GNSS (Global Navigation Satellite System) virtual observation value generation method and system based on real-time precise point positioning

Abstract

The invention provides a GNSS virtual observation value generation method and system based on real-time precise point positioning, and belongs to the technical field of GNSS positioning, and the method comprises the steps: obtaining ephemeris clock error data and observation data received by a reference station in real time, filling a UCUD PPP observation equation, and solving a non-difference floating point solution of a to-be-estimated parameter of each parameter station; through UPD estimation, non-difference floating point solution ambiguity parameters recover the whole cycle characteristic, and a fixed solution STEC and a fixed solution ZTD are obtained; the STEC is locally fitted into a function about the position, and a regional non-difference ionosphere model is established; the ZTD is locally fitted into a function about the position, and a regional non-difference troposphere model is established; and generating a double-difference atmospheric delay between the main reference station and the virtual reference station based on the non-difference ionosphere model and the regional non-difference troposphere model to obtain a virtual observation value. According to the method, the reliability of GNSS signal atmospheric delay is effectively improved, so that the quality of a virtual observation value is improved.

Description

Technical Field

[0001] The present invention relates to the field of GNSS positioning technology, and in particular to a method and system for generating GNSS virtual observation values ​​based on real-time precise single-point positioning. Background Art

[0002] GNSS virtual observations are the core product of network RTK positioning services. Network RTK users receive virtual observations and perform inter-station and inter-satellite differentials with local observations to eliminate the clock errors and hardware delay errors between the satellite and receiver ends, while significantly weakening the spatially correlated tropospheric and ionospheric delays, thereby obtaining centimeter-level high-precision baseline solutions.

[0003] The traditional virtual observation generation method is based on the double-difference network solution, which requires the construction of a receiver network based on certain topological rules, and the adjacent reference stations constitute the baseline. The CORS server uses a certain parameter estimation method to solve the inter-station and inter-satellite double-difference observation equations, fixes the double-difference ambiguity to an integer, and estimates the centimeter-level double-difference tropospheric and ionospheric delays. However, the double-difference model has the problem of relying on common-view satellites in the solution stage; in the troposphere / ionosphere modeling stage, modeling is often limited to small units, and it is difficult to fully utilize the characteristics of the continuous distribution of atmospheric error areas. The above characteristics of the double-difference network solution limit the accuracy of atmospheric error extraction and modeling. In addition, the parameters of the double-difference observation model are often not intuitive, which makes it difficult to expand or add external constraints. Summary of the invention

[0004] The present invention provides a GNSS virtual observation value generation method and system based on real-time precise single-point positioning, which is used to solve the technical problems of insufficient satellite utilization and difficulty in atmospheric error area modeling in the existing double-difference network solution method, effectively improve the reliability of GNSS signal atmospheric delay, and thus improve the quality of virtual observation values.

[0005] In a first aspect, the present invention provides a method for generating GNSS virtual observation values ​​based on real-time precise single-point positioning, comprising: obtaining ephemeris clock error data and observation data received in real time by a reference station, filling in UCUD PPP observation equations, and solving non-difference floating-point solutions of parameters to be estimated for each parameter station; wherein the parameters to be estimated include three-dimensional coordinates of the user station, re-parameterized receiver clock error, slant range ionospheric delay, zenith tropospheric delay ZTD, and re-parameterized phase floating-point ambiguity; through UPD estimation, the non-differenced floating-point solution ambiguity parameters are restored to integer characteristics to obtain a fixed solution STEC and a fixed solution ZTD; locally fitting STEC as a function of position to establish a regional non-differenced ionospheric model; and locally fitting ZTD as a function of position to establish a regional non-differenced tropospheric model; based on the non-differenced ionospheric model and the regional non-differenced tropospheric model, generating a double-differenced atmospheric delay between a main reference station and a virtual reference station to obtain a virtual observation value; wherein the main reference station is the reference station closest to the virtual reference station.

