GNSS (Global Navigation Satellite System) high-frequency polar shift estimation method and application

Abstract

The invention discloses a GNSS high-frequency pole shift estimation method and application, and relates to the technical field of global navigation satellite systems, and the method comprises the steps: building a GNSS high-frequency pole shift estimation model based on ionosphere-free combination observation values, joint estimation pole shift parameters, satellite orbit parameters, observation station coordinates, troposphere delay, clock correction and ambiguity parameters; performing zero mean constraint on the polar shift reverse day frequency band component, and strongly constraining the amplitude of the reverse day frequency band component to be zero through a virtual observation equation; and superposing the zero-mean constraint equation into a normal equation, weakening the correlation between the polar shift parameter and the satellite orbit parameter, and completing high-frequency polar shift parameter estimation. The method can solve the problem that the polar movement cannot be estimated due to strong correlation between the polar movement in the weekly day and satellite orbit parameters.

Description

Technical Field

[0001] The present application relates to the technical field of global navigation satellite systems, and particularly to a GNSS high-frequency polar motion estimation method, device, electronic device, and computer-readable storage medium. Background Art

[0002] Polar tides are generated due to the movement of the Earth's poles relative to the inertial space. It is the elastic response of the Earth's crust to the deviation of the Earth's axis of rotation. The impact of polar tides on positioning can reach 2.5 cm vertically and 0.7 cm horizontally in deformation. Polar tide correction is usually calculated using the mean pole and the longitude and latitude of the station. The mean pole position is characterized by polar motion. Therefore, the accuracy of polar motion directly determines the accuracy of polar tide correction. Polar motion describes the displacement change of the poles, covering long-term changes of decades, fluctuations on the decadal scale, interannual and seasonal changes, as well as short-term changes of dozens of days, etc. Significant progress has been made in the research on the excitation of polar motion on short-term to interannual time scales and long-term changes. However, existing research has confirmed that polar motion also has high-frequency changes of diurnal and semi-diurnal periods. Approximately 60% of the high-frequency changes in polar motion are excited by ocean tides, mainly concentrated in the diurnal and semi-diurnal frequency bands, and the magnitude of their changes reaches 600 μas, which is equivalent to a pole displacement of 20 - 30 mm. Currently, the excitation mechanism of 30% of the high-frequency changes in polar motion has not been fully clarified, which is also one of the error sources that must be refined to achieve high-precision positioning.

[0003] GNSS (Global Navigation Satellite System) technology has comprehensive advantages such as high precision, global coverage of stations, all-weather observation, high observation repeatability, and high time resolution, and can obtain higher polar motion determination accuracy. The polar motion and polar motion rate accuracy with daily resolution determined by it can reach 30 μas and 150 μas / day respectively. The accurate determination of polar motion by GNSS technology is achieved by determining the transfer matrix between the Earth-fixed coordinate system and the inertial coordinate system. In GNSS data processing, polar motion and satellite orbit parameters in the inertial system are estimated simultaneously. In order to more accurately capture the time variation of polar motion in a shorter time, a polar motion product with higher time resolution is required. Theoretically, as the estimation interval shortens, the number of estimated polar motion parameters increases exponentially, and the correlation between parameters also increases. Existing research has found that when the polar motion parameter estimation interval is consistent with the GNSS data processing interval, the polar motion parameters are completely correlated with the orbit parameters, resulting in the inability to estimate polar motion. Therefore, adding a constraint equation for polar motion parameters to the observation equation to solve the problem of non-estimable high-frequency polar motion is of great significance for improving the accuracy of polar tide correction and positioning accuracy. Summary of the Invention

[0004] To overcome the defects of the above-mentioned prior art, an embodiment of the present invention provides a GNSS high-frequency polar motion estimation method and application, which can solve the problem that the polar motion within a day is strongly correlated with satellite orbit parameters, resulting in the inestimability of polar motion.

