Method for generating network RTK differential correction based on integration of Beidou and low earth orbit constellation

Abstract

The application provides a network RTK differential correction number generation method based on Beidou and low-orbit constellation fusion, which comprises data acquisition, receiving pseudorange observation values and carrier phase observation values of Beidou satellite navigation system satellites and low-orbit constellation satellites through a ground reference station receiver simultaneously; constructing a joint observation model of Beidou satellite navigation system and low-orbit constellation, and using an extended Kalman filtering algorithm to estimate receiver clock difference and system bias between the two systems in real time; adaptive weighted differential correction number calculation, calculating pseudorange differential correction numbers of Beidou satellites and low-orbit satellites respectively based on the estimated system bias; correction number broadcasting, dynamically determining the effective duration of the differential correction number of the low-orbit satellite according to the orbit height of the low-orbit satellite, and encoding the correction numbers of the Beidou satellites and the low-orbit satellites into RTCM text format to broadcast to the user end; the user end receives the correction numbers, corrects the local Beidou satellite and low-orbit satellite observation values, performs joint RTK solving, and verifies and confirms ambiguity fixing.

Description

Technical Field

[0001] This invention relates to the field of satellite navigation and positioning technology, and in particular to a method for high-precision real-time differential positioning using a low-Earth orbit (LEO) communication constellation to enhance the BeiDou Navigation Satellite System (BDS). Specifically, it is a network RTK (Real-Time Kinematic) differential correction generation method, system, and related applications based on the fusion of BeiDou and LEO constellations. Background Technology

[0002] Real-time dynamic carrier phase differential (RTK) technology is a key technology for achieving centimeter-level high-precision positioning and has been widely applied in fields such as geodesy, precision agriculture, autonomous driving, drone navigation, and infrastructure deformation monitoring. Traditional network RTK technology mainly relies on medium-to-high Earth orbit Global Navigation Satellite Systems (GNSS), such as the US GPS, China's BeiDou (BDS), Europe's Galileo, and Russia's GLONASS. The satellites of these systems typically orbit at altitudes above 20,000 kilometers, with orbital periods of approximately 12 hours.

[0003] However, traditional GNSS network RTK technology faces three core challenges in practical applications: 1. Long convergence time: Due to the slow changes in the geometric configuration of medium and high orbit satellites, the resolution of carrier phase ambiguity requires a long observation time to achieve reliable fixation. In environments with severe signal obstruction, such as urban canyons and forest areas, frequent signal interruptions and reacquisitions require repeated initialization of RTK positioning, resulting in excessively long convergence times (usually exceeding 100 seconds). This severely impacts operational efficiency and user experience, especially in dynamic scenarios with extremely high real-time requirements, such as autonomous driving.

[0004] 2. Poor geometry: In complex observation environments, the number of visible GNSS satellites may decrease sharply, and the uneven distribution of satellites in the sky leads to an increase in the position accuracy factor (PDOP), resulting in a significant decrease in positioning accuracy and reliability. This is one of the main bottlenecks limiting the robust application of RTK technology in all scenarios.

[0005] 3. Immature LEO Constellation Enhancement Technology: In recent years, low Earth orbit (LEO) communication constellations, represented by Starlink, OneWeb, and China's Qianfan and GW constellations, have flourished. These constellations consist of hundreds or even thousands of LEO satellites, characterized by a large number of satellites, low orbital altitudes (typically 500-1200 km), high orbital speeds (approximately 7.8 km / s), and short orbital periods (90-120 minutes). The overall geometry of the constellation is formed by all its satellites, significantly improving global coverage and geometric diversity; however, the individual characteristics of each satellite, such as orbital altitude and signal propagation path, directly affect the error characteristics of its observations. Introducing LEO constellation signals into RTK processing can greatly improve satellite geometry and significantly accelerate ambiguity convergence. However, BDS and LEO constellations are heterogeneous systems, differing in time references, coordinate frames, and signal systems, posing significant challenges to direct fusion.

[0006] Currently, effectively integrating BDS and LEO constellations to enhance RTK performance has become a research hotspot. One of the most critical technical challenges is handling Inter-System Bias (ISB). ISB is a systematic deviation caused by factors such as hardware delays and time reference differences between different navigation systems. For heterogeneous systems like BDS and LEO, due to the rapid movement of LEO satellites relative to ground stations and users, their ISB exhibits significant time-varying characteristics, far more drastic than the ISB variations between traditional GNSS systems. Failure to accurately model and compensate for this time-varying ISB will severely impact the accuracy of fused positioning and the success rate of ambiguity fixation.

[0007] A search revealed that Chinese patent application CN109946727A discloses a "Network RTK Method for Enhancing Low-Earth Orbit Navigation Constellations." This application proposes using low-Earth orbit constellations to improve geometric configurations; however, its technical solution focuses on constellation design and the basic system framework, failing to propose specific ISB time-varying modeling methods for the rapid motion characteristics of LEO satellites, nor does it address how to adaptively generate and broadcast differential corrections based on the characteristics of LEO satellites. Furthermore, this patent application is currently in a withdrawn state, indicating that its technical solution may contain defects or be incomplete.