[0006] According to a GNSS virtual observation value generation method based on real-time precise single-point positioning provided by the present invention, a double-difference atmospheric delay between a main reference station and a virtual reference station is generated based on a non-differenced ionosphere model and a regional non-differenced troposphere model to obtain a virtual observation value, including: substituting the plane coordinates of the virtual reference station and the main reference station into the regional non-differenced ionosphere model and the regional non-differenced troposphere model respectively to generate a double-differenced atmospheric delay between the main reference station and the virtual reference station; wherein the double-differenced atmospheric delay includes a double-differenced ionospheric delay and a double-differenced tropospheric delay; performing geometric correction and atmospheric delay correction on the basis of the actual observation value of the main reference station to obtain the non-differenced phase and pseudo-range virtual observation values ​​of the virtual reference station for the common-view satellite; and a network RTK user makes a difference between the actual observation value and the virtual observation value to construct a double-differenced observation value.

[0007] According to a GNSS virtual observation value generation method based on real-time precise single point positioning provided by the present invention, the expression of the UCUD PPP observation equation is:

[0008]

[0009] In the formula, the superscript s represents the satellite number, the subscript r represents the receiver, and i represents the carrier phase frequency; and The pseudorange and phase observations minus the calculated value OMC, respectively; and x represent the unit vector from the receiver to the satellite and the three-dimensional coordinate parameters of the user station to be estimated respectively; is the re-parameterized receiver clock error; γ i is the ionospheric delay coefficient; is the slant range ionospheric delay; is the tropospheric projection function; T ris the zenith tropospheric delay ZTD; λ i is the carrier wavelength of frequency i; is the reparameterized phase float ambiguity; and They refer to the observation noise of pseudorange and phase respectively.

[0010] According to the GNSS virtual observation value generation method based on real-time precise single-point positioning provided by the present invention, the non-differenced floating-point solution ambiguity parameters are restored to integer characteristics through UPD estimation to obtain fixed solutions STEC and ZTD, including: converting the re-parameterized phase floating-point ambiguity into floating-point wide-lane ambiguity and ionospheric IF floating-point ambiguity; dividing into wide-lane and narrow-lane steps, based on the floating-point wide-lane ambiguity and ionospheric IF floating-point ambiguity, using the UPD network adjustment method to estimate the wide-lane UPD and narrow-lane UPD; respectively eliminating the UPD of the receiver and the satellite on the reference station through inter-satellite single difference and UPD correction; respectively obtaining the single-difference wide-lane ambiguity and the single-difference narrow-lane ambiguity through rounding and LAMBDA algorithm, and then restoring them to non-combined ambiguity, constraining and updating the floating-point solution parameter estimation results, and obtaining the fixed solution STEC and ZTD.

[0011] According to the GNSS virtual observation value generation method based on real-time precise single-point positioning provided by the present invention, the model parameters of the regional non-differenced ionosphere model and the regional non-differenced troposphere model are solved using a linear least squares method.

[0012] According to the GNSS virtual observation value generation method based on real-time precise single-point positioning provided by the present invention, the re-parameterized phase floating point ambiguity Convert to floating point wide lane blur and eliminate ionospheric IF float ambiguity Specifically include:

[0013]

[0014] Among them, the definition is the ionosphere-free combination coefficient.

[0015] In a second aspect, the present invention further provides a GNSS virtual observation value generation system based on real-time precise single-point positioning, comprising:

[0016] The non-difference floating-point solution calculation module is used to obtain the ephemeris clock error data and the observation data received in real time by the reference station, fill in the UCUD PPP observation equation, and solve the non-difference floating-point solution of the parameters to be estimated for each parameter station; the parameters to be estimated include the three-dimensional coordinates of the user station, the re-parameterized receiver clock error, the slant range ionospheric delay, the zenith tropospheric delay ZTD, and the re-parameterized phase floating-point ambiguity;

[0017] The fixed solution calculation module is used to restore the integer characteristics of the non-difference floating point solution ambiguity parameters through UPD estimation, and obtain the fixed solution STEC and the fixed solution ZTD;

