GNSS (Global Navigation Satellite System) real-time precise single-point positioning ambiguity fixing method for complex environment

Abstract

The invention relates to the technical field of GNSS (Global Navigation Satellite System) navigation and positioning, in particular to a GNSS real-time precise single-point positioning ambiguity fixing method for a complex environment. The method comprises the steps of obtaining and processing data, obtaining a precision satellite orbit and a precision satellite clock error from original observation data, broadcast ephemeris and an SSR correction number which are originally obtained in sequence, obtaining original frequency point non-difference floating point ambiguity, obtaining fixed integer inter-satellite single-difference wide-lane ambiguity, and obtaining floating point inter-satellite single-difference narrow-lane ambiguity. And finally, selecting the complete set ambiguity according to the precision index of the floating point narrow lane ambiguity, and carrying out iteration to obtain an ambiguity subset meeting the optimal aperture check rule. Through the method, the ambiguity fixing reliability can be further improved, and the convergence time is shortened.

Description

Technical Field

[0001] The present invention relates to the technical field of Global Navigation Satellite System (GNSS) navigation and positioning, and in particular to a method for fixing GNSS real-time precise point positioning ambiguity in a complex environment. Background Art

[0002] The navigation service accuracy of GNSS itself can reach the meter level, which can meet the positioning requirements of daily vehicles, ships, etc., but still cannot meet the application requirements of the real-time high-precision industry. To solve this problem, some research scholars have proposed the Precise Point Positioning (PPP) technology, which greatly improves the positioning accuracy of GNSS. The PPP technology has multiple advantages compared with the RTK (Real-Time Kinematic) technology. First, the PPP technology has a wide range of applications and can be used anywhere, without being restricted by the number and location of base stations, and is very suitable for remote areas. Second, under ideal conditions, the PPP technology can provide high precision of sub-meter or even centimeter level, meeting the high-precision application requirements. In addition, PPP does not rely on fixed base stations and real-time data transmission, making it more flexible in construction or field surveys. Its post-processing ability also enables the use of longer-term data to improve accuracy, suitable for precise measurement. At the same time, due to the use of the global satellite system, PPP performs better in environments with severe multipath signals or interference. Although the PPP technology is already very mature at present, there are still many problems in its ambiguity resolution algorithm (AR), which has become a research hotspot for many experts and scholars.

[0003] Since PPP estimates the floating-point solution of ambiguity, there is a correlation between ambiguity and other estimated parameters, and it usually takes dozens of minutes for ambiguity convergence. If the ambiguity can be fixed, the convergence speed and positioning accuracy of PPP can be greatly improved. The core of PPP AR is to restore the integer characteristics of the ambiguity parameter, and the main implementation methods of this step include the Uncalibrated Phase Delays (UPD) method and the Integer Recovery Clock (IRC) method.

[0004] After external product correction, the integer characteristics of PPP ambiguity can be restored. Therefore, the ambiguity fixing theory and methods in the GNSS field are also applicable to precise point positioning. Currently, most of the ambiguity fixing research in the GNSS field is implemented based on the LAMBDA (Least-squares Ambiguity Decorrelation Adjustment, LAMBD) decorrelation search method or the BIE (Best Integer Equivariant, BIE) optimal integer equivariant estimation method. However, both of these methods have problems of low reliability or efficiency in complex environments.

[0005] Patent CN111638535B uses the best integer equivariant (BIE) for PPP ambiguity fixing and achieves good results, proving that the positioning error of the PPP fixed solution of the BIE method is less than that of the LAMBDA method. However, when performing real-time positioning in complex environments, due to the relatively low accuracy of real-time satellite orbits, clock errors and other products, the solution accuracy of the floating-point ambiguity of the filter estimation is relatively low, which will increase the possibility of incorrect fixing of the BIE ambiguity. At the same time, with the continuous increase in the number of GNSS satellites and the number of observations, the number of ambiguity parameters to be estimated involved in ambiguity fixing is also increasing. The solution of such high-dimensional ambiguity parameters will not only reduce the success rate of all ambiguities being fixed successfully, but also increase the possibility of incorrect fixing of the ambiguities. Summary of the Invention

[0006] The present invention provides a method for GNSS real-time precise point positioning ambiguity fixing in complex environments; the present invention improves the BIE ambiguity fixing strategy based on the data-driven idea in the LAMBDA method to integrate the advantages of the LAMBDA method and the BIE method and make up for the corresponding deficiencies, aiming to further improve the reliability of ambiguity fixing and shorten the convergence time.