[0008] In recent years, progress on the joint processing of BDS and LEO has been limited. A 2025 study proposed a "LEO ISL-assisted rapid joint orbit determination method," utilizing LEO-borne GNSS data and regional ground station data to achieve rapid joint precise orbit determination of GNSS and LEO. However, the aforementioned research mainly focuses on satellite orbit determination, aiming to determine the satellite's own orbital parameters. Its observation models and parameter estimation strategies differ fundamentally from those used in ground-based RTK applications. In the scenario of generating differential corrections using network RTK, joint observation of BDS and LEO faces new technical challenges: the inter-system bias (ISB) caused by the rapid motion of LEO satellites exhibits significant time-varying characteristics, and the ISB processing models in existing orbit determination studies cannot be directly applied to the real-time generation of RTK corrections.

[0009] Therefore, there is an urgent need in this field for a new network RTK method that can effectively handle the time-varying ISB problem in the heterogeneous fusion of BDS and LEO and can adaptively generate efficient differential correction numbers, so as to fully realize the enhancement potential of LEO constellations. Summary of the Invention

[0010] This invention aims to address the following technical problems in existing BDS and LEO heterogeneous constellation RTK fusion technologies: 1. Due to the high-speed motion of LEO satellites, the inter-system bias (ISB) between BDS and LEO exhibits rapidly time-varying characteristics. Existing static or slowly varying ISB models cannot accurately compensate for this, leading to decreased fusion positioning accuracy and difficulty in fixing ambiguities. 2. LEO and BDS satellites differ significantly in orbital altitude, signal propagation paths, etc. Using the same differential correction strategy cannot fully leverage the advantages of LEO satellites and may even introduce additional errors. 3. The geometric position of LEO satellites changes rapidly. Traditional fixed-duration differential correction broadcasting strategies cannot balance timeliness and data bandwidth, resulting in correction aging or data redundancy.

[0011] To address the aforementioned technical problems, this invention provides a method for generating network RTK differential corrections based on the fusion of BeiDou and a low-Earth orbit (LEO) constellation. The LEO constellation is a low Earth orbit communication constellation with an orbital altitude lower than that of medium- and high-Earth orbit navigation satellites, forming a heterogeneous fusion system with the BeiDou satellite navigation system. The method includes the following steps: The data acquisition step involves simultaneously receiving pseudorange and carrier phase observations from BeiDou Navigation Satellite System satellites and the aforementioned low-orbit constellation satellites via a ground reference station receiver. The joint observation model construction and inter-system deviation estimation steps involve constructing a joint observation model of the BeiDou satellite navigation system and the low-Earth orbit constellation, and using the extended Kalman filter algorithm to estimate the receiver clock error and the inter-system deviation between the two systems in real time. The time-varying characteristics of the inter-system deviation caused by the rapid motion of the low-Earth orbit satellite relative to the BeiDou satellite are included. The inter-system deviation is estimated as a time-varying state parameter in the observation model, and its corresponding process noise covariance matrix component is set to be significantly larger than the process noise of the deviation within the BeiDou system. The adaptive weighted differential correction calculation steps are as follows: based on the estimated inter-system deviation, the pseudorange differential corrections for BeiDou satellites and low-Earth orbit satellites are calculated respectively. In this step, an adaptive weighting factor based on the orbital altitude is introduced for the low-Earth orbit satellites. The weighting factor is determined according to the difference in signal propagation paths between the low-Earth orbit satellites and BeiDou satellites, as well as the difference in spatial correlation between ionospheric and tropospheric errors. The correction data broadcasting step involves dynamically determining the effective duration of the differential correction data based on the orbital altitude of the low-Earth orbit satellite. The effective duration is significantly shorter than that of the BeiDou satellite correction data. The correction data of the BeiDou satellite and the low-Earth orbit satellite are encoded into RTCM message format and broadcast to the user terminal. The user-side RTK solution process involves receiving the correction values, correcting local BeiDou satellite and low-orbit satellite observations, performing joint RTK solution, and verifying that the ambiguity is fixed.

[0012] Moreover, in the steps of constructing the joint observation model and estimating the inter-system bias, the estimation of the inter-system bias uses a higher time update rate than the estimation of the bias within the BeiDou system.

[0013] Furthermore, in the steps of constructing the joint observation model and estimating the inter-system bias, an extended Kalman filter is used, whose state vector includes receiver position, receiver clock error, inter-system bias, and zenith tropospheric delay; the corresponding component of the process noise covariance matrix set for the inter-system bias has a value that is significantly greater than the process noise of the bias estimation within the BeiDou system, so as to track the rapid changes in the inter-system bias.

[0014] Furthermore, in the step of calculating the adaptive weighted differential correction, the adaptive weighting factor of the low-orbit satellite is determined according to the preset interval of its orbital altitude. When the orbital altitude is in different intervals, a corresponding weighting coefficient is assigned. The weighting design is based on the difference in observation noise characteristics caused by the short signal propagation path of the low-orbit satellite.

[0015] Moreover, in the step of broadcasting correction data, the effective duration of the differential correction data of the low-orbit satellite is dynamically adjusted according to its orbital altitude. Its value is positively correlated with the orbital altitude and is significantly shorter than the effective duration of the correction data of the Beidou satellite.

[0016] Furthermore, in the step of integrating RTK solution at the user end, an adaptive ambiguity search strategy is adopted to take advantage of the rapid changes in the geometry of low-Earth orbit satellites. This includes shortening the observation arc length of the ambiguity search when the elevation angle change rate of low-Earth orbit satellites exceeds a preset threshold, in order to accelerate convergence.

[0017] Moreover, the low-Earth orbit constellation adopts the Walker constellation configuration, with its orbital inclination set within a preset range, forming a heterogeneous fusion system with the BeiDou-3 satellite navigation system to achieve geometrical complementarity.