[0018] A non-differenced atmospheric delay modeling module for locally fitting STEC as a function of position to establish a regional non-differenced ionosphere model; and locally fitting ZTD as a function of position to establish a regional non-differenced troposphere model;

[0019] The virtual observation value generation module is used to substitute the plane coordinates of the virtual reference station and the main reference station into the regional non-differenced ionosphere model and the regional non-differenced troposphere model respectively to generate the double-differenced atmospheric delay between the main reference station and the virtual reference station; perform geometric correction and atmospheric delay correction on the basis of the actual observation values ​​of the main reference station to obtain the non-differenced phase and pseudo-range virtual observation values ​​of the virtual reference station for the common-view satellite;

[0020] Among them, the main reference station is the reference station closest to the virtual reference station.

[0021] In a third aspect, the present invention provides an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the steps of a method for generating GNSS virtual observation values ​​based on real-time precise single-point positioning as described in any one of the above are implemented.

[0022] In a fourth aspect, the present invention further provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of a method for generating GNSS virtual observation values ​​based on real-time precise single-point positioning as described in any one of the above.

[0023] The method and system for generating GNSS virtual observation values ​​based on real-time precise single-point positioning provided by the present invention have the following beneficial effects compared with the prior art:

[0024] (1) The atmospheric error extraction stage of the present invention does not rely on common-view satellites, which can improve the utilization rate of multi-constellation satellite resources;

[0025] (2) The non-differential ionospheric and tropospheric parameters in the present invention are easier to implement regional modeling. The regional model can effectively utilize the consistency of atmospheric errors in the region compared to the intra-unit model, improve the model accuracy, and thus improve the quality of the final product virtual observation value;

[0026] (3) The scalability of the non-difference model in the present invention not only makes it easy to add various constraints to the server observation equations based on the actual situation of the survey area, but also provides RTK and PPP-RTK mode services through a single server solution, thereby improving the multi-mode work efficiency of the network RTK server. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0028] Figure 1 It is a flow chart of a method for generating GNSS virtual observation values ​​based on real-time precise single-point positioning provided by the present invention;

[0029] Figure 2 It is a structural schematic diagram of a GNSS virtual observation value generation system based on real-time precise single-point positioning provided by the present invention;

[0030] Figure 3 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0031] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0032] It should be noted that, in the description of the embodiments of the present invention, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "include one..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0033] The basic idea of ​​the present invention is to estimate the non-differenced GNSS state parameters based on the UCUD PPP observation model and real-time / predicted global precision products, extract the atmospheric delay affecting the GNSS signal, namely the slant path total electron content (STEC) and the zenith tropospheric delay (ZTD), and use the spatial autocorrelation of regional non-differenced STEC and ZTD to establish an atmospheric fitting model for the target position. A single model is used to predict the atmospheric delay of any point within the reference network (network RTK service), thereby solving the problem that it is difficult to perform regional modeling for atmospheric delay solution using the traditional double-difference network.

[0034] Aiming at the problem that the real-time UCUD PPP ambiguity loses its integer characteristics due to hardware delay in practice, and the ambiguity is difficult to fix, resulting in low parameter estimation accuracy, the uncorrected phase delay (UPD) correction method is introduced to separate the station-satellite UPD from the undifferenced ambiguity of all reference stations in the region. Then the ambiguity is corrected by inter-satellite difference and UPD at each reference station to obtain the ambiguity with integer characteristics and adjust the parameter estimation results, so that the PPP solution can achieve the same accuracy as the double-difference network solution. Figure 1 : is a flow chart of a method for generating GNSS virtual observation values ​​based on real-time precise single-point positioning provided by the present invention, such as Figure 1 As shown, including but not limited to the following steps:

[0035] Step 1: Obtain the ephemeris clock error data and the observation data received in real time by the reference station, fill in the UCUD PPP observation equation, and solve the non-difference floating-point solution of the parameters to be estimated for each parameter station; the parameters to be estimated include the three-dimensional coordinates of the user station, the re-parameterized receiver clock error, the slant range ionospheric delay, the zenith tropospheric delay ZTD, and the re-parameterized phase floating-point ambiguity.

