A positioning method and system based on Beidou PPP-B2b

Abstract

The application discloses a positioning method and system based on Beidou PPP-B2b, and comprises the following steps: acquiring PPP-B2b orbit correction numbers broadcast by Beidou No.3 system geosynchronous orbit satellites; establishing a first full-network state space error estimation model of corresponding estimated parameters of satellite clock errors of multiple satellites, multiple satellites and multiple reference station servers according to the PPP-B2b orbit correction numbers; introducing reference constraints to the first full-network state space error estimation model, and redefining parameters to solve the satellite clock errors and the corresponding estimated parameters, so that positioning is performed according to the solved satellite clock errors. The application can quickly solve the satellite clock errors, improve the precision and reliability of the satellite clock errors, and realize wide-area real-time precise positioning.

Description

Technical Field

[0001] This invention relates to the field of global satellite navigation technology, and in particular to a positioning method and system based on BeiDou PPP-B2b. Background Technology

[0002] Wide-area real-time, high-precision positioning is a growing trend in the application of Global Navigation Satellite Systems (GNSS). The completion of the BeiDou-3 system, in particular, has spurred demand for real-time, high-precision GNSS positioning in emerging fields such as autonomous driving and precision agriculture in my country. Wide-area real-time precise positioning technology, based on wide-area differential positioning technology, generates high-precision real-time satellite orbit, clock bias, and ionospheric information through innovations in core technologies such as real-time precise orbit and clock bias of navigation satellites. Users then employ precise single-point positioning based on carrier phase observations to achieve wide-area dual-frequency real-time dynamic differential positioning with decimeter-level precision. Currently, the ultra-fast clock bias products provided by the International GNSS Service (IGS) have an accuracy of approximately 3ns, which cannot meet the demands of high-precision positioning.

[0003] One of the key technical challenges hindering wide-area real-time, high-precision positioning is the calculation of high-frequency precise clock bias. Methods for calculating satellite clock bias include three modes: non-differential, epoch-based differential, and hybrid epoch-based differential. The first mode typically uses ionospherically de-electro-dependent GNSS observations for non-differential calculation, resulting in floating-point ambiguities. The estimated satellite clock bias initially depends on the accuracy of pseudorange observations and changes in satellite geometry, requiring a certain amount of time for ambiguity convergence. The second mode, epoch-based differential, eliminates many ambiguity parameters and reduces ambiguity estimation time, but the initial satellite clock bias introduces satellite-related biases, leading to poor reliability of the final calculated clock bias. The third mode often relies on the accuracy of pseudorange observations, requiring continuous satellite observations in the initial stage. If satellite signal obstruction occurs during the calculation process, the clock bias needs to be re-initialized. Therefore, a method is urgently needed to calculate high-frequency precise satellite clock bias with fixed ambiguities to achieve wide-area real-time precise positioning. Summary of the Invention

[0004] The purpose of this invention is to address the shortcomings of the prior art by proposing a positioning method and system based on BeiDou PPP-B2b, aiming to achieve wide-area real-time precise positioning.

[0005] In a first aspect, the present invention provides a positioning method based on BeiDou PPP-B2b, the method comprising:

[0006] Obtain the PPP-B2b orbital correction data broadcast by the geostationary orbit satellites of the BeiDou-3 system;

[0007] Based on the PPP-B2b orbital corrections, a first full-network spatial error estimation model is established, which includes satellite clock errors of multiple satellites in multiple positioning systems, and the corresponding parameters to be estimated for multiple satellites and multiple reference station servers.

[0008] A baseline constraint is introduced into the first full-network spatial error estimation model, and the parameters are redefined to solve for the satellite clock error and the corresponding estimated parameter, so as to enable positioning based on the solved satellite clock error.

[0009] This invention utilizes PPP-B2b orbital corrections broadcast by geostationary orbit satellites of the BeiDou-3 system, reducing the additional costs associated with achieving real-time precise positioning. By employing reference constraints and redefining model parameters, it enables rapid calculation of satellite clock bias, improving the accuracy and reliability of satellite clock bias. Compared to differential and hybrid differential methods for calculating satellite clock bias, it achieves high-precision real-time positioning without introducing satellite reference bias or relying on pseudorange observation accuracy. The obtained time coordinate sequence can be used for positioning accuracy assessment. Furthermore, it can solve for corresponding parameters to be estimated without additional calculations, reducing computational load.

[0010] Furthermore, the step of introducing benchmark constraints into the first full-network spatial error estimation model and redefining the parameters to solve for the satellite clock error and the corresponding parameters to be estimated includes:

[0011] The pseudorange deviation of each frequency point is recombined with the first parameter to obtain the hardware delay deviation between the first frequency point observation value and the second frequency point observation value of the receiver and the satellite in turn.

[0012] Based on the hardware delay deviation between the receiver and the satellite, the satellite clock error and the corresponding parameters to be estimated in the first network-wide state space error estimation model are redefined to obtain the second network-wide state space error estimation model with ambiguity parameters having integer characteristics.

[0013] The floating-point solutions of the ambiguity parameters with integer characteristics are searched to obtain fixed ambiguity solutions. Based on the fixed ambiguity solutions, the satellite clock bias and the corresponding parameters to be estimated are calculated.