[0018] On the other hand, the present invention provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements a network RTK differential correction generation method based on the fusion of BeiDou and low-Earth orbit constellations as described above.

[0019] On the other hand, the present invention provides a non-transitory computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements a network RTK differential correction number generation method based on the fusion of BeiDou and low-orbit constellations as described above.

[0020] On the other hand, the present invention provides a computer program product, including a computer program, characterized in that: when the computer program is executed by a processor, it implements a network RTK differential correction number generation method based on the fusion of BeiDou and low-orbit constellations as described above.

[0021] Compared with the prior art, the present invention achieves the following significant beneficial effects through the above technical solution: 1. Achieved precise unification of spatiotemporal references for heterogeneous constellations: Through the innovative ISB time-varying modeling method, the core problem caused by the inconsistency of time references and hardware delays between BDS and LEO constellations was effectively solved, enabling high-precision joint processing of observations from the two heterogeneous systems under a unified reference framework.

[0022] 2. Significantly reduced RTK convergence time: By fully utilizing the advantage of rapidly changing LEO satellite geometry, the process of resolving carrier phase ambiguity is greatly accelerated. Experimental data shows that, in typical scenarios, the convergence time of static RTK can be reduced from 107 seconds in a traditional BDS single system to 36 seconds, an improvement of up to 66.4%, with similar significant improvements in dynamic scenarios.

[0023] 3. Significantly improved positioning accuracy and reliability: Through an adaptive weighting strategy, LEO satellite observation data is processed more effectively, and combined with a stronger satellite geometry, positioning accuracy is significantly improved. Experimental data shows that the root mean square (RMS) error of static horizontal positioning is reduced from 3.8 cm to 1.8 cm, an improvement of 52%. Simultaneously, in environments with poor satellite visibility, the success rate of ambiguity fixation increases from 92.5% to 98.8%, significantly enhancing system availability and robustness.

[0024] 4. Optimized differential data broadcasting efficiency: By dynamically determining the effective duration of LEO corrections, unnecessary data redundancy is avoided while ensuring the accuracy of corrections, thus optimizing the utilization efficiency of communication bandwidth and making it more suitable for large-scale users and complex network environments. Attached Figure Description

[0025] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0026] Figure 1 This is a schematic diagram of the overall system architecture provided in an embodiment of the present invention; Figure 2 This is a flowchart of the method provided in an embodiment of the present invention; Figure 3 This is a schematic diagram of the ISB estimation process provided in an embodiment of the present invention (based on extended Kalman filtering). Figure 4 This is a comparison diagram of the BeiDou and low-orbit satellite correction number generation processes provided in this embodiment of the invention; Figure 5 This is a comparison chart of PDOP values ​​and the number of visible satellites under BDS single system and BDS+LEO fusion system; Figure 6 This is a comparison chart of convergence curves between a single BDS system and a BDS+LEO fusion system. Figure 7 This is a schematic diagram illustrating the relationship between LEO satellite orbital altitude and adaptive weighting factor provided in an embodiment of the present invention; Figure 8 This is a schematic diagram illustrating the calculation of the effective duration of LEO satellite corrections provided in an embodiment of the present invention; Figure 9 This is a bar chart comparing the performance of different schemes in terms of convergence time, positioning accuracy, and ambiguity fixation rate. Figure 10It is a comparison curve of the time-varying characteristics of the intra-system bias and the inter-system bias (ISB) of BDS-LEO; Figure 11 It is a comparison curve of the ambiguity fixation rate of different schemes over time; Figure 12 This is a schematic diagram of the system implementation provided in an embodiment of the present invention. Detailed Implementation

[0027] The technical solutions of the present invention will be clearly and completely described below with reference to the embodiments and 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 of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0028] Reference Figures 1 to 12 This invention provides a method and system for generating network RTK differential corrections based on the fusion of BeiDou and low-orbit constellations.

[0029] Example 1: Application in server-side network RTK differential correction generation scenario See Figure 1 The embodiment provides a method for generating network RTK differential corrections based on the fusion of BeiDou and a low Earth orbit (LEO) constellation. The LEO constellation is a low Earth orbit communication constellation with an orbital altitude lower than that of medium and high Earth orbit navigation satellites, forming a heterogeneous fusion system with the BeiDou Navigation Satellite System (BDS). The method includes the following steps: S1. Data Acquisition: Simultaneously receive pseudorange and carrier phase observations from satellites of the BeiDou Navigation Satellite System (BDS) and satellites from the aforementioned Low Earth Orbit (LEO) constellation via a ground reference station receiver. The LEO constellation includes, but is not limited to, the GW LEO constellation or the Qianfan constellation. Satellites from the aforementioned LEO constellation can be referred to as LEO satellites.

[0030] Preferably, the LEO constellation is configured as the Walker constellation with an orbital inclination of 40°~60°, forming a heterogeneous fusion system with BeiDou-3 (BDS-3) to achieve geometrical complementarity.