[0036] Specifically, determine 3 or more dual-frequency (or more) GNSS reference stations that constitute the regional reference station network, obtain the antenna phase delay (PCO) and antenna phase deviation (PCV) calibration results of each station, establish a communication link from each reference station to the network RTK processing center, and the server receives the observation data stream and navigation data stream in RTCM format output by each reference station receiver. The observation data sampling interval should be set to no less than 5s and no more than 30s to ensure the solution efficiency and provide a sufficiently high time resolution.

[0037] To improve the continuity and accuracy of broadcast ephemeris, the server simultaneously receives the real-time ephemeris and clock error (SSR) correction data stream provided by the IGS Analysis Center based on the global reference station network, and pre-downloads the most recent ultra-fast predicted ephemeris and clock error before solving, which is used for repair when the SSR correction data stream is interrupted.

[0038] After the server completes and tests the above data access, it starts the re-parameterized UCUD PPP non-difference atmospheric delay parameter estimation. A thread is established for each reference station, and the Kalman filter is used as the parameter estimation method. The linearized and re-parameterized UCUD PPP function model and the random model are used as the observation equation of the Kalman filter, which is expressed as:

[0039]

[0040] In the formula, the superscript s represents the satellite number, the subscript r represents the receiver, and i represents the carrier phase frequency; and are the pseudorange and phase observations minus the calculated values ​​(OMC), respectively; and x represent the unit vector from the receiver to the satellite and the three-dimensional coordinate parameters of the user station to be estimated respectively; is the re-parameterized receiver clock error; is the ionospheric delay coefficient, f represents the frequency; is the slant range ionospheric delay; is the tropospheric projection function; T r is the zenith tropospheric delay ZTD; λ i is the carrier wavelength of frequency i; is the reparameterized phase float ambiguity; and They refer to the observation noise of pseudorange and phase respectively.

[0041] The parameters to be estimated in the above observation equation include: When setting the state equation of the Kalman filter, the receiving clock error, STEC, and ZTD are all modeled as random walk models. The initial value and initial noise of the parameters are set for the Kalman filter. At each epoch, the state is updated through observation information. As the observation time increases and the number of observations increases, the state parameters tend to be stable. Usually, a higher floating point solution parameter estimation accuracy can be obtained after 2 hours.

[0042] Step 2: Through UPD estimation, the non-differenced floating-point solution ambiguity parameters are restored to integer characteristics, and the fixed solution STEC and fixed solution ZTD are obtained, thereby improving the accuracy of GNSS atmospheric delay extraction.

[0043] Specifically, after each thread completes the solution, the re-parameterized phase floating point ambiguity is converted into (For example, frequency i = 1, 2) is converted into floating-point wide-lane ambiguity which is easier to fix and the matching deionospheric IF float ambiguity

[0044]

[0045] definition is the ionosphere-free combination coefficient. Based on the error propagation law, Post-test variance estimation and The variance of each reference station is read from each solution thread. and It is divided into two steps, wide lane and narrow lane, and the UPD of wide lane and narrow lane UPD are estimated by UPD network adjustment method.

[0046] (1) Wide Lane UPD Estimation

[0047] Consider the undifferenced widelane integer ambiguity Including reference station UPDu rand satellite UPDu s , Express Round to the nearest integer to satisfy the relationship:

[0048]

[0049] Will As an observation, u r,wl , As parameters, the WL UPD network solution equation is constructed as follows:

[0050]