[0014] This invention employs benchmark constraints and reorganizes model parameters to eliminate the correlation between the ionosphere, phase deviation, and ambiguity in the model, thereby reducing computational complexity and enabling rapid calculation of satellite clock bias when the ambiguity solution is fixed, thus improving the accuracy and reliability of satellite clock bias.

[0015] Furthermore, the pseudorange deviation at each frequency point is recombined using the first parameter to sequentially obtain the hardware delay deviation between the receiver's and satellite's first frequency point observations and the second frequency point observations, specifically as follows:

[0016] The pseudorange deviation at each frequency point is divided into frequency-dependent terms and frequency-independent terms, and the pseudorange deviations corresponding to the receiver and satellite are obtained respectively.

[0017] Based on the pseudorange deviation between the receiver and the satellite, the hardware delay deviation between the observation values ​​at the first frequency point and the observation values ​​at the second frequency point is calculated, thus obtaining the hardware delay deviation between the receiver and the satellite.

[0018] Furthermore, the step of redefining the satellite clock bias and corresponding estimated parameters in the first network-wide state-space error estimation model based on the hardware delay deviation between the receiver and the satellite includes:

[0019] Based on the hardware delay deviation between the receiver and the satellite, and using the ionosphere-free pseudorange deviation benchmark and hardware delay benchmark between the receiver and the satellite as the first benchmark constraint, the satellite clock error and the corresponding parameters to be estimated in the first whole network state space error estimation model are reorganized into the second parameter to obtain the third whole network state space error estimation model.

[0020] The reference station with the most observed satellites is taken as the core reference station. The receiver clock error of the core reference station and the multi-frequency hardware delay deviation of the corresponding receiver are used as the second reference constraint. The parameters in the third network state space error estimation model are redefined, and the fourth network state space error estimation model corresponding to each reference station is obtained in turn.

[0021] Based on the receiver carrier deviation and ambiguity corresponding to the core reference station as the third reference constraint, the satellite carrier deviation, receiver phase deviation of non-core reference stations, and ambiguity corresponding to non-core reference stations are redefined to obtain the fifth network-wide state space error estimation model for each reference station.

[0022] This invention employs multiple parameter recombinations to eliminate the correlation between parameters in the corresponding model. By using the parameters of the core reference station as a benchmark, the correlation between parameters of non-core reference stations is further eliminated. This reduces the computational complexity of positioning and the amount of computation, enabling the rapid solution of satellite clock bias in the final model and improving the accuracy of BeiDou PPP-B2b-based positioning, thereby enhancing the reliability of BeiDou PPP-B2b-based positioning.

[0023] Furthermore, following the fifth network-wide state-space error estimation model corresponding to each reference station, the following is also included:

[0024] Using the ambiguity of the first satellite at the initial epoch as the fourth benchmark constraint, the carrier bias and the corresponding ambiguity of the receiver of the non-core reference station are redefined to obtain the sixth network-wide state space error estimation model for the non-core base station.

[0025] Furthermore, after constructing the first state-space error estimation model for the entire network, the method further includes: converting the observation equations in the first state-space error estimation model for the entire network into a matrix representation for solving.

[0026] This invention transforms the carrier phase observation equation in the model into a matrix expression, which facilitates subsequent solution of satellite clock bias and determination of the number of parameters, reduces computational complexity and computational load, thereby enabling rapid solution of satellite clock bias in the final model and improving the accuracy of BeiDou PPP-B2b positioning.

[0027] Furthermore, the second whole-network state-space error estimation model is specifically as follows:

[0028] Based on the fifth network-wide state space error estimation model corresponding to the core reference station and the sixth network-wide state space error estimation model for each non-core base station, the number of parameters to be estimated and the number of reference constraints are determined, resulting in a second network-wide state space error estimation model with integer ambiguity parameters.

[0029] Furthermore, the positioning method based on BeiDou PPP-B2b searches for floating-point solutions with integer ambiguity using the LAMBDA algorithm to obtain a solution with fixed ambiguity.

[0030] Furthermore, it also includes: obtaining PPP-B2b orbital correction data broadcast by geostationary orbit satellites of the BeiDou-3 system;

[0031] Precise single-point positioning is performed based on the PPP-B2b orbital correction and the calculated satellite clock error to obtain the user's positioning coordinates. The user's positioning coordinates are then continuously observed to obtain a time coordinate sequence.

[0032] Based on the time coordinate sequence, the accuracy and reliability of satellite clock bias for positioning based on BeiDou PPP-B2b are evaluated.

[0033] Secondly, the present invention provides a positioning system based on BeiDou PPP-B2b, comprising:

[0034] The PPP-B2b orbit correction data acquisition module is used to acquire PPP-B2b orbit correction data broadcast by the geostationary orbit satellites of the BeiDou-3 system.

[0035] The model building module is used to build a first full-network spatial error estimation model based on the PPP-B2b orbit corrections, which includes the satellite clock errors of multiple satellites in multiple positioning systems, the corresponding parameters to be estimated of multiple satellites and multiple reference station servers.