[0031] S2. Joint Observation Model Construction and Inter-System Bias Estimation: A joint observation model of BDS and LEO is constructed, and the receiver clock error and the inter-system bias (ISB) between the BDS and LEO systems are estimated in real time using the extended Kalman filter (EKF) algorithm. The time-varying characteristics of the ISB are caused by the rapid motion of the LEO satellite relative to the BDS satellite. The ISB is estimated as a time-varying state parameter in the observation model, and the corresponding component of its process noise covariance matrix is ​​significantly larger than the process noise of the intra-system bias of the BDS system. In one possible implementation, the joint observation model described in step S2 fully considers the geometric differences between LEO satellites and BDS satellites. Since the orbital altitude of LEO satellites is much lower than that of BDS satellites, the distribution range and rate of change of the element values ​​of the geometric distance of the observations are significantly different, which leads to the need for ISB estimation to adopt a higher time update rate than the intra-system bias estimation of BDS.

[0032] The key to constructing a mathematical model for joint BDS and LEO observations lies in using the Extended Kalman Filter (EKF) algorithm to estimate the ISB between BDS and LEO as a time-varying state parameter in real time. To accurately capture the rapid changes in ISB caused by the high-speed motion of the LEO satellite (approximately 7.8 km / s), a process noise significantly larger than the intra-satellite deviation in traditional GNSS systems (e.g., ...) is introduced into the EKF state transition model for the ISB state component. ≈ 0.01m 2 / s), thereby enabling accurate tracking of the time-varying characteristics of the ISB.

[0033] See Figure 3 The estimation of ISB in step S2 employs an extended Kalman filter (EKF), an algorithm already known and will not be described in detail here. The state vector is set as... ,in, As coordinates, For clock difference, The speed of light; The zenith tropospheric delay is used; considering the rapid changes in geometric configuration caused by the rapid motion of the LEO satellite, the corresponding components of the ISB process noise covariance matrix are set to... Its value ranges from 0.005 to 0.02 m² / s, with a preferred value of 0.01 m² / s, which is significantly greater than the 0.001 m² / s within the BDS system bias estimate, in order to track the rapid changes in ISB.

[0034] S3. Adaptive Weighted Differential Correction Calculation: Based on the ISB estimated in step S2, calculate the pseudorange differential correction (PRC) for both the BDS and LEO satellites, introducing an adaptive weighting factor based on orbital altitude for the LEO satellite. The weighting factor is determined based on the differences in signal propagation paths between LEO satellites and BDS satellites and the differences in spatial correlation of ionospheric / tropospheric errors. In one possible implementation, the adaptive weighting factor of the LEO satellite mentioned in step S3 According to the track height Confirmed: When < hour, = ;when ≤ ≤ hour, = ;when > hour, = ;in and For the orbital height threshold, , and These are the weighting coefficients; Preferably, = 800km, = 1200km, = 1.2, = 1.0, = 0.8; The weight design is based on the differences in observation noise characteristics caused by the short propagation path of LEO satellite signals. That is, this weight factor is assigned different weights (1.2, 1.0, 0.8) according to different LEO satellite orbital altitudes (divided into intervals such as <800km, 800-1200km, and >1200km) to reflect the differences in LEO satellite signal propagation paths and changes in observation noise characteristics at different orbital altitudes, thereby optimizing the accuracy of the correction.

[0035] S4. Correction broadcast: The effective duration of the differential correction is dynamically determined based on the LEO satellite orbital altitude. The effective duration is significantly shorter than that of the BDS correction. The BDS and LEO corrections are encoded into RTCM message format and broadcast to the user terminal. In one possible implementation, the effective duration of the differential correction is dynamically determined based on the LEO satellite's orbital altitude and speed. The lower the orbit, the faster the speed, and the shorter the effective duration (e.g., 1.5-2.5 seconds), and vice versa. This ensures the timeliness of the corrections and avoids accuracy loss due to correction aging. Subsequently, the corrections from BDS and LEO are uniformly encoded into a standard RTCM message format and broadcast to the user terminal via mobile communication networks or satellite links.

[0036] The effective duration of the LEO differential correction in step S4 Dynamically adjusted based on track altitude: Where h is the orbital altitude of the LEO satellite, For reference height, k is an empirical coefficient; preferably, = 1000 km, the value of k ranges from 1.5 to 2.5 seconds, the preferred value is 2.0 seconds, which is significantly shorter than the effective duration of 5 to 10 seconds of the BDS correction number.

[0037] S5. User-side fusion RTK solution: The user receives the correction data, corrects the BDS and LEO observations, performs joint RTK solution using the LAMBDA algorithm, and confirms the ambiguity is fixed through the Ratio test.

[0038] Specifically, the user terminal receives and decodes the RTCM message containing BDS and LEO corrections, and performs differential corrections on the local BDS and LEO observations. Taking advantage of the rapidly changing geometric configuration after the addition of LEO satellites, an adaptive ambiguity search strategy is employed, and algorithms such as LAMBDA are used for joint ambiguity resolution of BDS and LEO. After confirming successful ambiguity fixation through methods such as the Ratio test, high-precision real-time positioning results can be output.

[0039] In one possible implementation, during the user-end fusion RTK solution in step S5, an adaptive ambiguity search strategy is adopted, taking advantage of the rapid changes in the geometric configuration of LEO satellites (their orbital period is much shorter than that of BDS satellites): when the rate of change of the elevation angle of LEO satellites exceeds a preset threshold, the observation arc length of the ambiguity search is shortened to accelerate convergence; preferably, the preset threshold is 0.3°~0.7° / second, with a preferred value of 0.5° / second, and the observation arc length is shortened to 20~40 seconds, with a preferred value of 30 seconds.

[0040] Example 2: Static High-Precision Positioning Scenario See Figure 2 This embodiment describes the application of the present invention in static measurement scenarios, such as the layout of surveying benchmarks and the monitoring of building deformation.