[0051] In the formula, the superscript (1, 2…n) represents the satellite, the subscript (1, 2…m) represents the receiver, and I represents the unit array. is the Kronecker integrator symbol. To solve this equation, we need to solve its rank deficiency and also need to calculate u r,wl , Assign initial values. For rank deficiency, adding a zero mean constraint on the satellite-side UPD can make the normal equation reversible. The initial value can be obtained by the following three steps: (a) Set the receiver UPD of the reference station that observes the most satellites to 0 and take the decimal part of the floating-point ambiguity to calculate the satellite UPD; (b) For the next reference station with the same satellite, deduct the satellite-side UPD of the same satellite and take the average to obtain the UPD of this station. If this station observes other satellites, deduct the UPD of this station to obtain the satellite-side UPD; (c) After obtaining the UPD of all reference stations, deduct the reference station UPD from the undifferenced floating-point ambiguity and re-take the average of the decimal part as the satellite-side UPD. Iterate the above three steps several times to obtain a more stable UPD initial value. After solving the initial value and rank deficiency, the wide lane UPD can be obtained by the linear least squares method.

[0052] (2) Combination solution for narrow lane ambiguity

[0053] Use the previous step WL UPD fix result to remove the floating point wide lane ambiguity The station star UPD absorbed in the middle is rounded to get the whole-cycle WL ambiguity Solving Floating-Point Narrow Lane Ambiguities Wide Lane Integer Ambiguity And the equation satisfied by the ionospheric IF float ambiguity elimination:

[0054]

[0055] Get floating point narrow lane blur

[0056] (3) Narrow Lane UPD Estimation

[0057] It is believed that the narrow lane ambiguity satisfies the relationship:

[0058]

[0059] The NL UPD network adjustment equation is constructed in the same way as the wide lane, and the satellite UPD 0 mean constraint is added to make the equation estimable and the same iterative method is used to assign initial values. The narrow lane UPD is obtained by the linear least squares method.

[0060] Based on the above-mentioned satellite UPD, the UPD of the receiver and satellite on the reference station are eliminated respectively through inter-satellite single difference and UPD correction, and the single difference wide lane ambiguity and single difference narrow lane ambiguity are obtained respectively through rounding and LAMBDA algorithm, and then they are restored to non-combined ambiguity. The estimation results of the floating-point solution parameters are constrained and updated to obtain more reliable fixed solutions STEC and ZTD.

[0061] Step 3: Locally fit STEC as a function of position to establish a regional non-differential ionospheric model.

[0062] By using the characteristics of the slant range delay approximation of each reference station in the region, STEC is locally fitted as a simple function of position, such as a polynomial:

[0063]

[0064] Among them, dλ and are respectively a point in the region to the reference position λ0 and The longitude and latitude difference. is the model coefficient of satellite s, m and n are the model orders, and is the 0th order term, i.e., the constant coefficient term of the polynomial model. The ionospheric parameters estimated by the non-difference model actually absorb the pseudo-range hardware delay of the reference station and the satellite. Using the known ionospheric delay of each user station and the relative position offset of the user station to the center, the design matrix H of the polynomial (such as bilinear model) model parameters is constructed. 0 , estimate a total of n sets of polynomial parameters of n satellites and m receiver-side hardware delays, as shown in equation (10).

[0065]

[0066] To solve the rank deficiency problem in the above equation, (a) the DCB at the satellite end and each 0th-order parameter are linearly correlated and inseparable, so the DCB is absorbed by the 0th-order parameter and will not affect the subsequent generation of virtual observations; (b) the lack of a reference station causes the DCB parameters at the receiver end to have a rank deficiency, which can be eliminated by adding a zero-mean constraint on the DCB at the reference station receiver end. After eliminating the rank deficiency, the linear least squares method can be used to solve the above equation to achieve non-differential ionospheric modeling. When the DCB at the reference station receiver end is not solved, a reference satellite can also be selected to perform inter-satellite differentiation on the above equation and estimate the model coefficients for each satellite.

[0067] In order to avoid the influence of inaccurate observations on the accuracy of the entire single-star model, iterative quality control is performed when solving the above equations using LSQ. That is, when the RMS after adjustment is greater than a certain threshold, the ionospheric observation with the largest observation residual is removed and adjusted again until the RMS of the adjustment is less than the threshold or the number of iterations exceeds the limit.

[0068] Step 4: Locally fit the ZTD as a function of position to establish a regional non-differenced tropospheric model.