[0036] The parameter calculation module is used to introduce benchmark constraints into the first full-network spatial error estimation model, redefine the parameters, and solve the satellite clock error and the corresponding estimated parameters so as to enable positioning based on the solved satellite clock error. Attached Figure Description

[0037] Figure 1 This is a positioning method based on BeiDou PPP-B2b provided in the embodiments of the present invention;

[0038] Figure 2 This is a schematic diagram of the interaction between the user terminal and the server terminal based on BeiDou PPP-B2b positioning provided in an embodiment of the present invention;

[0039] Figure 3 This is a schematic diagram of the structure of a positioning system based on BeiDou PPP-B2b provided in an embodiment of the present invention. Detailed Implementation

[0040] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0041] This invention proposes a method for high-frequency precise clock bias calculation based on BeiDou PPP-B2b. Using GNSS observation data from reference stations in the Asia-Pacific region, it receives orbit corrections from PPP-B2b signals broadcast by geostationary orbit satellites of the BeiDou-3 navigation system. Employing GNSS non-differential, non-combined observations and introducing external or internal reference constraints, it calculates high-frequency precise satellite clock bias under fixed ambiguity. The calculated high-frequency precise satellite clock bias is then broadcast to the user's reference station. The user can then achieve wide-area real-time precise positioning using the PPP-B2b orbit corrections and the broadcast ephemeris including the satellite clock bias. Figure 1 This is a positioning method based on BeiDou PPP-B2b provided in an embodiment of the present invention, including steps S11 to S13, specifically:

[0042] Step S11: Obtain the PPP-B2b orbit correction data broadcast by the geostationary orbit satellites of the BeiDou-3 system.

[0043] It is worth noting that the scope of the GNSS reference stations covers the Asia-Pacific region. The reference stations are divided into user-end and service-end stations. The user-end reference stations receive the calculated satellite clock bias results and simulate user positioning based on the satellite clock bias, allowing for preliminary verification of the accuracy of the satellite clock bias products using positioning coordinates. The service-end reference stations are used to calculate high-frequency satellite clock bias and corresponding parameters to be estimated. Specifically, a multi-system, network-wide state-space error estimation model is constructed based on the reference stations selected for satellite clock bias calculation at the service end. Furthermore, within the selected area, an additional receiver is set up to receive PPP-B2b orbit correction data broadcast by the BeiDou-3 system's geostationary orbit satellites.

[0044] Step S12: Based on the PPP-B2b orbital corrections, establish a first full-network spatial error estimation model that includes the satellite clock errors of multiple satellites in multiple positioning systems, the corresponding parameters to be estimated for multiple satellites and multiple reference station servers.

[0045] Preferably, the first whole-network state-space error estimation model can be expressed as:

[0046] (1)

[0047] (2)

[0048] Where the subscript k represents the receiver of the base station on the server side, which can be represented as: The subscript i represents the epoch, and the subscript s represents the satellite, which can be represented as: The subscript S represents the positioning system, and the subscript j represents the observable frequency of each system, which can be expressed as: Formulas (1) and (2) are the non-difference pseudorange equation and carrier phase observation equation of the reference station, respectively; , These represent the pseudorange observation and carrier phase observation at frequency j between satellite s and receiver k, respectively; This represents the geometric distance from the satellite to the phase center of the receiver antenna; , Indicates receiver clock bias and satellite clock bias; , These represent tropospheric delay and ionospheric delay, respectively. It is the frequency ratio. This represents the value of frequency j. This represents the value of frequency j; , These represent the hardware delays of the receiver and the satellite at frequency j, respectively. , These represent the carrier phase deviations of the receiver and the satellite at frequency j, respectively. It is the carrier wavelength at frequency j; It is the ambiguity of the non-difference phase integer at frequency j; Other modelable errors include: antenna phase center correction, antenna phase entanglement, relativistic effects, and tidal correction. The difference is corrected into the observed values ​​using an empirical model; , It represents the pseudorange observation value at frequency j and the phase observation noise; c represents the speed of light. For positioning systems, and These are the GPS and BDS constellation systems, respectively, with the number of positioning systems represented by M.

[0049] It is worth noting that since BeiDou PPP-B2b only broadcasts orbital correction data for the GPS and BDS systems, the state-space error estimation model for the entire network is only modeled for these two systems.

[0050] The process includes, after constructing the first state-space error estimation model for the entire network, converting the observation equations in the first state-space error estimation model into matrix representations for solving.

[0051] Preferably, the matrix representation is in the form of:

[0052] (3)

[0053] in, Represents the residual. The condition matrix, For the parameter to be estimated, For actual observed values, subscript This refers to the index of the parameter to be estimated. (Including...) 1-dimensional satellite clock bias And the corresponding parameters to be estimated, which include: 1D zenith tropospheric wet delay at each site This will be estimated as an unknown parameter in the future. 1D receiver clock bias , 1D satellite clock bias , 1D receiver pseudorange deviation at various frequencies , 1D satellite pseudorange deviation at various frequencies Among them, the pseudorange deviation of each frequency point of the receiver and the pseudorange deviation of each frequency point of the satellite are the corresponding hardware delays of the receiver and the satellite. 1D receiver carrier deviation at various frequency points , 1D satellite terminal carrier offset at various frequency points , 1D Ionospheric Delay of Each Satellite at Each Reference Station in the Inclination Direction ,as well as 1D Ambiguity at Each Frequency Point The dimension of the matrix is In formula (3), there are related problems with parameters such as ionosphere, phase deviation and ambiguity. It is necessary to introduce external reference or redefine the parameters to eliminate rank deficiency and solve satellite clock error and corresponding parameters to be estimated.