[0005] On the one hand, an embodiment of the present invention proposes a GNSS high-frequency polar motion estimation method, including: based on the ionosphere-free combination observations, jointly estimating the polar motion parameters, satellite orbit parameters, station coordinates, tropospheric delay, clock bias and ambiguity parameters to construct a GNSS high-frequency polar motion estimation model; performing a zero-mean constraint on the reverse solar-day frequency band component of the polar motion, and strongly constraining the amplitude of the reverse solar-day frequency band component to zero through a virtual observation equation; superimposing the zero-mean constraint equation into the normal equation to weaken the correlation between the polar motion parameters and the satellite orbit parameters, and completing the estimation of the high-frequency polar motion parameters.

[0006] In an embodiment of the present invention, the implementation manner of the zero-mean constraint includes: expanding the trigonometric function model of the reverse solar-day frequency band component of the polar motion into a linear observation equation, constructing a virtual observation equation through least squares estimation, and forcing the estimated value of its amplitude parameter to be zero.

[0007] In an embodiment of the present invention, the construction of the virtual observation equation is specifically as follows: Let the amplitude of the reverse solar-day frequency band component of the polar motion be A r , and the phase be Based on the observation sequence, construct the design matrix v = Ax - l, and realize the zero-mean constraint of the amplitude through the formula , where v is the residual, l = [x1, y1, x2, y2, …, x n , y n .

[0008] In an embodiment of the present invention, the construction manner of the ionosphere-free combination observations is: using dual-frequency pseudorange and phase observations, eliminating the influence of ionospheric delay through linear combination, and the specific formula is: Where and are the pseudorange and phase observations from the receiver r to the satellite s at the frequency f, in meters; is the satellite-ground geometric distance, including satellite coordinates, station coordinates and polar motion parameters; t r and t s are the receiver clock bias and satellite clock bias in meters respectively; is the tropospheric wet delay projection function; Z r is the tropospheric zenith delay; is the ionospheric delay related to the frequency f; d r,f and b r,f are the pseudorange and phase hardware delays at the receiver end respectively; d s,fand b s,f are the pseudorange and phase hardware delays at the satellite side, respectively; is the integer cycle ambiguity; λ f is the wavelength of the frequency f; ∈ P and ∈ Φ represent the residual errors of the pseudorange phase observation.

[0009] In an embodiment of the present invention, the retrograde diurnal frequency band component of the polar motion is associated with the nutation parameter and is initially constrained by a nutation prior model, and then a zero-mean constraint is superimposed to further weaken the correlation.

[0010] In an embodiment of the present invention, the construction method of the normal equation is specifically as follows: superimpose the linearized observation equations and introduce a zero-mean constraint equation to form an extended normal equation: B T PBx = B T Pl; where B is the design matrix and P is the weight matrix of the observed values.

[0011] On the other hand, an embodiment of the present invention also proposes a GNSS high-frequency polar motion estimation device, including: a GNSS high-frequency polar motion estimation model construction module, configured to jointly estimate polar motion parameters, satellite orbit parameters, station coordinates, tropospheric delay, clock error, and ambiguity parameters based on ionosphere-free combined observations to construct a GNSS high-frequency polar motion estimation model; a zero-mean constraint module, configured to perform zero-mean constraint on the retrograde diurnal frequency band component of the polar motion and strongly constrain the amplitude of the retrograde diurnal frequency band component to zero through a virtual observation equation; a high-frequency polar motion parameter estimation module, configured to superimpose the zero-mean constraint equation into the normal equation to weaken the correlation between the polar motion parameters and the satellite orbit parameters and complete the high-frequency polar motion parameter estimation.

[0012] On yet another aspect, an embodiment of the present invention also proposes an electronic device, including: a memory and one or more processors connected to the memory, the memory storing a computer program, and the processor being configured to execute the computer program to implement the GNSS high-frequency polar motion estimation method as described in any one of the above embodiments.

[0013] On still another aspect, an embodiment of the present invention also proposes a computer-readable storage medium, the computer-readable storage medium storing computer-executable instructions, and the computer-executable instructions being configured to execute the GNSS high-frequency polar motion estimation method as described in any one of the above embodiments.