[0007] The present invention adopts the following technical solutions to achieve the invention purpose:

[0008] A method for GNSS real-time precise point positioning ambiguity fixing in complex environments, comprising the following steps:

[0009] S1: Obtain the original observation data, broadcast ephemeris, and SSR corrections;

[0010] S2: Process the broadcast ephemeris and SSR corrections to obtain precise satellite orbits and precise satellite clock errors;

[0011] S3: Process the original observation data, precise satellite orbits, and precise satellite clock errors to obtain the original frequency non-differenced floating-point ambiguity;

[0012] S4: Process the undifferenced floating-point ambiguity of the original frequency points to obtain fixed integer inter-satellite single-difference wide-lane ambiguities;

[0013] S5: Process the integer inter-satellite single-difference wide-lane ambiguities to obtain the optimized undifferenced ambiguity of the original frequency points; process the integer inter-satellite single-difference wide-lane ambiguities and the optimized undifferenced ambiguity of the original frequency points to obtain floating-point inter-satellite single-difference narrow-lane ambiguities;

[0014] S6: Use the BIE method to process all the floating-point inter-satellite single-difference narrow-lane ambiguity parameters to obtain fixed integer inter-satellite single-difference narrow-lane ambiguities;

[0015] S7: Select the full-set ambiguities according to the accuracy index of the floating-point narrow-lane ambiguities, and iteratively obtain the ambiguity subset that meets the optimal aperture checking criterion.

[0016] In the aforementioned method for GNSS real-time precise point positioning ambiguity fixing in complex environments, step S2 includes:

[0017] For any time t, the formula for calculating the orbit correction in the SSR correction is:

[0018]

[0019] In the above formula, δorb is the vector of the orbit correction in the orbit plane coordinate system; δorb r 、δorb a 、δorb c respectively represent the components of the orbit correction in the radial, tangential, and normal directions at the reference time t0, with the unit of m; respectively represent the rates of change of the orbit correction in the radial, tangential, and normal directions, with the unit of m / s;

[0020] Convert the orbit correction from the orbit plane coordinate system to the Earth-fixed coordinate system, and the conversion formula is:

[0021]

[0022] In the above formula, [X Y Z] T is the satellite coordinate corrected by the orbit correction, that is, the precise satellite orbit; [X brd Y brd Z brd T is the satellite coordinate calculated using the broadcast ephemeris; e r 、e a 、e c are the unit vectors of the satellite radial, tangential, and normal vectors in the Earth-fixed coordinate system respectively;

[0023] ​The clock bias correction provided in the SSR correction is the correction amount for the clock bias calculated relative to the broadcast ephemeris. The precise satellite clock bias corrected by the clock bias correction is expressed as:

[0024] δClk = a0 + a1(t - t0) + a2(t - t0) 2 ;

[0025]

[0026] In the above formula, δClk is the satellite clock bias correction calculated based on the SSR correction; a0, a1, and a2 are the constant term, first-order term, and second-order term coefficients of the clock bias correction, respectively; dClk p is the precise satellite clock bias; dClk brd is the satellite clock bias calculated through the broadcast ephemeris; δClk is the satellite clock bias correction calculated based on the SSR correction; c is the speed of light.

[0027] In the method for fixing GNSS real-time precise single-point positioning ambiguity in a complex environment mentioned above, the method for fixing the ambiguity is characterized in that: Step S3 includes:

[0028] Construct an undifferenced and non-combined PPP positioning model, perform PPP floating-point solution calculation based on the precise satellite orbit and precise satellite clock bias restored in Step S2, and obtain the undifferenced floating-point ambiguity of the original frequency point;

[0029] Taking the L1 and L2 frequency point observations as an example, the pseudorange and phase observations of the satellite at the station in terms of frequency are expressed as:

[0030]

[0031] In the above formula, and represent the pseudorange observation value and the phase observation value, respectively; represents the geometric distance, which is calculated from the precise satellite orbit restored in Step S2 and the approximate coordinates of the user receiver; dt r represents the receiver clock bias; dt s represents the satellite clock bias, which is the precise satellite clock bias restored in Step S2; M s and zwd r represent the tropospheric mapping function and the zenith tropospheric delay, respectively; and represent the ionospheric mapping factor and the ionospheric delay at the first frequency, respectively; b r,i and represent the pseudorange hardware delays at the receiver end and the satellite end at frequency i, respectively; d r,i and represent the phase hardware delays at the receiver end and the satellite end at frequency i, respectively; λi and represent the wavelength and undifferenced integer ambiguity of the phase observation value at frequency i, respectively; represents the error and pseudorange observation noise at frequency i, represents the error and phase observation noise at frequency i, where the error includes multipath error, antenna phase center offset (PCO), antenna phase center variation (PCV), solid tide, ocean tide, pole tide, and relativistic effect error;