[0054] This invention transforms the carrier phase observation equation in the model into a matrix expression, which facilitates subsequent solution of satellite clock bias and determination of the number of parameters, reduces computational complexity and computational load, thereby enabling rapid solution of satellite clock bias in the final model and improving the accuracy of BeiDou PPP-B2b positioning.

[0055] Step S13: Introduce benchmark constraints to the first full-network spatial error estimation model and redefine the parameters, solve for the satellite clock error and the corresponding estimated parameters, so as to enable positioning based on the solved satellite clock error.

[0056] The process of introducing benchmark constraints into the first full-network spatial error estimation model, redefining parameters, solving for the satellite clock error and the corresponding parameters to be estimated, and obtaining the second full-network spatial error estimation model after parameter solving includes steps S121 to S123, specifically:

[0057] Step S121: Perform first parameter recombination on the pseudorange deviation of each frequency point to obtain the hardware delay deviation between the first frequency point observation value and the second frequency point observation value of the receiver and the satellite.

[0058] Specifically, the pseudorange deviation at each frequency point is divided into frequency-dependent terms and frequency-independent terms, and the pseudorange deviations corresponding to the receiver and the satellite are obtained respectively. Based on the pseudorange deviations corresponding to the receiver and the satellite, the hardware delay deviation between the observation values ​​at the first frequency point and the observation values ​​at the second frequency point is calculated, and the hardware delay deviations corresponding to the receiver and the satellite are obtained.

[0059] Preferably, the pseudorange bias of the satellite and the receiver can be expressed as follows:

[0060] (4)

[0061] (5)

[0062] Preferably, based on the pseudorange deviation between the satellite and the receiver, the corresponding hardware delay deviations between the receiver and the satellite can be expressed as follows:

[0063] (6) (7)

[0064] This invention employs a reorganization of model parameters, which can eliminate the correlation between the ionosphere, phase deviation, and ambiguity in the model, reduce computational complexity, and enable rapid calculation of satellite clock bias when the ambiguity solution is fixed, thereby improving the accuracy and reliability of satellite clock bias.

[0065] Step S122: Based on the hardware delay deviation between the receiver and the satellite, redefine the satellite clock error and the corresponding parameters to be estimated in the first whole-network state space error estimation model to obtain the second whole-network state space error estimation model with ambiguity parameters having integer characteristics.

[0066] Specifically, steps S221-S223, which involve redefining the satellite clock bias and corresponding parameters to be estimated in the first network-wide state space error estimation model based on the hardware delay deviation between the receiver and the satellite, are as follows:

[0067] Step S221: Based on the hardware delay deviation between the receiver and the satellite, and using the ionosphere-free pseudorange deviation benchmark and hardware delay benchmark between the receiver and the satellite as the first benchmark constraint, the satellite clock error and the corresponding estimated parameters in the first whole network state space error estimation model are reorganized into a second parameter to obtain the third whole network state space error estimation model.

[0068] Preferably, after recombining the satellite clock errors and corresponding estimated parameters in the first network-wide state-space error estimation model using the second parameter, it can be expressed as:

[0069] (8)

[0070] (9)

[0071] (10)

[0072] (11)

[0073] (12)

[0074] in, and These are the receiver clock bias and satellite clock bias after parameter recombination, respectively. , and denoted as ionospheric delay, carrier phase deviation of the receiver and satellite at frequency j, respectively, and c is an intermediate parameter introduced by recombining the parameters of the receiver clock bias and the satellite clock bias.

[0075] Preferably, the third whole-network state-space error estimation model can be expressed as:

[0076] (13)

[0077] (14)

[0078] (15)

[0079] In particular, since there is a correlation between receiver clock bias and satellite clock bias in the third state space error estimation model of the whole network, and there is also a correlation between receiver pseudorange bias and satellite pseudorange bias, it is necessary to eliminate the correlation in the third state space error estimation model of the whole network in order to make calculations.

[0080] Step S222: Taking the reference station with the most observed satellites as the core reference station, and using the receiver clock error of the core reference station and the multi-frequency hardware delay deviation of the corresponding receiver as the second reference constraint, redefine the parameters in the third whole network state space error estimation model, and obtain the fourth whole network state space error estimation model corresponding to each reference station in sequence.

[0081] Since there is a lack of external time reference, the station with the most observed satellites is selected as the core base station. The receiver clock error and receiver multi-frequency hardware delay deviation of the core base station are defined as the benchmark constraints to eliminate the correlation in the second network state space error estimation model. The observation frequency is greater than or equal to 3.