[0014] As can be seen from the above, compared with the prior art, the above embodiments of the present invention can at least have one or more of the following beneficial effects:

[0015] The GNSS high-frequency polar motion estimation method proposed in the embodiments of the present invention addresses the problem of strong correlation between polar motion within a day and satellite orbit parameters. By using the inverse daily frequency band polar motion zero-mean constraint method, after the inverse daily frequency band polar motion is constrained to zero, the correlations between polar motion, satellite orbit parameters, and polar motion parameters are significantly weakened, enabling the 5-minute equally spaced estimation of high-frequency polar motion and GNSS orbit determination network solutions. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The drawings described herein are used to provide a further understanding of the present invention and form a part of the present invention. The illustrative embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0017] Figure 1 is a flowchart of a GNSS high-frequency polar motion estimation method provided by an embodiment of the present invention;

[0018] Figure 2 is a schematic diagram of the correlation with orbit parameters at a 5-minute estimation interval provided by an embodiment of the present invention;

[0019] Figure 3 is a schematic structural diagram of a GNSS high-frequency polar motion estimation device provided by an embodiment of the present invention;

[0020] Figure 4 is a schematic structural diagram of an electronic device provided by an embodiment of the present invention;

[0021] Figure 5 is a schematic structural diagram of a computer-readable storage medium provided by an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0022] It should be noted that, without conflict, the embodiments in the present invention and the features in the embodiments may be combined with each other. The present invention will be described below with reference to the drawings and in conjunction with the embodiments.

[0023] In order to enable those of ordinary skill in the art to better understand the technical solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments, and all should fall within the protection scope of the present invention.

[0024] It should be noted that the terms "first", "second", etc. in the description, claims and above-mentioned drawings of the present invention are used to distinguish similar objects and do not necessarily describe a specific order or sequence. It should be understood that such terms can be interchanged under appropriate circumstances so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device comprising a series of steps or units does not necessarily limit to those clearly listed steps or units, but may include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0025] It should also be noted that the division of multiple embodiments in the present invention is only for the convenience of description and should not constitute a special limitation. The features in various embodiments can be combined and cross-referenced without contradiction.

[0026] As Figure 1 shown, the first embodiment of the present invention proposes a GNSS high-frequency polar motion estimation method, for example, including: Step S1, based on the ionosphere-free combination observations, jointly estimate the polar motion parameters, satellite orbit parameters, station coordinates, tropospheric delay, clock offset and ambiguity parameters to construct a GNSS high-frequency polar motion estimation model; Step S2, perform a zero-mean constraint on the retrograde daily frequency band component of the polar motion, and strongly constrain the amplitude of the retrograde daily frequency band component to zero through a virtual observation equation; Step S3, superimpose the zero-mean constraint equation into the normal equation to weaken the correlation between the polar motion parameters and the satellite orbit parameters, and complete the high-frequency polar motion parameter estimation.

[0027] Specifically, in Step S1, the precise determination of the polar motion by GNSS technology is achieved by determining the transformation matrix between the Earth-fixed system and the inertial system. The reference point coordinates in the Earth-fixed system are determined by ground stations, while the satellite coordinates in the inertial system are determined by the satellite dynamic orbit. In order to precisely observe the polar motion, it is usually necessary to perform network solution processing on the observations of a large-scale GNSS station network, and jointly estimate the polar motion, satellite orbit, clock offset and tropospheric and other parameters.

[0028] The GNSS pseudorange and phase undifferenced observation equations can be described as:

[0029]

[0030] In the above formula, and are respectively the pseudorange and phase observations from the receiver r to the satellite s at the frequency f, with the unit of meter; is the satellite-to-ground geometric distance, including satellite coordinates, station coordinates and polar motion parameters; t r and t sare the receiver clock error and satellite clock error in meters, respectively; is the tropospheric wet delay projection function; Z r is the tropospheric zenith delay; is the ionospheric delay related to frequency f; d r,f and b r,f are the pseudorange and phase hardware delays at the receiver end, respectively; d s,f and b s,f are the pseudorange and phase hardware delays at the satellite end, respectively; is the integer cycle ambiguity; λ f is the wavelength of frequency f; ∈ P and ∈ Φ represent the pseudorange-phase observation residual error. In the observation equation, the effects of dry delay of tropospheric delay, phase wrapping, relativistic effect, phase center deviation and variation, and tidal displacements such as solid tide and ocean tide are corrected by accurate models, and the residual error after correction can be ignored.

