GNSS virtual observation value generation method and system based on real-time precise single point positioning

Abstract

The present invention provides a method and system for generating GNSS virtual observation values ​​based on real-time precise single-point positioning, belonging to the field of GNSS positioning technology. The method comprises: obtaining ephemeris clock data and observation data received in real time by a reference station, filling in the UCUD PPP observation equation, and solving a non-differenced floating-point solution for the parameter to be estimated for each parameter station; restoring the integer characteristics of the non-differenced floating-point solution ambiguity parameter through UPD estimation 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 ionosphere model; and locally fitting ZTD as a function of position to establish a regional non-differenced troposphere model; based on the non-differenced ionosphere model and the regional non-differenced troposphere model, generating a double-differenced atmospheric delay between a master reference station and a virtual reference station to obtain a virtual observation value. The present invention effectively improves the reliability of the atmospheric delay of the GNSS signal, thereby improving the quality of the virtual observation value.

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. By receiving virtual observations and performing inter-station and inter-satellite differentials with local observations, network RTK users can eliminate clock errors and hardware delay errors between the satellite and receiver ends, while significantly reducing spatially correlated tropospheric and ionospheric delays, thereby obtaining centimeter-level high-precision baseline solutions.

[0003] Traditional virtual observation generation methods are based on double-difference network solutions, which require the construction of a receiver network based on certain topological rules, with adjacent reference stations forming a baseline. The CORS server uses certain parameter estimation methods to solve the inter-station and inter-satellite double-difference observation equations, fixing the double-difference ambiguities to integers, thereby estimating centimeter-level double-difference tropospheric and ionospheric delays. However, the double-difference model has the problem of relying on common-view satellites during the solution phase; in the tropospheric / ionospheric modeling phase, modeling is often limited to small cells, making it difficult to fully utilize the continuous distribution characteristics of the atmospheric error region. 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, making it difficult to expand or add external constraints. Summary of the Invention

[0004] The present invention provides a method and system for generating GNSS virtual observation values ​​based on real-time precise single-point positioning, which is used to solve the technical problems of insufficient satellite utilization and difficulty in modeling atmospheric error regions in existing double-difference network solutions, 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 point positioning, comprising: obtaining ephemeris clock error data and observation data received in real time by a reference station, filling in the UCUD PPP observation equation, and solving the non-differenced 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, a re-parameterized receiver clock error, a slant range ionospheric delay, a zenith tropospheric delay (ZTD), and a re-parameterized phase floating-point ambiguity; through UPD estimation, the non-differenced floating-point solution ambiguity parameters are restored to the 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 master reference station and a virtual reference station to obtain virtual observation values; wherein the master reference station is the reference station closest to the virtual reference station.

[0006] According to the present invention, a GNSS virtual observation value generation method based on real-time precise single-point positioning is provided. Based on a non-differenced ionosphere model and a regional non-differenced troposphere model, a double-differenced atmospheric delay is generated between a master reference station and a virtual reference station to obtain a virtual observation value. The method includes: substituting the plane coordinates of the virtual reference station and the master 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 master 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 actual observation value of the master reference station to obtain the non-differenced phase and pseudo-range virtual observation value of the virtual reference station for the common view satellite; and the network RTK user subtracts the actual observation value from the virtual observation value to construct a double-differenced observation value.

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

[0008]

[0009] Where, 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 the integer characteristics through UPD estimation to obtain the fixed solution STEC and the fixed solution ZTD. The method includes: converting the re-parameterized phase floating-point ambiguity into floating-point wide-lane ambiguity and ionospheric-free IF floating-point ambiguity; estimating the wide-lane UPD and narrow-lane UPD based on the floating-point wide-lane ambiguity and ionospheric-free IF floating-point ambiguity in two steps, wide-lane and narrow-lane, using the UPD network adjustment method; eliminating the UPD of the receiver on the reference station and the satellite respectively through inter-satellite single difference and UPD correction; obtaining the single-difference wide-lane ambiguity and the single-difference narrow-lane ambiguity respectively through rounding and the LAMBDA algorithm, and then restoring them to non-combined ambiguities, constraining and updating the floating-point solution parameter estimation results to obtain the fixed solution STEC and the fixed solution 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 the 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 ambiguity and eliminate ionospheric IF float ambiguity Specifically include:

[0013]

[0014] Among them, the definition is the ionospheric-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 undifferenced floating-point solution calculation module is used to obtain ephemeris clock error data and observation data received in real time by the reference station, fill in the UCUD PPP observation equation, and solve the undifferenced 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 reparameterized receiver clock error, the slant range ionospheric delay, the zenith tropospheric delay (ZTD), and the reparameterized phase floating-point ambiguity.