[0032] The unknown parameters involved in the above formula are estimated by classical Kalman filtering. The unknown parameters are the corrections to the approximate coordinates of the user receiver, receiver clock bias, zenith tropospheric delay, ionospheric delay, and undifferenced integer ambiguity.

[0033] In the method for fixing the ambiguity of GNSS real-time precise point positioning in a complex environment described above, step S4 includes:

[0034] The satellite undifferenced wide-lane ambiguity is obtained by combining the undifferenced integer ambiguities. The formula is:

[0035]

[0036] is the satellite undifferenced wide-lane ambiguity; represents the undifferenced integer ambiguity at frequency j;

[0037] The receiver-end wide-lane UPD is eliminated by the inter-satellite single-difference method to fix the wide-lane ambiguity. The formula is:

[0038]

[0039] In the above formula, ΔN WL is the fixed inter-satellite single-difference wide-lane ambiguity, and are the wide-lane ambiguities of two different satellites, and S ref is the reference satellite, selected from the satellite with the highest elevation angle;

[0040] Among them, those satisfying the difference from the integer within 0.2 cycles are directly rounded to an integer, which is the integer solution of the fixed integer inter-satellite single-difference wide-lane ambiguity. The formula is:

[0041]

[0042] In the above formula, is the integer inter-satellite single-difference wide-lane ambiguity.

[0043] In the method for fixing the ambiguity of GNSS real-time precise point positioning in a complex environment described above, step S5 includes:

[0044] Re-filter the PPP positioning model based on the wide-lane ambiguity to construct a virtual observation equation to optimize the original frequency non-differential ambiguity. The formula is:

[0045]

[0046] In the above formula, ll represents the virtual observation equation constructed based on the wide-lane ambiguity. is the inter-satellite single-difference wide-lane ambiguity fixed in step S4. and respectively represent the original frequency non-differential floating-point ambiguities calculated at frequencies i and j according to step S3.

[0047] In the above formula, respectively represent the pseudo-range observation value and the phase observation value at any frequency. respectively represent the ionospheric mapping factor and the ionospheric delay at any frequency. respectively represent the pseudo-range hardware delays at the receiver end and the satellite end at any frequency. respectively represent the phase hardware delays at the receiver end and the satellite end at any frequency. respectively represent the wavelength and the non-differential integer cycle ambiguity of the phase observation value at any frequency. represents the error and the pseudo-range observation noise at any frequency. represents the error and the phase observation noise at any frequency.

[0048] In the method for fixing the GNSS real-time precise point positioning ambiguity in the complex environment described above, step S6 includes:

[0049] Use the BIE method to process and fix all the floating-point inter-satellite single-difference narrow-lane ambiguity parameters. The BIE ambiguity fixing method is:

[0050]

[0051] In the above formula, is the integer solution of the inter-satellite difference narrow-lane ambiguity fixed based on the BIE method. is the inter-satellite difference floating-point narrow-lane ambiguity calculated in step S5. z is any set of n-dimensional integer vectors searched; Q is the covariance of the inter-satellite difference narrow-lane ambiguity.

[0052] Then, perform a reliability check on the integer solution of the inter-satellite difference narrow-lane ambiguity fixed based on the BIE method. The reliability check criterion is the optimal integer aperture check method:

[0053]

[0054] In the above formula, OIA refers to the check value, and c p takes 0.95. Indicates the floating-point ambiguity.

[0055] In the method for GNSS real-time precise point positioning ambiguity fixing in a complex environment described above, in step S7, the execution process of the iteration includes:

[0056] S701: Arrange the ambiguity subset to be fixed in descending order according to the variance.

[0057] S702: Try to fix all the narrow-lane ambiguities using the BIE method. If the ambiguity fixing reliability check cannot be passed, then remove the ambiguity with the largest variance and continue to repeat BIE until the number of remaining ambiguities is less than half of the total number of ambiguities.