[0069] The undifferenced model estimates the undifferenced tropospheric T at each reference station without absorbing the hardware delay. r . Similar to the regional modeling of the ionosphere, the zenith tropospheric delay can be locally fitted as a function of position by simple functions such as bilinear polynomials. After the server-side PPP has fully converged, the ZTD estimate is accurate, and the observation equation of the model parameters of the bilinear model coefficients is also constructed by using the known tropospheric delay of each user station and the offset of the user station relative to the center position. This equation can be directly solved by the linear least squares method, and the iterative quality control method used in ionosphere modeling is also used to finally obtain the accurate regional tropospheric correction model coefficients.

[0070] Step 5: Based on the non-differenced ionosphere model and the regional non-differenced troposphere model, generate the double-differenced atmospheric delay between the main reference station and the virtual reference station to obtain the virtual observation value; among which, the main reference station is the reference station closest to the virtual reference station.

[0071] The position of the virtual reference station v is determined by combining factors such as the user location and the reference station network type, and the nearest physical reference station A is selected as the main reference station. After the non-difference atmospheric delay modeling of each epoch is completed, the plane coordinates of A and v are brought into the model. At the same time, based on the principle of maximum altitude angle, the reference star is selected as 0 to generate the double difference atmospheric delay between the main reference station and the virtual reference station.

[0072] Double difference ionospheric delay for:

[0073]

[0074] In the formula, the subscript v represents the virtual reference station, A is the main reference station, the superscript 0 represents the reference star, and the other parameters have the same meanings as above. Similarly, based on the principle of maximum altitude angle, the reference star is selected as 0 to generate the double difference tropospheric delay between the main reference station and the virtual reference station

[0075] In the formula, β i(i=1,2,3,4) are the coefficients of the tropospheric model. The symbol v represents the virtual reference station, A is the main reference station, the superscript 0 represents the reference satellite, and the other parameters have the same meaning as above. The non-difference phase of the virtual reference station v to the common-view satellite can be obtained by performing geometric correction and atmospheric delay correction based on the actual observation value of the main reference station. and pseudorange virtual observations

[0076]

[0077] In the formula is the geometric correction term, i is the frequency. When calculating the satellite position based on the broadcast ephemeris with additional SSR correction, the difference in signal transmission time should be considered and the effect of the earth's rotation should be corrected on the satellite.

[0078] Network RTK users can construct double-difference observations by subtracting the actual observations from the above virtual observations, thereby reducing the atmospheric delay error, fixing the ambiguity, and obtaining high-precision coordinates.

[0079] Figure 2 : is a structural diagram of a GNSS virtual observation value generation system based on real-time precise single-point positioning provided by the present invention, such as Figure 2 As shown, there are a non-difference floating point solution calculation module 210, a fixed solution calculation module 220, a non-difference atmospheric delay modeling module 230 and a virtual observation value generation module 240.

[0080] The non-difference floating point solution calculation module 210 is used to obtain the ephemeris clock error data and the observation data received in real time by the reference station, fill in the UCUD PPP observation equation, and solve the non-difference floating point solution of the parameters to be estimated for each parameter station; wherein the parameters to be estimated include the three-dimensional coordinates of the user station, the re-parameterized receiver clock error, the slant range ionospheric delay, the zenith tropospheric delay ZTD and the re-parameterized phase floating point ambiguity;

[0081] A fixed solution calculation module 220 is used to restore the integer characteristics of the non-difference floating point solution ambiguity parameters through UPD estimation, and obtain the fixed solution STEC and the fixed solution ZTD;

[0082] The non-differenced atmospheric delay modeling module 230 is used to locally fit STEC as a function of position to establish a regional non-differenced ionosphere model; and locally fit ZTD as a function of position to establish a regional non-differenced troposphere model;

[0083] The virtual observation value generation module 240 is used to substitute the plane coordinates of the virtual reference station and the main reference station into the regional non-differenced ionosphere model and the regional non-differenced troposphere model respectively, to generate the differential atmospheric delay between the main reference station and the virtual reference station; perform geometric correction and atmospheric delay correction on the basis of the actual observation value of the main reference station to obtain the non-differenced phase and pseudo-range virtual observation values ​​of the virtual reference station for the common-view satellite; wherein the main reference station is the reference station closest to the virtual reference station.