[0031] Furthermore, in order to weaken the influence of ionospheric delay on GNSS observations, this scheme uses ionosphere-free combined observations to perform GNSS high-frequency ERP solution, f m and f n The ionosphere-free combined observations of the pseudorange-phase observations at frequencies are as follows:

[0032]

[0033] Writing Equation (1) in ionosphere-free combined form gives:

[0034]

[0035] The symbol definitions in Equation (3) are the same as those in Equation (1). The parameters to be estimated in Equation (3) include satellite orbit parameters, station coordinates, polar motion, troposphere, satellite clock error, receiver clock error, and ambiguity parameters. Among them, the hardware delay biases d s,IF and d r,IF are absorbed by the receiver clock error, and the phase delay biases b R,IF and b s,IF are absorbed by the ambiguity parameters.

[0036] Furthermore, linearize the GNSS observation equation of Equation (3). Let the reference orbit coordinates X in the inertial system s,0 =(x s,0 , y s,0 , z s,0 ), and the initial coordinates X of the station in the inertial system r,0 =R ERP0 (x r,0 , y r,0 , z r,0), the initial value X of the polar motion parameters ERP,0 , expand Equation (3) at the parameter initial value, and ignore the high-order terms above the second order to obtain the ionosphere-free combined pseudorange and phase error observation equations after linearization:

[0037]

[0038] In the above formula, V pc and V lc are the pseudorange and phase observation residuals respectively; l pc and l lc are the OMC (Observation Minus Computed) of the pseudorange and phase observations; m trop is the tropospheric wet component projection function; X = [dX r dX s X erp X trop t r t s N] T is the parameter to be estimated.

[0039] Furthermore, let the observation residual i at time t OMC be The satellite orbit parameter vector to be estimated is dX s (t i ) = φ(t, t0)x0, where x0 is the initial point orbit and φ(t, t0) is the satellite orbit state transition matrix. The parameter vector to be estimated is X i = [dX r (t i ) x0 X erp (t i ) X trop (t i ) t r (t i ) t s (t i ) N(t i )] T , and the corresponding design matrix Then the linearized observation equation at epoch t i can be written according to Equation (4) as:

[0040] v i = B i X i - l i (5)

[0041] From t1 to t nAfter the observation equations at each moment in the time period are superimposed, the normal equation is constructed:

[0042] B T PBx = B T Pl (6)

[0043] In the formula, P is the weight matrix of the observed values; after solving the normal equation according to the least squares criterion, the estimated value of the parameter can be calculated by the following formula:

[0044] x = (B T PB) -1 B T Pl (7)

[0045] After constructing the observation equation and the normal equation according to the above formula, the polar motion solution can be carried out.

[0046] In step S2, since the Earth rotation parameters are characterized by five angles instead of the necessary three angles to represent the transformation between the Earth-fixed reference frame and the celestial-fixed reference frame. Nutation and polar motion occur simultaneously and are intertwined in the Earth orientation and are artificially separated in the traditional parameterization. Nutation and polar motion are the same kind of motion observed from two different angles, so there is a problem of rank deficiency in parameter estimation. The retrograde diurnal frequency band component of polar motion can be expressed by nutation parameters:

[0047]

[0048] In the formula, θ is the Greenwich hour angle; ε0 is the mean obliquity of the ecliptic; x r and y r are the X and Y components of the retrograde diurnal frequency band of polar motion; Δψ and Δε are nutation parameters.

[0049] However, as shown in formula (9), the nutation parameters are strongly correlated with the right ascension of the ascending node Ω, the orbital inclination i, and the argument of latitude μ in the satellite orbit state.