[0058] S703: If the number of ambiguities that pass the ambiguity fixing reliability check is greater than half of the total number of ambiguities, it is considered that the ambiguity fixing is successful.

[0059] Compared with the prior art, the present invention has the following beneficial effects:

[0060] Aiming at the problems of low PPP floating-point solution accuracy in real-time complex environments, insufficient accuracy of the fixed solution by the LAMBDA method due to excessive ambiguity parameters, and low success probability of the traditional BIE method for fixing, the present invention proposes an improved method for GNSS real-time precise point positioning ambiguity fixing applicable to complex environments. The present invention first refines the original frequency ambiguity based on the fixed wide-lane ambiguity, thereby improving the PPP convergence time and the ambiguity fixing success rate; at the same time, aiming at the problem that it is difficult to perform reliability check for the traditional BIE method, an optimal aperture check scheme is proposed to check the BIE fixing reliability; and a partial ambiguity fixing strategy is added on the basis of the traditional full subset BIE, and the floating-point ambiguities with insufficient accuracy in the subset are removed based on the data-driven idea, increasing the ambiguity fixing success rate of the BIE method and greatly improving the PPP ambiguity fixing positioning performance in complex environments. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] Figure 1 is a schematic flow chart of the core steps of the present invention; DETAILED DESCRIPTION OF THE EMBODIMENTS

[0062] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention.

[0063] Embodiment. A method for GNSS real-time precise point positioning ambiguity fixing in a complex environment, the main step process refers to Figure 1 , and specifically includes the following steps:

[0064] S1: Obtain the original observation data, broadcast ephemeris, and SSR corrections;

[0065] This step is to receive and decode data using existing technologies. Currently, real-time SSR correction products of IGS analysis centers are generally broadcast according to the Ntrip protocol. Currently, several IGS analysis centers provide real-time orbit and clock SSR products for users, mainly including the Chinese Academy of Sciences (CAS), the German Aerospace Center (Deutsches Zentrum für Luft-und Raumfahrt, DLR), the French National Center for Space Studies (Centre National d'Etudes Spatiales, CNES), the German Federal Agency for Cartography and Geodesy (Bundesamt für Kartographie und BKG), the German Research Centre for Geosciences (Deutsches GeoForschungsZentrum, GFZ), the European Space Agency (ESA), the Shanghai Astronomical Observatory of the Chinese Academy of Sciences (Shanghai Astronomical Observatory, SHAO), and Wuhan University (Wuhan University, WHU), etc.

[0066] When receiving real-time data, the specific implementation process is as follows: (1) The server (NtripSerevr) is responsible for sending the real-time data stream to the processing center (NtripCaster). The real-time data stream includes the broadcast ephemeris, observation data, SSR corrections, etc. mentioned above; (2) The processing center (NtripCaster) assigns corresponding IP addresses, port numbers, mount points and other information to the real-time data stream; (3) The client (NtripClient) receives the real-time data stream based on the information provided by the processing center and the communication protocols such as TCP / IP or Http to obtain the corresponding real-time data.

[0067] It is also possible to receive and decode in real time product data streams such as broadcast ephemeris, orbit corrections, clock corrections, pseudorange bias corrections, phase bias corrections, etc., as well as real-time GNSS base station observation data streams based on the RTCM protocol;

[0068] Among them, the real-time orbital clock error and the ambiguity correction of the pseudorange phase deviation are encoded in the RTCMSC10403.3 format formulated by the Radio Technical Commission for Maritime services (RTCM). Generally, they are obtained through the Networked Transport of RTCM via Internet Protocol (Ntrip) in real time to access the corrections of the State Space Representation (SSR) of the IGS status parameters. The SSR corrections include satellite orbits, satellite clock errors, pseudorange deviations, phase deviations, etc. After receiving these corrections, the user can decode them according to the corresponding RTCM format and store the decoded corrections in the memory.

[0069] S2: Process the broadcast ephemeris and SSR corrections to obtain precise satellite orbits and precise satellite clock errors;

[0070] This step is mainly based on the broadcast ephemeris and, in combination with the satellite age parameters corresponding to various SSR corrections in step S1, the SSR corrections in step S1 can be combined with the calculated values of the broadcast ephemeris to form real-time precise satellite orbits and clock errors.

