordinates, azimuth, and altitude of the receiver. The calculation formula is: ； in, 、 represent the latitude and longitude coordinates of the ionospheric puncture point, respectively. 、 They represent the latitude and longitude coordinates of the receiver respectively, s represents the distance from the receiver to the puncture point, represents the distance from the puncture point to the center of the earth, El represents the altitude angle, and R E represents the radius of the earth, h represents the height of the ionosphere, h IPP represents the reference altitude of the ionosphere, Indicates the receiver altitude.

5. The Beidou satellite-based real-time rapid timing method based on multi-factor fusion as claimed in claim 1, characterized in that: The satellite-based PPP clock error accuracy is calculated based on the following formula: ； in, Indicates the satellite-based PPP clock error accuracy, represents the satellite-based PPP clock error, and Represent the clock differences of two different IGS products.

6. The Beidou satellite-based real-time rapid timing method based on multi-factor fusion as claimed in claim 5, characterized in that: The expression of the precise ephemeris random model is: ； in, represents the precise ephemeris random model, , represents the difference signal between the reconstructed signal and the original signal, Represents the energy obtained by integrating the difference signals.

7. A multi-factor integrated Beidou satellite-based real-time rapid timing system, using the method according to any one of claims 1 to 6, characterized in that: include: The observation value random model construction module is used to use a receiver that supports both Beidou SBAS signals and PPP-B2b signals to obtain pseudorange observations on two frequencies to calculate the vertical ionospheric delay at the receiver. The Kriging algorithm is then used to interpolate the receiver's position to obtain a continuous observation value random model for each receiver coverage area. The vertical ionospheric delay correction module is used to calculate the satellite-side differential code bias and use it to correct the ionospheric slant delay. It solves the coordinates of the ionospheric puncture point and combines it with the ionospheric projection function to obtain the vertical ionospheric delay corresponding to the puncture point, and uses it as the vertical ionospheric delay reference value. The ionospheric random model construction module is used to obtain the vertical ionospheric delay observation value of the reference point based on the observation value random model, calculate the difference between the vertical ionospheric delay observation value of the reference point and the vertical ionospheric delay reference value, and analyze the distribution of the difference at different latitudes and longitudes to establish an ionospheric random model that integrates time, latitude, and longitude; The precise ephemeris random model construction module is used to unify the reference frame of the satellite-based PPP orbit correction and the IGS post-precision orbit product to calculate the satellite-based PPP clock error accuracy. The original signal is generated based on the ionospheric random model and the signal is reconstructed using the wavelet analysis method. The precise ephemeris random model is then constructed based on the satellite-based PPP clock error, satellite-based PPP clock error accuracy, original signal and reconstructed signal. The model fusion and PPP solution module is used to fuse the observation value random model, ionosphere random model and precise ephemeris random model and perform PPP solution.

8. An electronic device, characterized in that: The method comprises a processor and a memory, wherein a computer program is stored in the memory, and the processor is configured to execute the steps of the method according to any one of claims 1 to 6 by calling the computer program stored in the memory.

9. A computer-readable storage medium for storing a computer program for performing multi-factor fusion Beidou satellite-based real-time rapid timing, characterized in that: When the computer program is run on a computer, the steps of the method according to any one of claims 1 to 6 are executed.

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