[0050]

[0051] Therefore, due to the strong correlation between the orbital parameters and the nutation parameters, the GNSS technology cannot directly estimate nutation. When estimating the polar motion at the GNSS daily resolution, the retrograde diurnal frequency band component of polar motion is naturally filtered and no additional processing is required. However, when estimating the high-frequency polar motion (within a day) of GNSS, although the nutation parameters are not actually estimated, the retrograde diurnal frequency band component (actually nutation) in the polar motion parameters is strongly correlated with the orbital parameters. In this embodiment, a nutation prior model is first used to constrain the nutation term, and a zero-mean constraint algorithm is adopted for the high-frequency polar motion to strongly constrain the nutation term in the retrograde diurnal frequency band to 0. The retrograde component of polar motion can be expressed as:

[0052]

[0053] where ω is the angular velocity of the Earth's rotation; A r and represent the amplitude and phase of the retrograde diurnal frequency band term. For each set of polar motion sequences with t ∈ [t1…t n , after trigonometric expansion, the observation equation is obtained:

[0054]

[0055] Written in matrix form, it can be obtained:

[0056] v = Ax - l (12)

[0057] where v is the residual; l = [x1, y1, x2, y2, …, x n , y n ; A is the design matrix; Solved using the least squares estimate:

[0058] x = (ATA) -1 A T l (13)

[0059] In this embodiment, the amplitude of the retrograde diurnal frequency band component of polar motion is constrained to 0, that is, let x = 0. Also, because the A matrix is simply structured, The matrix form of the final virtual observation equation can be written as:

[0060]

[0061] In step S3, by adding the retrograde diurnal frequency band constraint of equation (14) to the normal equation (6), the nutation term in the high-frequency polar motion sequence can be constrained to 0, reducing the correlation between the high-frequency polar motion parameters and the orbit parameters.

[0062] Such as Figure 2The figure shows the correlation between the XPOLE of polar motion and satellite orbit parameters at a 5-minute estimation interval (equal to the GNSS processing interval). For clear visibility, only the correlation between the first three polar motion parameters and the orbit parameters of satellite G01 is plotted. In the figure, (1) represents that the nutation terms in the retrograde daily frequency band are not processed, and only the nutation model correction is used; (2) is to additionally use the zero-mean constraint method to constrain the retrograde daily nutation terms to 0. It can be seen that when the polar motion in the retrograde daily frequency band is not constrained, the position and velocity parameters of satellite G01 have a strong correlation with the polar motion. The correlation between the Y and Z directions of the satellite position and the polar motion is as high as 0.9, and the polar motion and satellite orbit parameters cannot be separated. At the same time, the polar motion parameters at different reference points are almost completely correlated, and in this case, the polar motion cannot be accurately estimated. However, when the polar motion in the retrograde daily frequency band is strongly constrained to 0, the correlation between the polar motion and satellite orbit parameters and between polar motion parameters is greatly weakened, and the correlation degree drops to 0.1. The estimation of polar motion parameters will no longer be limited by the processing interval.

[0063] In summary, a GNSS high-frequency polar motion estimation method proposed in the first embodiment of the present invention, aiming at the problem of strong correlation between the polar motion within a day and satellite orbit parameters, adopts the zero-mean constraint method for the polar motion in the retrograde daily frequency band. After the polar motion in the retrograde daily frequency band is constrained to zero, the correlation between the polar motion and satellite orbit parameters and between polar motion parameters is significantly weakened, and high-frequency polar motion and 5-minute equal-interval estimation of the GNSS orbit determination network solution can be realized.

[0064] In addition, as Figure 3 shown, the second embodiment of the present invention also proposes a GNSS high-frequency polar motion estimation device, including: an estimation model construction module 201, a zero-mean constraint module 202, and a high-frequency polar motion parameter estimation module 203.

[0065] Among them, the estimation model construction module 201 is used to jointly estimate polar motion parameters, satellite orbit parameters, station coordinates, tropospheric delay, clock error, and ambiguity parameters based on the ionosphere-free combined observations to construct a GNSS high-frequency polar motion estimation model; the zero-mean constraint module 202 is used to perform zero-mean constraint on the retrograde daily frequency band components of the polar motion, and strongly constrain the amplitude of the retrograde daily frequency band components to zero through virtual observation equations; the high-frequency polar motion parameter estimation module 203 is used to superimpose the zero-mean constraint equation into the normal equation to weaken the correlation between the polar motion parameters and satellite orbit parameters and complete the estimation of high-frequency polar motion parameters.

[0066] Furthermore, the zero-mean constraint module 202 includes: a nutation model correction unit, which is used to perform preliminary constraint on the retrograde daily frequency band components through the nutation prior model; a zero-mean realization unit, which is used to construct a virtual observation equation and force the amplitude parameter to be zero.