[0082] Preferably, using the receiver clock bias of the core reference station and the multi-frequency hardware delay deviation of the corresponding receiver as the second reference constraint, the parameters in the third network-wide state-space error estimation model are redefined, which can be expressed as:

[0083] (16)

[0084] (17)

[0085] (18)

[0086] (19)

[0087] (20)

[0088] Preferably, based on the redefined parameters, the fourth network-wide state-space error estimation model corresponding to the core reference station can be expressed as:

[0089] ,(twenty one)

[0090] ,(twenty two)

[0091] .(twenty three)

[0092] Preferably, based on the redefined parameters, the fourth network-wide state-space error estimation model corresponding to the non-core reference stations can be expressed as:

[0093] , (twenty four)

[0094] (25)

[0095] (26)

[0096] In particular, since the receiver carrier deviation of the core reference station is related to the satellite carrier deviation and ambiguity in the fourth network state space error estimation model, it is necessary to eliminate this correlation.

[0097] Step S223: Based on the receiver carrier deviation and ambiguity corresponding to the core reference station as the third reference constraint, redefine the satellite carrier deviation, receiver phase deviation of non-core reference stations, and ambiguity corresponding to non-core reference stations, and sequentially obtain the fifth network-wide state space error estimation model corresponding to each reference station.

[0098] Preferably, the satellite carrier offset, non-core site receiver phase offset, and ambiguity are redefined as follows:

[0099] (27)

[0100] (28)

[0101] (29)

[0102] Preferably, the carrier phase observation equations of the fifth network-wide state-space error estimation model for the core base station carrier and non-core base stations after reparameterization can be expressed as follows:

[0103] (30)

[0104] (31)

[0105] The fifth network-wide state space error estimation model corresponding to each reference station is further included as follows: using the ambiguity of the first satellite in the initial epoch as the fourth reference constraint, the carrier deviation of the receiver of the non-core reference station and the ambiguity corresponding to the receiver are redefined to obtain the sixth network-wide state space error estimation model of the non-core base station.

[0106] Preferably, the redefined carrier bias and ambiguity of the receiver can be expressed as:

[0107] (32)

[0108] (33)

[0109] Preferably, based on the redefined receiver carrier bias and ambiguity, the carrier phase observation equation of the sixth network-wide state-space error estimation model for non-core base stations can be expressed as:

[0110] (34)

[0111] Among them, by defining each benchmark constraint, the number of parameters to be estimated is: The number of benchmarks is Finally, based on the obtained carrier phase observation equation, the ambiguity parameter with integer characteristics can be obtained.

[0112] This invention employs multiple parameter recombinations to eliminate the correlation between parameters in the corresponding model. By using the parameters of the core reference station as a benchmark, the correlation between parameters of non-core reference stations is further eliminated. This reduces the computational complexity of positioning and the amount of computation, enabling the rapid solution of satellite clock bias in the final model and improving the accuracy of BeiDou PPP-B2b-based positioning, thereby enhancing the reliability of BeiDou PPP-B2b-based positioning.

[0113] Specifically, the second whole-network state-space error estimation model is as follows:

[0114] Based on the fifth network-wide state space error estimation model corresponding to the core reference station and the sixth network-wide state space error estimation model for each non-core base station, the number of parameters to be estimated and the number of reference constraints are determined, resulting in a second network-wide state space error estimation model with integer ambiguity parameters.

[0115] Step S123: Search for the floating-point solution of the ambiguity parameter with integer characteristics to obtain the fixed ambiguity solution. Based on the fixed ambiguity solution, calculate the satellite clock error and the corresponding parameter to be estimated.

[0116] Preferably, the floating-point solution with integer ambiguity is searched using the LAMBDA algorithm to obtain a solution with fixed ambiguity.

[0117] Based on the calculated satellite clock bias, the user terminal can perform precise point positioning. Furthermore, based on the continuous positioning coordinates of the user terminal, the accuracy and reliability of the satellite clock bias for positioning based on BeiDou PPP-B2b are evaluated. Specifically: the user terminal obtains PPP-B2b orbit corrections broadcast by geostationary orbit satellites of the BeiDou-3 system; precise point positioning is performed based on the PPP-B2b orbit corrections and the calculated satellite clock bias to obtain the user terminal's positioning coordinates, and the user terminal's positioning coordinates are continuously observed to obtain a time coordinate sequence; based on the time coordinate sequence, the accuracy and reliability of the satellite clock bias for positioning based on BeiDou PPP-B2b are evaluated.

[0118] Furthermore, the calculated parameters can be applied to relevant fields, including: ionospheric parameters can be used for atmospheric modeling, saving the step of calculating the corresponding parameters and reducing computational load.

[0119] This invention utilizes PPP-B2b orbital corrections broadcast by geostationary orbit satellites of the BeiDou-3 system, reducing the additional costs associated with achieving real-time precise positioning. By employing reference constraints and redefining model parameters, it enables rapid calculation of satellite clock bias, improving the accuracy and reliability of satellite clock bias. Compared to differential and hybrid differential methods for calculating satellite clock bias, it achieves high-precision real-time positioning without introducing satellite reference bias or relying on pseudorange observation accuracy. The obtained time coordinate sequence can be used for positioning accuracy assessment. Furthermore, it can solve for corresponding parameters to be estimated without additional calculations, reducing computational load.