[0084] It should be noted that the GNSS virtual observation value generation system based on real-time precise single-point positioning provided in an embodiment of the present invention can, during specific operation, execute the GNSS virtual observation value generation method based on real-time precise single-point positioning described in any of the above embodiments, which will not be elaborated in this embodiment.

[0085] Figure 3 is a schematic diagram of the structure of the electronic device provided by the present invention, such as Figure 3 As shown, the electronic device may include: a processor 310, a communication interface 320, a memory 330 and a communication bus 340, wherein the processor 310, the communication interface 320 and the memory 330 communicate with each other through the communication bus 340. The processor 310 may call the logic instructions in the memory 330 to execute the GNSS virtual observation value generation method based on real-time precise single point positioning.

[0086] In addition, the logic instructions in the above-mentioned memory 330 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on such an understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art or the part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0087] On the other hand, the present invention also provides a computer program product, which includes a computer program stored on a non-transitory computer-readable storage medium, and the computer program includes program instructions. When the program instructions are executed by a computer, the computer can execute the GNSS virtual observation value generation method based on real-time precise single-point positioning provided in the above-mentioned embodiments.

[0088] On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to execute the GNSS virtual observation value generation method based on real-time precise single-point positioning provided in the above-mentioned embodiments.

[0089] The system embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated. Some or all of the modules may be selected according to actual needs to achieve the purpose of the present embodiment. Those of ordinary skill in the art may understand and implement the present invention without creative effort.

[0090] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0091] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for generating GNSS virtual observation values ​​based on real-time precise single-point positioning, characterized in that: include: Obtain the ephemeris clock error data and the observation data received in real time by the reference station, fill in the UCUD PPP observation equation, and solve the non-difference floating-point solution of the parameters to be estimated for each parameter station; the parameters to be estimated include the three-dimensional coordinates of the user station, the re-parameterized receiver clock error, the slant range ionospheric delay, the zenith tropospheric delay ZTD, and the re-parameterized phase floating-point ambiguity; Through UPD estimation, the non-differenced floating point solution ambiguity parameters are restored to integer characteristics, and the fixed solution STEC and fixed solution ZTD are obtained; The STEC is locally fitted as a function of the position to establish a regional non-differential ionosphere model; and the ZTD is locally fitted as a function of the position to establish a regional non-differential troposphere model; Based on the non-differenced ionosphere model and the regional non-differenced troposphere model, the double-differenced atmospheric delay between the main reference station and the virtual reference station is generated to obtain the virtual observation value; Among them, the main reference station is the reference station closest to the virtual reference station.

2. The method for generating GNSS virtual observation values ​​based on real-time precise point positioning according to claim 1 generates double-difference atmospheric delays between a main reference station and a virtual reference station based on a non-differenced ionosphere model and a regional non-differenced troposphere model to obtain virtual observation values, comprising: Substituting the plane coordinates of the virtual reference station and the main reference station into the regional non-differenced ionosphere model and the regional non-differenced troposphere model respectively, the double-differenced atmospheric delay between the main reference station and the virtual reference station is generated; wherein the double-differenced atmospheric delay includes the double-differenced ionosphere delay and the double-differenced troposphere delay; Based on the actual observation values ​​of the main reference station, geometric correction and atmospheric delay correction are performed to obtain the virtual reference station's undifferenced phase and pseudorange virtual observation values ​​of the common-view satellite. Network RTK users make a difference between the actual observation value and the virtual observation value to construct a double difference observation value.