[0041] Step S1: Data Acquisition A CORS network consisting of multiple ground reference stations is deployed within a region (e.g., a radius of 50 kilometers). Each reference station is equipped with a multi-mode, multi-frequency receiver capable of simultaneously tracking BDS (B1I, B3I signals) and the LEO constellation (taking the GW constellation as an example, its communication signals). The receiver continuously acquires raw pseudorange and carrier phase observation data from BDS and GW satellites at a sampling rate of 1 Hz and transmits it in real time to the data processing center via a network link.

[0042] Step S2: ISB Time-varying Modeling and Estimation The data processing center processes the received multi-reference station data. First, a non-differential, non-combined joint observation model of BDS and GW is constructed. Its pseudorange and carrier phase observation equations can be simplified as follows:

[0043] in, and These are pseudorange and carrier phase observations. Let be the geometric distance between the star and the Earth, and c be the speed of light. and These are receiver clock bias and satellite clock bias, respectively. and These are the ionospheric and tropospheric delays, respectively. Where is the wavelength, N is the integer ambiguity, and ISB is the inter-system bias between BDS and GW (for BDS satellites, ...). The value is 0 because, in this invention, the BeiDou Navigation Satellite System is chosen as the reference standard. Therefore, for the observation equations of BeiDou satellites, the inter-system bias term is set to zero. For the observation equations of low-Earth orbit satellites, an inter-system bias parameter to be estimated is introduced to compensate for the time reference difference and hardware delay difference between the two systems. To mitigate pseudorange observation noise and multipath error, This is due to carrier phase observation noise and multipath error.

[0044] The core idea is to use the Extended Kalman Filter (EKF) to estimate the state vector. The state vector X is defined as:

[0045] in, The coordinates are the base station coordinates (which can be set to known or to be estimated in the network solution). This represents the deviation between the receiver clock bias and the BDS time. The inter-system deviation of the GW system relative to the BDS system. This is the wet delay of the zenith troposphere.

[0046] In the state prediction (time update) step of EKF, the state transition equation is: Where F is the state transition matrix; This is the state estimate at time k-1. This represents the predicted state at time k-1. The key lies in setting the process noise covariance matrix Q. For The component, taking into account the rapid changes in ISB caused by the high-speed motion of the GW satellite at approximately 7.8 km / s (e.g.) Figure 10 As shown, its frequency and amplitude of change far exceed the internal deviation of the BDS system, and its corresponding process noise The process noise is set to a relatively large value, such as 0.01 m² / s. For traditionally slowly varying receiver clock errors and tropospheric delays, the process noise is set to a smaller value. This differentiated Q-matrix setting enables the EKF to effectively track the rapidly time-varying characteristics of the ISB, which is key to achieving accurate compensation.

[0047] Step S3: Calculation of Adaptive Weighted Difference Correction See Figure 4 The generation process for differential corrections between BeiDou satellites and low-Earth orbit satellites differs significantly, primarily in the handling of inter-system bias (ISB): For BeiDou satellites, the correction generation process includes: the base station receiver acquiring the raw observation data of the BeiDou satellites, and calculating the distance (c·dt) corresponding to the receiver clock bias. r ) and the geometric distance from the satellite to the base station ( The formula for calculating the pseudorange differential correction (PRC) of BeiDou satellites, based on ambiguity parameter processing, takes into account the effects of ionospheric delay and tropospheric delay errors. The formula is: PRC[i] = -(Vc·dt) r ), where V represents the comprehensive calculated distance value after taking into account various errors such as satellite clock error, geometric distance, ionospheric delay, and tropospheric delay.

[0048] For low-Earth orbit satellites, the correction generation process is similar to that of BeiDou satellites in terms of basic steps such as reference station observation, clock error calculation, geometric distance calculation, and ionospheric / tropospheric error processing. However, the key difference lies in the fact that the correction calculation requires additional introduction and subtraction of the inter-system bias (ISB) estimated in real-time during step S2. For example... Figure 4 As shown on the right, the formula for calculating the pseudorange differential correction for low-Earth orbit satellites is: PRC[i] = -(Vc·dt) r - ISB), where the ISB item reflects the time reference difference and hardware delay difference between the BeiDou system and the low-Earth orbit constellation, and is a core parameter to ensure the positioning accuracy of heterogeneous system fusion.

[0049] pass Figure 4 The comparison clearly shows that this invention explicitly incorporates a compensation mechanism for inter-system deviations in the generation of LEO satellite corrections, which is a key technical feature for achieving high-precision fusion of BeiDou and LEO constellations. In subsequent adaptive weighted calculations, a weighting factor will be further introduced based on the orbital altitude of the LEO satellites to optimize the contribution of LEO satellites at different orbital altitudes to the positioning solution.

[0050] One possible implementation is that the EKF completes the measurement update and obtains accurate... After estimating the values, the data processing center generates differential corrections for the reference station. For a BDS satellite i, its pseudorange correction... for:

[0051] For a GW satellite j, its pseudorange correction PRC_j is: in, , Let be the pseudorange corrections for satellite i and satellite j, respectively. , These are the pseudorange observations for satellite i and satellite j, respectively. At the speed of light, To estimate receiver clock bias, , The satellite clock biases for satellites i and j are respectively. , The estimated ionospheric delays for satellites i and j are respectively. , The estimated tropospheric delays for satellites i and j are respectively. Estimate inter-system bias for GW satellites.