[0120] This invention also provides a complete flowchart of the user terminal and server terminal based on BeiDou PPP-B2b positioning, see [link / reference]. Figure 2 This is a schematic diagram of the interaction process between the user terminal and the server terminal based on BeiDou PPP-B2b positioning provided in an embodiment of the present invention.

[0121] See Figure 3 This is a schematic diagram of the positioning system based on BeiDou PPP-B2b provided in an embodiment of the present invention, including: PPP-B2b orbit correction data acquisition module 31, model establishment module 32, and parameter calculation module 33.

[0122] The PPP-B2b orbit correction data acquisition module 31 is used to acquire the PPP-B2b orbit correction data broadcast by the geosynchronous orbit satellites of the BeiDou-3 system.

[0123] The model building module 32 is used to build a first full-network spatial error estimation model based on the PPP-B2b orbital corrections, which includes the satellite clock errors of multiple satellites in multiple positioning systems, the corresponding parameters to be estimated of multiple satellites and multiple reference station servers.

[0124] It is worth noting that since BeiDou PPP-B2b only broadcasts orbital correction data for the GPS and BDS systems, the state-space error estimation model for the entire network is only modeled for these two systems.

[0125] The process includes, after constructing the first state-space error estimation model for the entire network, converting the observation equations in the first state-space error estimation model into matrix representations for solving.

[0126] This invention transforms the carrier phase observation equation in the model into a matrix expression, which facilitates subsequent solution of satellite clock bias and determination of the number of parameters, reduces computational complexity and computational load, thereby enabling rapid solution of satellite clock bias in the final model and improving the accuracy of BeiDou PPP-B2b positioning.

[0127] The parameter calculation module 33 is used to introduce benchmark constraints into the first full-network spatial error estimation model, redefine the parameters, and solve the satellite clock error and the corresponding estimated parameter so as to enable positioning based on the solved satellite clock error.

[0128] The parameter calculation module 33, which introduces benchmark constraints into the first full-network spatial error estimation model and redefines the parameters, solves for the satellite clock error and the corresponding parameters to be estimated, to obtain the second full-network spatial error estimation model after parameter solving, includes steps S121~S123, specifically:

[0129] Step S121: Perform first parameter recombination on the pseudorange deviation of each frequency point to obtain the hardware delay deviation between the first frequency point observation value and the second frequency point observation value of the receiver and the satellite.

[0130] Specifically, the pseudorange deviation at each frequency point is divided into frequency-dependent terms and frequency-independent terms, and the pseudorange deviations corresponding to the receiver and the satellite are obtained respectively. Based on the pseudorange deviations corresponding to the receiver and the satellite, the hardware delay deviation between the observation values ​​at the first frequency point and the observation values ​​at the second frequency point is calculated, and the hardware delay deviations corresponding to the receiver and the satellite are obtained.

[0131] This invention employs a reorganization of model parameters, which can eliminate the correlation between the ionosphere, phase deviation, and ambiguity in the model, reduce computational complexity, and enable rapid calculation of satellite clock bias when the ambiguity solution is fixed, thereby improving the accuracy and reliability of satellite clock bias.

[0132] Step S122: Based on the hardware delay deviation between the receiver and the satellite, redefine the satellite clock error and the corresponding parameters to be estimated in the first whole-network state space error estimation model to obtain the second whole-network state space error estimation model with ambiguity parameters having integer characteristics.

[0133] Specifically, steps S221-S223, which involve redefining the satellite clock bias and corresponding parameters to be estimated in the first network-wide state space error estimation model based on the hardware delay deviation between the receiver and the satellite, are as follows:

[0134] Step S221: Based on the hardware delay deviation between the receiver and the satellite, and using the ionosphere-free pseudorange deviation benchmark and hardware delay benchmark between the receiver and the satellite as the first benchmark constraint, the satellite clock error and the corresponding estimated parameters in the first whole network state space error estimation model are reorganized into a second parameter to obtain the third whole network state space error estimation model.

[0135] In particular, since there is a correlation between receiver clock bias and satellite clock bias in the third state space error estimation model of the whole network, and there is also a correlation between receiver pseudorange bias and satellite pseudorange bias, it is necessary to eliminate the correlation in the third state space error estimation model of the whole network in order to make calculations.

[0136] Step S222: Taking the reference station with the most observed satellites as the core reference station, and using the receiver clock error of the core reference station and the multi-frequency hardware delay deviation of the corresponding receiver as the second reference constraint, redefine the parameters in the third whole network state space error estimation model, and obtain the fourth whole network state space error estimation model corresponding to each reference station in sequence.

[0137] It is worth noting that, due to the lack of an external time reference, a station with the most observed satellites is selected as the core base station. The receiver clock bias and receiver multi-frequency hardware delay deviation of the core base station are defined as benchmark constraints to eliminate the correlation in the second network-wide state-space error estimation model, where the observation frequency is greater than or equal to 3. In the fourth network-wide state-space error estimation model, the receiver carrier bias of the core reference station is correlated with the satellite carrier bias and ambiguity, and this correlation needs to be eliminated.