[0071] When using real-time SSR corrections to restore high-precision satellite orbits and clock errors, it is first necessary to match the broadcast ephemeris parameters with the SSR corrections. For GPS satellites and Galileo satellites, the IODE parameters can be directly used for matching. For BDS satellites, 24-bit cyclic redundancy check code (CRC) needs to be generated using 3 satellite clock error parameters and 15 ephemeris parameters in the broadcast ephemeris to obtain the issue of data ephemeris (IODE). For GLONASS satellites, the corresponding IODE parameters need to be generated through the Time of clock (TOC) parameter for matching, and the calculation formula is as follows:

[0072] IODE = int(mod(T oc + 10800, 86400) / 900 + 0.5);

[0073] The orbital corrections in the real-time SSR corrections are the correction amounts of the satellite's position and velocity in the radial, along-track, and cross-track directions. For any moment t, the calculation formula for the orbital corrections in the SSR corrections is:

[0074]

[0075] In the above formula, δorb is the vector of the orbital correction in the orbital plane coordinate system; δorb r 、δorb a 、δorb c respectively represent the components of the orbital correction in the radial, tangential, and normal directions at the reference time t0, with the unit of m; respectively represent the rates of change of the orbital correction in the radial, tangential, and normal directions, with the unit of m / s;

[0076] Convert the orbital correction from the orbital plane coordinate system to the Earth-fixed coordinate system. The conversion formula is:

[0077]

[0078] In the above formula, [X Y Z] T is the satellite coordinate corrected by the orbital correction, that is, the precise satellite orbit; [X brd Y brd Z brd T is the satellite coordinate calculated using the broadcast ephemeris; e r 、e a 、e c are the unit vectors of the satellite's radial, tangential, and normal vectors in the Earth-fixed coordinate system respectively;

[0079] The clock correction provided in the SSR correction is the correction amount relative to the clock difference calculated from the broadcast ephemeris. The precise satellite clock difference corrected by the clock correction is expressed as:

[0080] δClk = a0 + a1(t - t0) + a2(t - t0) 2 ;

[0081]

[0082] In the above formula, δClk is the satellite clock correction calculated based on the SSR correction; a0, a1, and a2 are the constant term, first-order term, and second-order term coefficients of the clock correction respectively; dClk p is the precise satellite clock difference; dClk brd is the satellite clock difference calculated through the broadcast ephemeris; δClk is the satellite clock correction calculated based on the SSR correction; c is the speed of light.

[0083] S3: Process the original observation data, precise satellite orbit, and precise satellite clock difference to obtain the non-differenced floating-point ambiguity of the original frequency point;

[0084] Construct a non-differenced and non-combined PPP positioning model, perform PPP floating-point solution calculation based on the precise satellite orbit and precise satellite clock difference restored in step S2, and obtain the non-differenced floating-point ambiguity of the original frequency point; ​

[0085] Taking the L1 and L2 frequency observations as an example, the pseudo-range and phase observations of the satellite at the station in terms of frequency are expressed as follows:

[0086]

[0087] In the above formula, and represent the pseudo-range observation value and the phase observation value respectively; represents the geometric distance, which is calculated from the precise satellite orbit restored in step S2 and the approximate coordinates of the user receiver; dt r represents the receiver clock error; dt s represents the satellite clock error, that is, the precise satellite clock error restored in step S2; M s and zwd r represent the tropospheric mapping function and the zenith tropospheric delay respectively; and represent the ionospheric mapping factor and the ionospheric delay at the first frequency respectively; b r,i and represent the pseudo-range hardware delays at the receiver end and the satellite end at frequency i respectively; d r,i and represent the phase hardware delays at the receiver end and the satellite end at frequency i respectively; λ i and represent the wavelength and the undifferenced integer ambiguity of the phase observation at frequency i respectively; represents the error and the pseudo-range observation noise at frequency i, represents the error and the phase observation noise at frequency i, where the error includes multipath error, antenna phase center error PCO (Phase Center Offset), antenna phase center variation PCV (PhaseCenter Variation), solid tide, ocean tide, polar tide, and relativistic effect error;

[0088] The unknown parameters involved in the above formula are estimated by classical Kalman filtering. The unknown parameters are the corrections of the approximate coordinates of the user receiver, the receiver clock error, the zenith tropospheric delay, the ionospheric delay, and the undifferenced integer ambiguity; among them, the undifferenced ambiguity parameter is generally estimated as a random walk parameter, and its process noise can be set to

[0089] S4: Process the undifferenced floating-point ambiguity of the original frequency points to obtain the fixed integer inter-satellite single-difference wide-lane ambiguity;