[0067] The GNSS high-frequency polar motion estimation method implemented by the parametric modeling device for the urban rail tunnel ventilation structure disclosed in the second embodiment of the present invention is as described in the foregoing first embodiment, so it will not be elaborated here. Optionally, each module in the second embodiment and the above other operations or functions are respectively for implementing the method described in the first embodiment, and the beneficial effects of the GNSS high-frequency polar motion estimation device provided in this embodiment are the same as those of the GNSS high-frequency polar motion estimation method provided in the foregoing first embodiment. For the sake of brevity, they will not be repeated here.

[0068] As Figure 4 shown, the third embodiment of the present invention further proposes an electronic device, for example, including: at least one processing unit and at least one storage unit, wherein the storage unit stores a computer program, and when the computer program is executed by the processing unit, the processing unit is caused to execute the method described in the first embodiment, and the beneficial effects of the electronic device provided in this embodiment are the same as those of the GNSS high-frequency polar motion estimation method provided in the first embodiment.

[0069] As Figure 5 shown, the fourth embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, and when the program is executed by a processor, the steps of the above method are implemented, and the beneficial effects of the computer-readable storage medium provided in this embodiment are the same as those of the GNSS high-frequency polar motion estimation method provided in the first embodiment.

[0070] Among them, the computer-readable storage medium may include, but is not limited to, any type of disk, including floppy disks, optical disks, DVDs, CD-ROMs, microdrives, and magneto-optical disks, ROMs, RAMs, EPROMs, EEPROMs, DRAMs, VRAMs, flash memory devices, magnetic or optical cards, nanosystems (including molecular memory ICs), or any type of medium or device suitable for storing instructions and / or data.

[0071] It should be noted that for the foregoing method embodiments, for the sake of simple description, they are all expressed as a series of action combinations. However, those skilled in the art should know that the present application is not limited by the described action sequence, because according to the present application, certain steps can be performed in other sequences or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily essential to the present application.

[0072] In the above embodiments, the descriptions of each embodiment have their own emphases. For the parts not detailed in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0073] In several embodiments provided by the present application, it should be understood that the disclosed device can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed coupling or direct coupling or communication connection between each other can be through some service interfaces. The indirect coupling or communication connection of the device or unit can be in an electrical or other form.

[0074] The units described as separate components may or may not be physically separated. The components displayed as units may or may not be physical units, that is, they can be located in one place, or they can be distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0075] In addition, in each embodiment of the present application, the functional units can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above-mentioned integrated units can be implemented in the form of hardware or in the form of software functional units.

[0076] If the above-mentioned integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on such an understanding, the technical solution of the present application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions to enable a computer device (which can be a personal computer, a server or a network device, etc.) to execute all or part of the steps of the methods described in each embodiment of the present application. And the aforementioned memory includes: USB flash drive, read-only memory (ROM), random access memory (RAM), mobile hard disk, magnetic disk or optical disc and other media that can store program codes.

[0077] Those of ordinary skill in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructing relevant hardware through a program. This program can be stored in a computer-readable memory. The memory can include: flash drive, read-only memory (ROM), random access memory (RAM), magnetic disk or optical disc, etc.

[0078] The above are only exemplary embodiments of the present disclosure, and the scope of the present disclosure cannot be limited thereby. That is, any equivalent changes and modifications made in accordance with the teachings of the present disclosure still fall within the scope covered by the present disclosure. Those skilled in the art will readily conceive of other embodiments of the present disclosure after considering the specification and practicing the disclosure herein. This application is intended to cover any variations, uses, or adaptations of the present disclosure that follow the general principles of the present disclosure and include known common general knowledge or conventional technical means in the technical field not described in the present disclosure. The specification and embodiments are only regarded as exemplary, and the scope and spirit of the present disclosure are defined by the claims.

[0079] The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity of description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope described in this specification.