[0138] Step S223: Based on the receiver carrier deviation and ambiguity corresponding to the core reference station as the third reference constraint, redefine the satellite carrier deviation, receiver phase deviation of non-core reference stations, and ambiguity corresponding to non-core reference stations, and sequentially obtain the fifth network-wide state space error estimation model corresponding to each reference station.

[0139] Following the fifth network-wide state-space error estimation model corresponding to each reference station, the following is also included:

[0140] Using the ambiguity of the first satellite at the initial epoch as the fourth benchmark constraint, the carrier bias and the corresponding ambiguity of the receiver of the non-core reference station are redefined to obtain the sixth network-wide state space error estimation model for the non-core base station.

[0141] By defining each benchmark constraint, the number of parameters to be estimated is... The number of benchmarks is Finally, based on the obtained carrier phase observation equation, the ambiguity parameter with integer characteristics can be obtained.

[0142] This invention employs multiple parameter recombinations to eliminate the correlation between parameters in the corresponding model. By using the parameters of the core reference station as a benchmark, the correlation between parameters of non-core reference stations is further eliminated. This reduces the computational complexity of positioning and the amount of computation, enabling the rapid solution of satellite clock bias in the final model and improving the accuracy of BeiDou PPP-B2b-based positioning, thereby enhancing the reliability of BeiDou PPP-B2b-based positioning.

[0143] Specifically, the second whole-network state-space error estimation model is as follows:

[0144] Based on the fifth network-wide state space error estimation model corresponding to the core reference station and the sixth network-wide state space error estimation model for each non-core base station, the number of parameters to be estimated and the number of reference constraints are determined, resulting in a second network-wide state space error estimation model with integer ambiguity parameters.

[0145] Step S123: Search for the floating-point solution of the ambiguity parameter with integer characteristics to obtain the fixed ambiguity solution. Based on the fixed ambiguity solution, calculate the satellite clock error and the corresponding parameter to be estimated.

[0146] It is worth noting that, based on the calculated satellite clock bias, the user terminal can perform precise point positioning, and the accuracy and reliability of the satellite clock bias for positioning based on BeiDou PPP-B2b can be evaluated based on the continuous positioning coordinates of the user terminal. Specifically: the user terminal obtains the PPP-B2b orbit correction numbers broadcast by the geostationary orbit satellites of the BeiDou-3 system; precise point positioning is performed based on the PPP-B2b orbit correction numbers and the calculated satellite clock bias to obtain the positioning coordinates of the user terminal, and the positioning coordinates of the user terminal are continuously observed to obtain a time coordinate sequence; based on the time coordinate sequence, the accuracy and reliability of the satellite clock bias for positioning based on BeiDou PPP-B2b are evaluated; and the corresponding estimated parameters calculated simultaneously can be further applied to corresponding fields, including: the ionospheric parameters among the estimated parameters can be used for atmospheric modeling.

[0147] This invention utilizes PPP-B2b orbital corrections broadcast by geostationary orbit satellites of the BeiDou-3 system, reducing the additional costs associated with achieving real-time precise positioning. By employing reference constraints and redefining model parameters, it enables rapid calculation of satellite clock bias, improving the accuracy and reliability of satellite clock bias. Compared to differential and hybrid differential methods for calculating satellite clock bias, it achieves high-precision real-time positioning without introducing satellite reference bias or relying on pseudorange observation accuracy. The obtained time coordinate sequence can be used for positioning accuracy assessment. Furthermore, it can solve for corresponding parameters to be estimated without additional calculations, reducing computational load.

[0148] Those skilled in the art will understand that embodiments of this application may also include computer program products. Therefore, this application may take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application may take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0149] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0150] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0151] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0152] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the technical principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A positioning method based on BeiDou PPP-B2b, characterized in that, The method includes: Obtain the PPP-B2b orbital correction data broadcast by the geostationary orbit satellites of the BeiDou-3 system; Based on the PPP-B2b orbital corrections, a first state-space error estimation model for the entire network is established, which includes satellite clock errors of multiple satellites in multiple positioning systems, and the corresponding parameters to be estimated for multiple satellites and multiple reference station servers. A baseline constraint is introduced into the first network-wide state space error estimation model, and the parameters are redefined. The satellite clock error and the corresponding estimated parameter are solved so that positioning can be performed based on the solved satellite clock error. The process of introducing benchmark constraints into the first network-wide state-space error estimation model and redefining the parameters to solve for the satellite clock bias and the corresponding parameters to be estimated includes: The pseudorange deviation of each frequency point is recombined with the first parameter to obtain the hardware delay deviation between the first frequency point observation value and the second frequency point observation value of the receiver and the satellite in turn. Based on the hardware delay deviation between the receiver and the satellite, the satellite clock error and the corresponding parameters to be estimated in the first network-wide state space error estimation model are redefined to obtain the second network-wide state space error estimation model with ambiguity parameters having integer characteristics. The floating-point solutions of the ambiguity parameters with integer characteristics are searched to obtain fixed ambiguity solutions. Based on the fixed ambiguity solutions, the satellite clock bias and the corresponding parameters to be estimated are calculated.