[0052] When generating the final network RTK corrections, adaptive weights are introduced for the LEO satellite observations. (Refer to...) Figure 7 This invention proposes a weighting factor based on orbital height h. For example, for LEO satellites with an orbital altitude h < 800 km, their signal propagation paths are short and less affected by ionospheric / tropospheric residuals, but multipath effects may be more significant, so a weight w = 1.2 can be assigned; for satellites with 800 km ≤ h ≤ 1200 km, a baseline weight w = 1.0 is assigned; and for satellites with h > 1200 km, a weight w = 0.8 is assigned. These weights will be used in the weighted least squares solution at the user end to optimize the final positioning results.

[0053] Step S4: Dynamic Valid Duration and Broadcasting Reference Figure 8 LEO satellite correction validity period It is dynamically adjusted according to its orbital height h. For example, using the formula... ,in The reference altitude is 1000 km, and k is an empirical coefficient (e.g., 2.0 seconds). For a LEO satellite at 1000 km altitude, the effective duration of the correction is 2 seconds; while for a satellite at 500 km altitude, the effective duration is 1 second. In contrast, the effective duration of the correction for BDS satellites is typically 5-10 seconds. This dynamic strategy ensures the timeliness of the corrections.

[0054] Finally, the differential corrections, including weights and effective duration information for both BDS and LEO satellites, are encoded in the RTCM 3.x standard format (which can use the MSM message type) and broadcast via the NTRIP protocol.

[0055] Step S5: User-side fusion solution A static measurement user (such as a measuring rod) receives RTCM corrections and adjusts local observations accordingly. Due to the fusion of LEO satellites, the total number of visible satellites increases, and their geometries change rapidly (e.g., Figure 5 As shown, the PDOP value is lower and more variable, which provides more favorable conditions for ambiguity resolution. The user end uses the LAMBDA algorithm for ambiguity search. Figure 6 and Figure 11 As shown, the fusion system achieves a higher success rate in ambiguity fixation, and the convergence time to centimeter-level accuracy is reduced from 107 seconds to 36 seconds. The final output positioning accuracy (horizontal RMS) is improved from 3.8 cm to 1.8 cm (e.g., Figure 9 (As shown).

[0056] Example 3: Dynamic High-Precision Positioning Scenario This embodiment describes the application of the present invention in an in-vehicle autonomous driving scenario.

[0057] The RTK terminal on the vehicle repeats step S5 in Example 1. Unlike static scenarios, dynamic scenarios have higher requirements for real-time performance and continuity.

[0058] Under the method of this invention, when a vehicle is driving in an urban canyon and some BDS satellite signals are blocked, LEO satellites from different azimuths and with rapidly changing elevation angles can promptly "fill in the gaps," maintaining a sufficient number of visible satellites and a good geometric configuration, thus avoiding a sharp drop in positioning accuracy or positioning interruption.

[0059] When a vehicle experiences a complete signal loss due to overpasses or other obstacles and then reacquires the signal, the rapid movement of LEO satellites allows for faster accumulation of the independent observation equations required for ambiguity resolution. The adaptive ambiguity search strategy employed in this invention dynamically adjusts the observation arc length based on the rate of change of the LEO satellite's elevation angle. When the rate of change of the elevation angle exceeds a threshold (e.g., 0.5° / second), the observation arc length for ambiguity search can be shortened to 30 seconds, thus achieving rapid reconvergence. This is crucial for maintaining continuous lane-level positioning for autonomous vehicles.

[0060] Figure 2The diagram shows the method flowchart of the present invention, where the 'convergence' judgment after step S5 represents whether the ambiguity has been successfully fixed. In a static positioning scenario, this judgment is used to determine whether a convergence state capable of outputting high-precision results has been reached; in a dynamic positioning scenario, this judgment is performed continuously at each epoch to ensure the continuity and reliability of real-time positioning.

[0061] In summary, this invention successfully solves the key technical challenges of RTK fusion by accurately modeling the time-varying ISB between BDS and LEO heterogeneous systems, employing an adaptive differential correction strategy, and implementing a dynamic broadcasting mechanism. This significantly improves the convergence speed, accuracy, reliability, and availability of high-precision positioning, and has broad application prospects in fields such as surveying, autonomous driving, and drones.

[0062] Example 4: Dynamic High-Precision Positioning Scenario This embodiment provides a network RTK differential correction generation system based on the fusion of BeiDou and low-Earth orbit constellations, including: a data acquisition module, a joint calculation module, a correction generation module, a data broadcasting module, and a user positioning module.

[0063] In one possible implementation, the joint solution module includes: an observation preprocessing unit, an ISB estimation unit, and a state update unit.

[0064] In one possible implementation, the correction number generation module includes: an adaptive weighting unit, a correction number calculation unit, and an effective duration determination unit.

[0065] See Figure 12 This embodiment provides a network RTK differential correction generation system based on the fusion of BeiDou and low-Earth orbit constellations. The data acquisition module, joint solution module, correction generation module, data broadcasting module, and user positioning module are implemented as follows: I. Data Acquisition Module Deployed in a ground-based reference station network, it simultaneously receives raw observation data (pseudorange, carrier phase) from BeiDou satellites (BDS) and low Earth orbit (LEO) satellites in the space segment via multi-mode, multi-frequency receivers, and transmits the observation data to the data processing center in real time.