[0090] This step mainly calculates the floating wide-lane ambiguities of each satellite based on step S3, selects the satellite with the highest elevation angle as the reference satellite, uses the inter-satellite single-difference method to eliminate the wide-lane UPD at the receiver end, corrects the wide-lane UPD at the satellite end using the received satellite phase deviation correction, and fixes the wide-lane ambiguity by rounding; specifically as follows:

[0091] The non-differenced wide-lane ambiguity of the satellite is obtained through non-differenced integer ambiguity combination, and the formula is:

[0092]

[0093] is the non-differenced wide-lane ambiguity of the satellite; represents the non-differenced integer ambiguity at frequency j;

[0094] The wide-lane UPD at the receiver end is eliminated through the inter-satellite single-difference method to fix the wide-lane ambiguity, and the formula is:

[0095]

[0096] In the above formula, ΔN WL is the fixed inter-satellite single-difference wide-lane ambiguity, and are the wide-lane ambiguities of two different satellites, and S ref is the reference satellite, selected from the satellite with the highest elevation angle;

[0097] Among them, those that satisfy the difference from the integer cycle within 0.2 cycles are directly rounded to an integer, which is the integer solution of the fixed integer inter-satellite single-difference wide-lane ambiguity, and the formula is:

[0098]

[0099] In the above formula, is the integer inter-satellite single-difference wide-lane ambiguity.

[0100] In this step, if it does not meet the condition, the wide-lane ambiguity is not fixed and remains the floating wide-lane ambiguity.

[0101] S5: Process the integer inter-satellite single-difference wide-lane ambiguity to obtain the optimized original frequency non-differenced ambiguity; process the integer inter-satellite single-difference wide-lane ambiguity and the optimized original frequency non-differenced ambiguity to obtain the floating inter-satellite single-difference narrow-lane ambiguity;

[0102] Based on the wide-lane ambiguity, a virtual observation equation is constructed to re-filter and solve the PPP positioning model to optimize the original frequency non-differenced ambiguity, and the formula is:

[0103]

[0104] In the above formula, ll represents the virtual observation equation constructed based on the wide-lane ambiguity, is the inter-satellite single-difference wide-lane ambiguity fixed in step S4, and respectively represent the original frequency-point undifferenced floating ambiguities calculated at frequencies i and j according to step S3;

[0105] In the above formula, respectively represent the pseudorange observation value and the phase observation value at any frequency; respectively represent the ionospheric mapping factor and the ionospheric delay at any frequency; respectively represent the pseudorange hardware delays at the receiver end and the satellite end at any frequency; respectively represent the phase hardware delays at the receiver end and the satellite end at any frequency; respectively represent the wavelength and the undifferenced integer ambiguity of the phase observation value at any frequency; represents the error and the pseudorange observation noise at any frequency; represents the error and the phase observation noise at any frequency.

[0106] This step adds a constraint scheme based on the wide-lane fixed solution, which can refine the extracted narrow-lane ambiguity, accelerate the PPP convergence speed, and improve the success rate of ambiguity fixing.

[0107] S6: Use the BIE method to process all the floating inter-satellite single-difference narrow-lane ambiguity parameters to obtain the fixed integer inter-satellite single-difference narrow-lane ambiguity;

[0108] Using the BIE method to process all the floating inter-satellite single-difference narrow-lane ambiguity parameters is for fixing. The BIE ambiguity fixing method is:

[0109]

[0110] In the above formula, is the integer solution of the inter-satellite difference narrow-lane ambiguity fixed based on the BIE method, is the inter-satellite difference floating narrow-lane ambiguity calculated in step S5, z is any set of n-dimensional integer vectors searched; Q is the covariance of the inter-satellite difference narrow-lane ambiguity;

[0111] Then, a reliability check is performed on the integer solution of the inter-satellite difference narrow-lane ambiguity fixed based on the BIE method. The reliability check criterion is the optimal integer aperture check method:

[0112]

[0113] In the above formula, OIA refers to the check value, c p takes 0.95; refers to the floating ambiguity.

[0114] S7: Select the full set of ambiguities according to the accuracy index of the floating-point narrow-lane ambiguity, and iteratively obtain the ambiguity subset that meets the optimal aperture check criterion.