2. The positioning method based on BeiDou PPP-B2b as described in claim 1, characterized in that, The pseudorange deviation at each frequency point is recombined using the first parameter to obtain the hardware delay deviation between the receiver's and satellite's first frequency point observations and the second frequency point observations, specifically: The pseudorange deviation at each frequency point is divided into frequency-dependent terms and frequency-independent terms, and the pseudorange deviations corresponding to the receiver and satellite are obtained respectively. Based on the pseudorange deviation between the receiver and the satellite, the hardware delay deviation between the observation values ​​at the first frequency point and the observation values ​​at the second frequency point is calculated, thus obtaining the hardware delay deviation between the receiver and the satellite.

3. The positioning method based on BeiDou PPP-B2b as described in claim 1, characterized in that, The step of redefining the satellite clock bias and corresponding parameters to be estimated in the first network-wide state-space error estimation model based on the hardware delay deviation between the receiver and the satellite includes: Based on the hardware delay deviation between the receiver and the satellite, and using the ionosphere-free pseudorange deviation benchmark and hardware delay benchmark between the receiver and the satellite as the first benchmark constraint, the satellite clock error and the corresponding estimated parameters in the first whole network state space error estimation model are reorganized into the second parameter to obtain the third whole network state space error estimation model. The reference station with the most observed satellites is taken as the core reference station. The receiver clock error of the core reference station and the multi-frequency hardware delay deviation of the corresponding receiver are used as the second reference constraint. The parameters in the third network state space error estimation model are redefined, and the fourth network state space error estimation model corresponding to each reference station is obtained in turn. Based on the receiver carrier deviation and ambiguity corresponding to the core reference station as the third reference constraint, the satellite carrier deviation, receiver phase deviation of non-core reference stations and ambiguity corresponding to non-core reference stations are redefined, and the fifth network-wide state space error estimation model corresponding to each reference station is obtained in turn. Following the fifth network-wide state-space error estimation model corresponding to each reference station, the following is also included: Using the ambiguity of the first satellite in the initial epoch as the fourth benchmark constraint, the carrier bias and the corresponding ambiguity of the receiver of the non-core reference station are redefined to obtain the sixth network-wide state space error estimation model of the non-core base station. The second whole-network state-space error estimation model is as follows: Based on the fifth network-wide state space error estimation model corresponding to the core reference station and the sixth network-wide state space error estimation model for each non-core base station, the number of parameters to be estimated and the number of reference constraints are determined, resulting in a second network-wide state space error estimation model with integer ambiguity parameters.

4. The positioning method based on BeiDou PPP-B2b as described in claim 1, characterized in that, After constructing the first state-space error estimation model for the entire network, the method further includes: converting the observation equations in the first state-space error estimation model for the entire network into a matrix representation for solving.

5. The positioning method based on BeiDou PPP-B2b as described in claim 1, characterized in that, The LAMBDA algorithm is used to search for floating-point solutions with integer characteristics for ambiguity, thus obtaining solutions with fixed ambiguity.

6. The positioning method based on BeiDou PPP-B2b as described in claim 1, characterized in that, Also includes: Obtain the PPP-B2b orbital correction data broadcast by the geostationary orbit satellites of the BeiDou-3 system; Precise single-point positioning is performed based on the PPP-B2b orbital correction and the calculated satellite clock error to obtain the user's positioning coordinates. The user's positioning coordinates are then continuously observed to obtain a time coordinate sequence. Based on the time coordinate sequence, the accuracy and reliability of satellite clock bias for positioning based on BeiDou PPP-B2b are evaluated.

7. A positioning system based on BeiDou PPP-B2b, characterized in that, include: The PPP-B2b orbit correction data acquisition module is used to acquire PPP-B2b orbit correction data broadcast by the geostationary orbit satellites of the BeiDou-3 system. The model building module is used to build a first network-wide state space error estimation model based on the PPP-B2b orbit corrections, which includes satellite clock errors of multiple satellites in multiple positioning systems, and corresponding parameters to be estimated for multiple satellites and multiple reference station servers. The parameter calculation module is used to introduce benchmark constraints into the first whole network state space error estimation model, redefine the parameters, and solve the satellite clock error and the corresponding estimated parameter so as to enable positioning based on the solved satellite clock error. The parameter calculation module introduces benchmark constraints into the first network-wide state-space error estimation model and redefines the parameters to solve for the satellite clock error and the corresponding estimated parameters, including: The parameter calculation module performs a first parameter recombination on the pseudorange deviation of each frequency point, and sequentially obtains the hardware delay deviation between the first frequency point observation value and the second frequency point observation value of the receiver and the satellite. Based on the hardware delay deviation between the receiver and the satellite, the satellite clock error and the corresponding parameters to be estimated in the first network-wide state space error estimation model are redefined to obtain the second network-wide state space error estimation model with ambiguity parameters having integer characteristics. The floating-point solutions of the ambiguity parameters with integer characteristics are searched to obtain fixed ambiguity solutions. Based on the fixed ambiguity solutions, the satellite clock bias and the corresponding parameters to be estimated are calculated.

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