[0066] II. Joint Solving Module This module is responsible for the joint processing of BDS and LEO, enabling time-varying modeling and accurate estimation of inter-system biases, specifically including: Observation preprocessing unit: performs quality control and error correction on the raw observation data (such as antenna phase center correction, relativistic effect correction, etc.) and constructs the joint observation equation of BDS and LEO.

[0067] The ISB estimation unit employs the Extended Kalman Filter (EKF) algorithm to estimate the inter-system bias (ISB) between the BDS and LEO as a time-varying state parameter in real time. The core innovation lies in: addressing the rapidly changing ISB characteristics caused by the high-speed motion of the LEO satellite by introducing significantly larger process noise (such as...) into the ISB state. Figure 12 As shown, Q = 0.01 m² / s), enabling it to accurately track the rapid changes in ISB, which is much greater than the process noise of the deviation within the BDS system.

[0068] State update unit: Corrects the predicted state based on the current observation value and outputs updated parameters such as receiver clock error, ISB, and tropospheric delay.

[0069] III. Correction Number Generation Module Based on the parameters output by the joint solution module, differential corrections for BDS and LEO satellites are generated, specifically including: Adaptive weighted unit: Based on the orbital altitude of LEO satellites, dynamically calculate adaptive weighting factors (e.g., ... Figure 12 As shown, w = 0.8~1.2). The lower the orbital altitude, the shorter the signal propagation path and the different observation noise characteristics. Corresponding weights are assigned (e.g., w=1.2 when h<800km, w=0.8 when h>1200km) to optimize the contribution of LEO satellites at different orbital altitudes to the positioning solution.

[0070] Correction Calculation Unit: Calculates the pseudorange differential correction (PRC) for BDS and LEO satellites respectively. The key difference is that the LEO satellite correction calculation requires subtracting the inter-system bias (ISB) output from the ISB estimation unit. See the specific calculation formula below. Figure 4 .

[0071] Effective Duration Determination Unit: Based on the orbital altitude of the LEO satellite, dynamically determine the effective duration of its differential correction (e.g., Figure 12 As shown, the effective duration is 1.5~2.5 seconds. The lower the orbit and the faster the running speed, the shorter the effective duration, ensuring the timeliness of the correction.

[0072] IV. Data Broadcasting Module The generated BDS and LEO satellite differential corrections, weight information, and effective duration information are encoded according to the RTCM standard format and broadcast in real time to user terminals within the coverage area through mobile communication networks or satellite links.

[0073] V. User Location Module The user-end receiver receives and decodes RTCM corrections, performs differential corrections on local observations, utilizes the rapidly changing geometric configuration of LEO satellites, employs an adaptive ambiguity search strategy for fusion RTK calculations, and finally outputs high-precision positioning results (centimeter level).

[0074] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

[0075] In specific implementation, the method proposed in the technical solution of this invention can be automatically executed by those skilled in the art using computer software technology. System devices for implementing the method, such as computer-readable storage media storing the corresponding computer program of the technical solution of this invention and computer equipment including the computer program running the corresponding computer program, should also be within the protection scope of this invention.

[0076] The apparatus provided by the present invention is described below. The apparatus described below can be referred to in correspondence with the network RTK differential correction number generation method based on the fusion of BeiDou and low-orbit constellations described above.

[0077] In another embodiment, the present invention provides an electronic device that may include: a processor, a communications interface, a memory, and a communication bus, wherein the processor, the communications interface, and the memory communicate with each other via the communication bus. The processor can call logical instructions in the memory to execute a network RTK differential correction number generation method based on the fusion of BeiDou and low-Earth orbit constellations.

[0078] Furthermore, the logical instructions in the aforementioned memory can be implemented as software functional units and sold or used as independent products, and can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0079] In another possible embodiment, the present invention also provides a computer program product, the computer program product including a computer program, the computer program being stored on a non-transitory computer-readable storage medium, and when the computer program is executed by a processor, the computer is able to execute the software processing part of the network RTK differential correction number generation method based on the fusion of BeiDou and low-orbit constellations provided by the above methods.

[0080] By executing the computer program, the rapid geometric change characteristics of the low-Earth orbit constellation can be fully utilized to accelerate ambiguity resolution, significantly shorten RTK initialization time, and improve positioning accuracy and reliability, making it particularly suitable for complex scenarios such as urban canyons and dynamic measurements.

[0081] In another possible embodiment, the present invention also provides a non-transitory computer-readable storage medium on which a computer program is stored. The computer-readable storage medium can be any tangible medium containing or storing a program, such as, but not limited to, read-only memory (ROM), random access memory (RAM), magnetic disk, optical disk, flash drive, solid-state drive, etc. When the computer program is executed by a processor, it implements the network RTK differential correction number generation method based on the fusion of BeiDou and low-Earth orbit constellations as described in any of the preceding embodiments.

[0082] In another possible embodiment, a network RTK differential correction number is provided, which is generated by the method described above. This differential correction number includes BeiDou satellite differential correction numbers and low-Earth orbit satellite differential correction numbers, both of which are encoded into a message conforming to the RTCM standard format and broadcast to the user terminal via a mobile communication network or satellite link.

[0083] Among them, the BeiDou satellite differential correction data is generated based on the observation data of BeiDou satellites from the reference station network. It is used to correct common errors in the pseudorange observations of BeiDou satellites by user-end receivers, such as satellite clock errors, orbital errors, ionospheric and tropospheric delays.