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

[0018] The undifferenced atmospheric delay modeling module is used to locally fit the STEC as a function of position to establish a regional undifferenced ionospheric model; and to locally fit the ZTD as a function of position to establish a regional undifferenced tropospheric 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; based on the actual observation values ​​of the main reference station, geometric correction and atmospheric delay correction are performed to obtain the non-differenced phase and pseudo-range virtual observation values ​​of the virtual reference station on 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. When the processor executes the program, the processor implements the steps of any of the above-described methods for generating GNSS virtual observation values ​​based on real-time precise single-point positioning.

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

[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. Compared with the intra-unit model, the regional model can effectively utilize the consistency of atmospheric errors in the region, improve the model accuracy, and thus improve the quality of the final product virtual observation value;

[0026] (3) The scalability of the non-differential model in the present invention not only makes it easy to add various constraints to the server-side observation equations based on the actual conditions of the survey area, but also provides both RTK and PPP-RTK mode services through a single server-side solution, thereby improving the multi-mode working 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, a brief introduction is given below to 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 any creative work.

[0028] Figure 1 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;

[0029] Figure 2 Schematic diagram of the structure of the 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] To make the objectives, technical solutions, and advantages of the present invention more clear, the technical solutions of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the embodiments described are only some of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts shall fall 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 "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, article, or apparatus comprising a series of elements includes not only those elements but also other elements not explicitly listed, or also includes elements inherent to such process, method, article, or apparatus. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, method, article, or apparatus comprising the element.

[0033] The basic idea of ​​the present invention is to estimate the undifferenced 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 zenith tropospheric delay (ZTD), and use the spatial autocorrelation of regional undifferenced STEC and ZTD to establish an atmospheric fitting model for the target location. A single model is used to predict the atmospheric delay at any point within the reference network (network RTK service), solving the problem that traditional double-difference network solutions for atmospheric delay are difficult to perform regional modeling.

[0034] In practice, the real-time UCUD PPP ambiguities lose their integer cycle characteristics due to hardware delay, which makes it difficult to fix the ambiguities and leads to low parameter estimation accuracy. To address the problem, an uncorrected phase delay (UPD) correction method is introduced. The station-satellite UPD is separated from the undifferenced ambiguities of all reference stations in the region. The ambiguities are then corrected for inter-satellite differences and UPD at each reference station to obtain ambiguities with integer cycle characteristics. The parameter estimation results are then adjusted to make the PPP solution achieve the same accuracy as the double-difference network solution. Figure 1 : is a flow chart of the 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 ephemeris clock data and observation data received in real time by the reference station, fill in the UCUD PPP observation equation, and solve the non-differenced floating-point solution of the parameters to be estimated for each parameter station. The parameters to be estimated include the 3D coordinates of the user station, the reparameterized receiver clock error, the slant range ionospheric delay, the zenith tropospheric delay (ZTD), and the reparameterized phase floating-point ambiguity.

[0036] Specifically, three or more dual-frequency GNSS reference stations (or more) that comprise the regional reference station network are identified. The antenna phase delay (PCO) and antenna phase deviation (PCV) calibration results are obtained for each station. A communication link is established from each reference station to the network RTK processing center. The server receives the observation and navigation data streams in RTCM format output by each reference station receiver. The observation data sampling interval should be set to no less than 5 seconds and no more than 30 seconds to ensure solution efficiency and provide sufficiently high temporal resolution.

[0037] To improve the continuity and accuracy of broadcast ephemeris, the server also receives the real-time ephemeris and clock correction (SSR) data stream provided by the IGS Analysis Center based on the global reference station network. Before solving, it pre-downloads the latest ultra-fast predicted ephemeris and clock errors to repair the interruption of the SSR correction data stream.

[0038] After the server completes and tests the above data access, it starts the reparameterized UCUD PPP undifferenced atmospheric delay parameter estimation. A thread is established for each reference station, using Kalman filtering as the parameter estimation method, with the linearized and reparameterized UCUD PPP function model and the random model as the observation equation of the Kalman filter, expressed as:

[0039]

[0040] Where, 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 observation 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; 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 for the Kalman filter, the received clock error, STEC, and ZTD are all modeled as random walks. Initial parameter values ​​and initial noise are set for the Kalman filter. At each epoch, the state is updated using observations. As observation time increases and the number of observations increases, the state parameters tend to stabilize. Typically, a high degree of floating-point solution parameter estimation accuracy can be achieved after two hours.

[0042] Step 2: Through UPD estimation, the non-differenced floating-point ambiguity resolution parameters are restored to their integer characteristics, and the fixed solutions STEC and 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 ionospheric-free 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 The UPD of wide lane and narrow lane are estimated by using UPD network adjustment method in two steps.