[0080] It is easy for those skilled in the art to understand that the above are only preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A GNSS high frequency polar motion estimation method, characterized in that: include: Based on the ionosphere-free combined observations, the polar motion parameters, satellite orbit parameters, station coordinates, tropospheric delay, clock error and ambiguity parameters are jointly estimated to construct a GNSS high-frequency polar motion estimation model. A zero mean constraint is imposed on the reverse daily frequency band component of the polar motion, and the amplitude of the reverse daily frequency band component is strongly constrained to be zero through a virtual observation equation; The zero mean constraint equation is superimposed on the normal equation to weaken the correlation between the polar motion parameters and the satellite orbit parameters, thereby completing the estimation of high-frequency polar motion parameters.

2. The GNSS high frequency polar motion estimation method according to claim 1, characterized in that: The implementation of the zero mean constraint includes: The trigonometric function model of the reverse daily frequency component of the polar motion is expanded into a linear observation equation, and a virtual observation equation is constructed through least squares estimation, and the estimated value of its amplitude parameter is constrained to be zero.

3. The GNSS high frequency polar motion estimation method according to claim 1, characterized in that: The construction of the virtual observation equation is specifically as follows: Assume that the amplitude of the polar motion reverse daily frequency band component is A r , the phase is Based on the observation sequence, the design matrix v = Ax-l is constructed and the formula Implement the zero mean constraint of the amplitude, where v is the residual, l=[x1,y1,x2,y2,…,x n ,y n ].

4. The GNSS high frequency polar motion estimation method according to claim 1, characterized in that: The construction method of the ionosphere-free combined observation value is: The dual-frequency pseudorange and phase observation values ​​are used to eliminate the influence of ionospheric delay through linear combination. The specific formula is: in, and are the pseudorange and phase observation values ​​from receiver r to satellite s at frequency f, in meters; is the geometric distance between the satellite and the ground, including the satellite coordinates, station coordinates and polar motion parameters; t r and t s They are the receiver clock error and satellite clock error in meters respectively; is the tropospheric wet delay projection function; Z r is the tropospheric zenith delay; is the ionospheric delay associated with frequency f; d r,f and b r,f are the pseudorange and phase hardware delays at the receiver end; d s,f and b s,f are the pseudorange and phase hardware delays at the satellite end, respectively; is the integer-cycle ambiguity; f is the wavelength of frequency f; ∈ P and ∈ Φ Represents the residual error of pseudorange phase observation.

5. The GNSS high frequency polar motion estimation method according to claim 1, characterized in that: The reverse daily frequency component of the polar motion is associated with the nutation parameters and is initially constrained by the nutation prior model, and then a zero mean constraint is superimposed to further weaken the correlation.

6. The GNSS high frequency polar motion estimation method according to claim 1, characterized in that: The construction method of the normal equation is specifically as follows: The linearized observation equations are superimposed and the zero mean constraint equation is introduced to form the extended method equation: T PBx=B T Pl; where B is the design matrix and P is the observation weight matrix.

7. A GNSS high frequency polar motion estimation device, characterized in that: include: The estimation model building module is used to jointly estimate the polar motion parameters, satellite orbit parameters, station coordinates, tropospheric delay, clock error and ambiguity parameters based on the ionosphere-free combined observation values ​​to build a GNSS high-frequency polar motion estimation model; A zero mean constraint module is used to perform a zero mean constraint on the reverse daily frequency band component of the polar motion, and to strongly constrain the amplitude of the reverse daily frequency band component to zero through a virtual observation equation; The high-frequency polar motion parameter estimation module is used to superimpose the zero mean constraint equation into the normal equation, weaken the correlation between the polar motion parameter and the satellite orbit parameter, and complete the high-frequency polar motion parameter estimation.

8. The GNSS high frequency polar motion estimation device according to claim 7, characterized in that: The zero mean constraint module comprises: A nutation model correction unit is used to preliminarily constrain the inverse day-band component through a nutation prior model; Zero-mean implementation unit, used to construct virtual observation equations and force amplitude parameters to be zero.

9. An electronic device, characterized in that: include: A memory and one or more processors connected to the memory, the memory storing a computer program, and the processor being used to execute the computer program to implement the GNSS high-frequency polar shift estimation method as described in any one of claims 1-6.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable commands, and the computer-executable commands are used to execute the GNSS high-frequency polar shift estimation method as described in any one of claims 1-6.

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