[0115] The execution process of the iteration includes:

[0116] S701: Arrange the ambiguity subset to be fixed in descending order according to the variance size;

[0117] S702: Try to fix all the narrow-lane ambiguities using the BIE method. If the ambiguity fixing reliability check cannot be passed, remove the ambiguity with the largest variance and continue to repeat BIE until the number of remaining ambiguities is less than half of the total number of ambiguities;

[0118] S703: If the number of ambiguities that pass the ambiguity fixing reliability test is greater than half of the total number of ambiguities, it is considered that the ambiguity fixing is successful.

[0119] S8: Use the successfully fixed narrow-lane ambiguities as pseudo-observations to constrain the PPP floating solution, and update the filtered solution to obtain the PPP parameter solution with fixed ambiguities.

[0120] As described above, it is only the preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention, according to the technical solution of the present invention and its inventive concept, makes equivalent substitutions or changes, and all should be covered within the protection scope of the present invention.

Claims

1. A method for GNSS real-time precise point positioning ambiguity fixing in complex environments It is characterized in that: The method includes the following steps: S1: Obtain the original observation data, broadcast ephemeris, and SSR corrections; S2: Process the broadcast ephemeris and SSR corrections to obtain precise satellite orbits and precise satellite clock biases; S3: Process the original observation data, precise satellite orbits, and precise satellite clock biases to obtain the original frequency non-differenced floating-point ambiguities; S4: Process the original frequency non-differenced floating-point ambiguities to obtain fixed integer inter-satellite wide-lane ambiguities; S5: Process the integer inter-satellite wide-lane ambiguities to obtain optimized original frequency non-differenced ambiguities; process the integer inter-satellite wide-lane ambiguities and the optimized original frequency non-differenced ambiguities to obtain floating-point inter-satellite narrow-lane ambiguities; S6: Use the BIE method to process all the floating-point inter-satellite narrow-lane ambiguity parameters to obtain fixed integer inter-satellite narrow-lane ambiguities; S7: Select the full set of ambiguities according to the accuracy index of the floating-point narrow-lane ambiguities, and iteratively obtain an ambiguity subset that meets the optimal aperture checking criterion.

2. The method for GNSS real-time precise single-point positioning ambiguity fixing in complex environments according to claim 1, characterized in that : Step S2 includes: For any time t, the formula for the orbit correction number in the SSR correction is: In the above formula, δorb is the vector of the orbital correction in the orbital plane coordinate system; δorb r , δorb a , δorb c respectively represent the components of the orbital correction in the radial, tangential, and normal directions at the reference time t0, with the unit of m; respectively represent the rates of change of the orbital correction in the radial, tangential, and normal directions, with the unit of m / s; Convert the orbit correction number from the orbital plane coordinate system to the geodetic coordinate system, and the conversion formula is: In the above formula, [X Y Z] T is the satellite coordinates corrected by the orbit correction, that is, the precise satellite orbit; [X brd Y brd Z brd T is the satellite coordinates calculated using the broadcast ephemeris; e r , e a , e c are the unit vectors of the satellite radial, tangential, and normal vectors in the earth-fixed coordinate system, respectively;​ The clock bias correction provided in the SSR correction is the correction amount relative to the clock bias calculated from the broadcast ephemeris. The precise satellite clock bias corrected by the clock bias correction is expressed as: δClk = a0 + a1(t - t0) + a2(t - t0) 2 ; In the above formula, δClk is the satellite clock error correction calculated based on the SSR correction; a0, a1, and a2 are the constant term, first-order term, and second-order term coefficients of the clock error correction, respectively; dClk p is the precise satellite clock error; dClk brd is the satellite clock error calculated through the broadcast ephemeris; δClk is the satellite clock error correction calculated based on the SSR correction; c is the speed of light.

3. The method for GNSS real-time precise single-point positioning ambiguity fixing in complex environments according to claim 2, characterized in that : Step S3 includes: Construct a non-differenced and non-combined PPP positioning model, perform PPP floating-point solution calculation based on the precise satellite orbits and precise satellite clock biases restored in step S2, and obtain the original frequency non-differenced floating-point ambiguities; Taking the L1 and L2 frequency observations as an example, the pseudo-range and phase observations of the satellite by the station at the frequency are expressed as: In the above formula, and respectively represent the pseudorange observation value and the phase observation value; represents the geometric distance, which is calculated from the precise satellite orbit recovered in step S2 and the approximate coordinates of the user receiver; dt r represents the receiver clock error; dt s represents the satellite clock error, which is the precise satellite clock error recovered in step S2; M s and zwd r respectively represent the tropospheric mapping function and the zenith tropospheric delay; and respectively represent the ionospheric mapping factor and the ionospheric delay at the first frequency; b r,i and respectively represent the pseudorange hardware delays at the receiver end and the satellite end at frequency i; d r,i and respectively represent the phase hardware delays at the receiver end and the satellite end at frequency i; λ i and respectively represent the wavelength and the non-differenced integer ambiguity of the phase observation value at frequency i; represents the error and the pseudorange observation noise at frequency i, represents the error and the phase observation noise at frequency i, where the error includes multipath error, antenna phase center error PCO, antenna phase center variation PCV, solid tide, ocean tide, pole tide, and relativistic effect error; The unknown parameters involved in the above formula are estimated using the classical Kalman filter. The unknown parameters are the corrections of the approximate coordinates of the user receiver, the receiver clock bias, the zenith tropospheric delay, the ionospheric delay, and the non-differenced integer ambiguity.