[0046] (1) Wide Lane UPD Estimation

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

[0048]

[0049] Will As the observed value, 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. Solving this equation requires solving its rank deficiency and also u r,wl , Assign initial values. To address the rank deficiency, adding a zero-mean constraint on the satellite-side UPD makes the normal equation reversible. The initial values ​​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 fractional 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 station UPD. If the station observes other satellites, deduct the station UPD 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 fractional part average 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 fixed result to deduct the floating point wide lane ambiguity The UPD of the station star absorbed in the middle is rounded to get the whole-week WL ambiguity Resolving floating-point narrow lane ambiguity Wide Lane Integer Ambiguity And the equations satisfied by the ionospheric IF float ambiguity are:

[0054]

[0055] Get floating point narrow lane ambiguity

[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 for wide lanes. A satellite UPD zero 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 using 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. The single-difference wide-lane ambiguity and single-difference narrow-lane ambiguity are obtained respectively through rounding and LAMBDA algorithm. Then they are restored to non-combined ambiguities, and the floating-point solution parameter estimation results are constrained to update 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 utilizing 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 difference in longitude and latitude. 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 pseudorange hardware delay of the reference station and the satellite end. Using the known ionospheric delay of each user station and the offset of the user station relative to the center position, the design matrix H for the polynomial (such as bilinear model) model parameters is constructed. 0 , estimate the n sets of polynomial parameters of n satellites and the m receiver hardware delays, as shown in the following equation (10).

[0065]

[0066] To address the rank deficiency in the above equation, (a) the satellite-side DCB and the zero-order parameters are linearly correlated and inseparable, so the DCB is absorbed by the zero-order parameters and does not affect the generation of subsequent virtual observations. (b) The lack of a reference station causes the receiver-side DCB parameters to have a rank deficiency, which can be eliminated by adding a zero-mean constraint on the DCB at the reference station receiver. After eliminating the rank deficiency, solving the above equation using linear least squares can achieve undifferenced ionospheric modeling. Alternatively, a reference satellite can be selected to perform inter-satellite differencing on the above equation, estimating the model coefficients satellite by satellite.

[0067] 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 undifferenced tropospheric model.

[0069] The undifferenced model estimates the undifferenced tropospheric T at each reference station without absorbing hardware delay. r Similar to regional ionospheric modeling, 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 estimation is accurate. Using the known tropospheric delay of each user station and the offset of the user station relative to the center position, the observation equation of the model parameters of the bilinear model coefficients is also constructed. This equation can be directly solved using the linear least squares method, and the iterative quality control method used in ionospheric modeling is also adopted to finally obtain the accurate regional tropospheric correction model coefficients.

[0070] Step 5: Generate the double-difference atmospheric delay between the master reference station and the virtual reference station based on the undifferenced ionosphere model and the regional undifferenced troposphere model to obtain the virtual observation value; the master reference station is the reference station closest to the virtual reference station.

[0071] The location of the virtual reference station v is determined by combining factors such as the user's location and the reference station network. The nearest physical reference station A is selected as the primary reference station. After the undifferenced atmospheric delay modeling is completed for each epoch, the A and v plane coordinates are entered into the model. Simultaneously, based on the principle of maximum elevation angle, a reference star is marked as zero to generate a double-differenced atmospheric delay between the primary and virtual reference stations.

[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] Where, β i(i=1,2,3,4) are the coefficients of the tropospheric model. The index 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. Based on the actual observations of the main reference station, the geometric correction and atmospheric delay correction are performed to obtain the undifferenced phase of the virtual reference station v to the common view satellite. and pseudorange virtual observations

[0076]

[0077] In the formula is the geometric correction term, i is the frequency, and 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 virtual observations, thereby reducing the atmospheric delay error, fixing the ambiguity, and obtaining high-precision coordinates.

[0079] Figure 2 : is a structural diagram of the 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-differenced floating-point solution calculation module 210, a fixed solution calculation module 220, a non-differenced atmospheric delay modeling module 230 and a virtual observation value generation module 240.

[0080] The undifferenced floating-point solution calculation module 210 is used to obtain ephemeris clock error data and observation data received in real time by the reference station, fill in the UCUD PPP observation equation, and solve the undifferenced 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 reparameterized receiver clock error, the slant range ionospheric delay, the zenith tropospheric delay (ZTD), and the reparameterized phase floating-point ambiguity.

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

[0082] The non-differenced atmospheric delay modeling module 230 is used to locally fit the STEC as a function of position to establish a regional non-differenced ionospheric model; and locally fit the ZTD as a function of position to establish a regional non-differenced tropospheric 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 on 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 by the embodiment of the present invention can execute the GNSS virtual observation value generation method based on real-time precise single-point positioning described in any of the above embodiments during specific operation, which will not be elaborated in this embodiment.