3. The method for generating GNSS virtual observation values ​​based on real-time precise single point positioning according to claim 1, characterized in that: The expression of the UCUD PPP observation equation is: In the formula, the superscript s represents the satellite number, the subscript r represents the receiver, and i represents the carrier phase frequency; and The pseudorange and phase observations minus the calculated value OMC, respectively; and x represent the unit vector from the receiver to the satellite and the three-dimensional coordinate parameters of the user station to be estimated respectively; is the re-parameterized receiver clock error; γ i is the ionospheric delay coefficient; is the slant range ionospheric delay; is the tropospheric projection function; T r is the zenith tropospheric delay ZTD; λ i is the carrier wavelength of frequency i; is the reparameterized phase float ambiguity; and They refer to the observation noise of pseudorange and phase respectively.

4. The method for generating GNSS virtual observation values ​​based on real-time precise single point positioning according to claim 1, characterized in that: Through UPD estimation, the non-differenced floating point solution ambiguity parameters are restored to integer characteristics, and the fixed solution STEC and fixed solution ZTD are obtained, including: Convert the reparameterized phase float ambiguity into float widelane ambiguity and ionospheric-free IF float ambiguity; It is divided into two steps, wide lane and narrow lane. Based on the floating wide lane ambiguity and the ionospheric IF floating ambiguity, the UPD network adjustment method is used to estimate the wide lane UPD and narrow lane UPD. The UPD of the receiver and satellite at the reference station are eliminated by inter-satellite single difference and UPD correction respectively; The single-difference wide lane ambiguity and single-difference narrow lane ambiguity are obtained respectively by rounding and LAMBDA algorithm, and then restored to non-combined ambiguity. The estimation results of floating-point solution parameters are constrained to update, and the fixed solution STEC and the fixed solution ZTD are obtained.

5. The method for generating GNSS virtual observation values ​​based on real-time precise single point positioning according to claim 1, characterized in that: The model parameters of the regional non-difference ionosphere model and the regional non-difference troposphere model are solved using a linear least squares method.

6. The method for generating GNSS virtual observation values ​​based on real-time precise single point positioning according to claim 1, characterized in that: The phase float ambiguity to be reparameterized Convert to floating point wide lane blur and eliminate ionospheric IF float ambiguity Specifically include: Among them, the definition is the ionosphere-free combination coefficient.

7. A GNSS virtual observation value generation system based on real-time precise single-point positioning, characterized in that: include: The non-difference floating-point solution calculation module is used to obtain the ephemeris clock error data and the observation data received in real time by the reference station, fill in the UCUD PPP observation equation, and solve the non-difference floating-point solution of the parameters to be estimated for each parameter station; the parameters to be estimated include the three-dimensional coordinates of the user station, the re-parameterized receiver clock error, the slant range ionospheric delay, the zenith tropospheric delay ZTD, and the re-parameterized phase floating-point ambiguity; The fixed solution calculation module is used to restore the integer characteristics of the non-difference floating point solution ambiguity parameters through UPD estimation, and obtain the fixed solution STEC and the fixed solution ZTD; A non-differenced atmospheric delay modeling module for locally fitting STEC as a function of position to establish a regional non-differenced ionosphere model; and locally fitting ZTD as a function of position to establish a regional non-differenced troposphere model; The virtual observation value generation module is used to substitute the plane coordinates of the virtual reference station and the main reference station into the regional non-differenced ionosphere model and the regional non-differenced troposphere model respectively to generate the double-differenced atmospheric delay between the main reference station and the virtual reference station; perform geometric correction and atmospheric delay correction on the basis of the actual observation values ​​of the main reference station to obtain the non-differenced phase and pseudo-range virtual observation values ​​of the virtual reference station for the common-view satellite; Among them, the main reference station is the reference station closest to the virtual reference station.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the steps of the method for generating GNSS virtual observation values ​​based on real-time precise point positioning as described in any one of claims 1 to 6 are implemented.

9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method for generating GNSS virtual observation values ​​based on real-time precise single-point positioning as described in any one of claims 1 to 6 are implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method for generating GNSS virtual observation values ​​based on real-time precise single-point positioning as described in any one of claims 1 to 6 are implemented.

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