4. The method for GNSS real-time precise point positioning ambiguity fixing in complex environments according to claim 3, characterized in that : Step S4 includes: Obtain the satellite non-differenced wide-lane ambiguity by combining non-differenced integer ambiguities, and the formula is: is the undifferenced wide-lane ambiguity of the satellite; represents the undifferenced integer ambiguity at frequency j; Eliminate the wide-lane UPD at the receiver end through the inter-satellite single-difference method to fix the wide-lane ambiguity, and the formula is: In the above formula, ΔN WL is the fixed inter-satellite single-difference wide-lane ambiguity, and are the wide-lane ambiguities of two different satellites, and S ref is the reference satellite, selected from the satellite with the highest elevation angle; Among them, those with a difference from the integer cycle within 0.2 cycles are directly rounded to an integer, which is the integer solution of the fixed integer inter-satellite wide-lane ambiguity, and the formula is: In the above formula, is the integer inter-satellite single-difference wide-lane ambiguity.

5. The method for GNSS real-time precise single-point positioning ambiguity fixing in a complex environment according to claim 4, wherein : Step S5 includes: Re-filter and solve the PPP positioning model based on the wide-lane ambiguity to construct a virtual observation equation to optimize the original frequency non-differenced ambiguity, and the formula is: In the above formula, ll represents the virtual observation equation constructed based on the wide-lane ambiguity, which is the inter-satellite single-difference wide-lane ambiguity fixed in step S4, and respectively represent the original frequency-point undifferenced floating-point ambiguities calculated at frequencies i and j according to step S3; In the above formula, respectively represent the pseudorange observation value and the phase observation value at any frequency; γ * and respectively represent the ionospheric mapping factor and the ionospheric delay at any frequency; respectively represent the pseudorange hardware delays at the receiver end and the satellite end at any frequency; respectively represent the phase hardware delays at the receiver end and the satellite end at any frequency; λ * and respectively represent the wavelength and the non-differenced integer ambiguity of the phase observation value at any frequency; represents the error and the pseudorange observation noise at any frequency; represents the error and the phase observation noise at any frequency.

6. The method for GNSS real-time precise single-point positioning ambiguity fixing in complex environments according to claim 5, characterized in that : Step S6 includes: Using the BIE method to process all the floating-point inter-satellite narrow-lane ambiguity parameters is to perform fixing. The BIE ambiguity fixing method is: In the above formula, is the integer solution of the inter-satellite difference narrow-lane ambiguity fixed based on the BIE method, is the floating-point narrow-lane ambiguity of the inter-satellite difference calculated in step S5, z is any set of n-dimensional integer vectors searched; Q is the covariance of the inter-satellite difference narrow-lane ambiguity; Then perform reliability checking on the integer solution of the inter-satellite difference narrow-lane ambiguity fixed by the BIE method. The reliability checking criterion is the optimal integer aperture checking method: In the above formula, OIA refers to the verification value, and c p takes 0.95; refers to the floating-point ambiguity.

7. The method for GNSS real-time precise single-point positioning ambiguity fixation for complex environments according to claim 6, wherein : In step S7, the execution process of the iteration includes: S701: Arrange the ambiguity subset to be fixed in descending order according to the variance size; S702: Try to fix all the narrow-lane ambiguities using the BIE method. If the ambiguity fixing reliability check cannot be passed, then reject the ambiguity with the largest variance and repeat BIE until the number of remaining ambiguities is less than half of the total number of ambiguities. S703: If the number of ambiguities that pass the ambiguity fixing reliability check is greater than half of the total number of ambiguities, it is considered that the ambiguity fixing is successful.

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