[0085] Figure 3 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 via the communication bus 340. The processor 310 may call logic instructions in the memory 330 to execute a method for generating GNSS virtual observation values ​​based on real-time precise 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 sold or used as an independent product. Based on this 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 for enabling 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, etc. Various 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 separate. Some or all of the modules may be selected based on actual needs to achieve the objectives of the present embodiment. Persons of ordinary skill in the art will be able to understand and implement the present invention without inventive effort.

[0090] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, or of course, by hardware. Based on this understanding, the essence of the above technical solution or the part that contributes to the existing technology can be embodied in the form of a software product. The computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a magnetic disk, an optical disk, etc., and includes a number of instructions for enabling 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 certain 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 various 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 ephemeris clock data and observation data received in real time by the reference station, fill in the UCUD PPP observation equation, and solve the non-differenced floating-point solution of the parameters to be estimated for each parameter station. The parameters to be estimated include the 3D coordinates of the user station, the reparameterized receiver clock error, the slant range ionospheric delay, the zenith tropospheric delay (ZTD), and the reparameterized phase floating-point ambiguity. Through UPD estimation, the non-differenced floating point ambiguity resolution parameters are restored to the integer characteristics, and the fixed solution STEC and fixed solution ZTD are obtained; Locally fitting STEC as a function of position to establish a regional non-differential ionospheric model; and locally fitting ZTD as a function of position to establish a regional non-differential tropospheric 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; The expression of the UCUD PPP observation equation is: ； ； In the formula, the superscript Indicates the satellite number, subscript Represents the receiver, Indicates the carrier phase frequency; and The pseudorange and phase observations minus the calculated value OMC respectively; and x They represent the unit vector from the receiver to the satellite and the three-dimensional coordinate parameters of the user station to be estimated; is the re-parameterized receiver clock error; is the ionospheric delay coefficient; is the slant range ionospheric delay; is the tropospheric projection function; is the zenith tropospheric delay ZTD; Frequency i carrier wavelength; is the reparameterized phase float ambiguity; and refer to the observation noise of pseudorange and phase respectively; Through UPD estimation, the non-differenced floating-point ambiguity resolution parameters are restored to their integer characteristics, and the fixed solutions STEC and ZTD are obtained, including: Convert the reparameterized phase float ambiguity into float widelane ambiguity and ionospheric-free IF float ambiguity; The wide lane UPD and narrow lane UPD are estimated in two steps: wide lane UPD and narrow lane UPD. Based on the floating wide lane ambiguity and the ionospheric IF floating ambiguity, the UPD network adjustment method is used. 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 floating-point solution parameter estimation results are constrained and updated to obtain the fixed solution STEC and the fixed solution ZTD.

2. The method for generating GNSS virtual observations based on real-time precise point positioning according to claim 1, generating a double-differenced atmospheric delay between a master reference station and a virtual reference station based on a non-differenced ionosphere model and a regional non-differenced troposphere model to obtain virtual observations, comprising: Substituting the plane coordinates of the virtual reference station and the master reference station into the regional non-differenced ionosphere model and the regional non-differenced troposphere model respectively, generates the double-differenced atmospheric delay between the master reference station and the virtual reference station; wherein the double-differenced atmospheric delay includes the double-differenced ionospheric delay and the double-differenced tropospheric delay; Based on the actual observation values ​​of the main reference station, geometric correction and atmospheric delay correction are performed to obtain the undifferenced phase and pseudorange virtual observation values ​​of the virtual reference station on the common view satellite; Network RTK users subtract the actual observation value from 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 point positioning according to claim 1, characterized in that: The model parameters of the regional non-differenced ionosphere model and the regional non-differenced troposphere model are both solved using a linear least squares method.

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

5. A GNSS virtual observation value generation system based on real-time precise single point positioning, used to implement the GNSS virtual observation value generation method according to any one of claims 1 to 4, characterized in that: include: The undifferenced floating-point solution calculation module is used to obtain ephemeris clock error data and observation data received in real time by the reference station, fill in the UCUD PPP observation equation, and solve the undifferenced 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 reparameterized receiver clock error, the slant range ionospheric delay, the zenith tropospheric delay (ZTD), and the reparameterized phase floating-point ambiguity. The fixed solution calculation module is used to restore the integer characteristics of the non-differenced floating point solution ambiguity parameters through UPD estimation, and obtain the fixed solution STEC and the fixed solution ZTD; The undifferenced atmospheric delay modeling module is used to locally fit the STEC as a function of position to establish a regional undifferenced ionospheric model; and to locally fit the ZTD as a function of position to establish a regional undifferenced tropospheric 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; based on the actual observation values ​​of the main reference station, geometric correction and atmospheric delay correction are performed to obtain the non-differenced phase and pseudo-range virtual observation values ​​of the virtual reference station on the common view satellite; Among them, the main reference station is the reference station closest to the virtual reference station.

6. 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 single point positioning as described in any one of claims 1 to 4 are implemented.

7. 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 4 are implemented.

8. 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 4 are implemented.

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