[0084] In the generation process of low-Earth orbit satellite differential corrections, in addition to the aforementioned common error corrections, two key pieces of information are specifically included: Adaptive weighting information based on orbital altitude: This weighting information is determined according to the real-time orbital altitude of the low-Earth orbit (LEO) satellites. For example, the weight value is set to 1.2 for LEO satellites with orbital altitudes below 800 km; 1 for LEO satellites with orbital altitudes between 800 km and 1200 km; and 0.8 for LEO satellites with orbital altitudes above 1200 km. This weighting information is used by the user terminal to weight the LEO satellite observations at different orbital altitudes during fusion calculations, thereby optimizing their contribution to the positioning solution.

[0085] Dynamic valid duration information: This valid duration information is dynamically determined based on the real-time orbital altitude of the low-Earth orbit satellite and is positively correlated with the orbital altitude. For example, for a low-Earth orbit satellite with an orbital altitude of 1,000 kilometers, its correction validity duration is set to two seconds; the validity duration shortens accordingly when the orbital altitude decreases and extends accordingly when the orbital altitude increases. This information is used by the user to determine the timeliness of the correction and avoid introducing errors by using outdated corrections.

[0086] After the differential correction is encoded into an RTCM message, the user terminal can decode the correction data of the BeiDou satellite, the correction data of the low-orbit satellite, and their associated weights and effective duration information, thereby achieving joint high-precision positioning of BeiDou and low-orbit satellites.

[0087] In another possible embodiment, a network RTK positioning terminal device is provided. This device can be a vehicle-mounted terminal, a measurement receiver, an airborne module of a drone, a smartphone, or other mobile devices requiring high-precision positioning. The device includes a receiving unit, a communication unit, a processing unit, and an output unit.

[0088] Receiver Unit: Used to receive navigation signals from the BeiDou Navigation Satellite System and low-Earth orbit (LEO) constellations, and to acquire raw pseudorange and carrier phase observation data. This unit typically includes a multi-frequency, multi-mode antenna and an RF front-end, capable of simultaneously tracking signals from BeiDou-3 (BDS-3) and LEO communication constellations (such as the GW constellation and the Qianfan constellation).

[0089] Communication unit: Used to receive RTCM format differential correction data broadcast by the data processing center via mobile communication networks (such as 4G / 5G) or satellite links. This correction data includes pseudorange differential correction data from BeiDou satellites and low-Earth orbit satellites, as well as adaptive weight information and dynamic effective duration information based on orbital altitude attached to low-Earth orbit satellites.

[0090] Processing Unit: As the core of the terminal, it is responsible for performing the following operations: Using the correction data received by the communication unit, differential corrections are performed on local BeiDou satellite and low-orbit satellite observations to eliminate common errors; The adaptive weight information and effective duration information of low-orbit satellites are extracted from the correction data for optimization of subsequent solutions; The LAMBDA algorithm is used for joint RTK calculation of BeiDou and low Earth orbit. During the calculation process, the rapid change of the geometry of low Earth orbit satellites is taken into account, and an adaptive ambiguity search strategy is adopted (for example, when the elevation angle change rate of low Earth orbit satellites exceeds 0.5 degrees per second, the observation arc length of ambiguity search is shortened to 30 seconds) to accelerate ambiguity fixation. After confirming the successful fixation of ambiguity through the Ratio test, high-precision real-time position, velocity, and time information were calculated.

[0091] Output unit: Used to output the high-precision positioning results obtained by the processing unit. The output format can be digital interface (such as serial port, USB, Bluetooth), display screen, data recording, or uploading to the control center via network.

[0092] This terminal device integrates differential corrections from BeiDou and low-Earth orbit constellations, enabling rapid convergence and centimeter-level positioning in dynamic environments. It is particularly suitable for high-precision positioning applications such as autonomous driving, drone navigation, and precision agriculture.

[0093] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0094] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0095] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for generating network RTK differential corrections based on the fusion of BeiDou and a low-Earth orbit constellation, wherein the low-Earth orbit constellation is a low Earth orbit communication constellation with an orbital altitude lower than that of medium- and high-Earth orbit navigation satellites, forming a heterogeneous fusion system with the BeiDou satellite navigation system, characterized in that... Includes the following steps: The data acquisition step involves simultaneously receiving pseudorange and carrier phase observations from BeiDou Navigation Satellite System satellites and the aforementioned low-orbit constellation satellites via a ground reference station receiver. The joint observation model construction and inter-system deviation estimation steps involve constructing a joint observation model of the BeiDou satellite navigation system and the low-Earth orbit constellation, and using the extended Kalman filter algorithm to estimate the receiver clock error and the inter-system deviation between the two systems in real time. The time-varying characteristics of the inter-system deviation caused by the rapid motion of the low-Earth orbit satellite relative to the BeiDou satellite are included. The inter-system deviation is estimated as a time-varying state parameter in the observation model, and its corresponding process noise covariance matrix component is set to be significantly larger than the process noise of the deviation within the BeiDou system. The adaptive weighted differential correction calculation steps are as follows: based on the estimated inter-system deviation, the pseudorange differential corrections for BeiDou satellites and low-Earth orbit satellites are calculated respectively. In this step, an adaptive weighting factor based on the orbital altitude is introduced for the low-Earth orbit satellites. The weighting factor is determined according to the difference in signal propagation paths between the low-Earth orbit satellites and BeiDou satellites, as well as the difference in spatial correlation between ionospheric and tropospheric errors. The correction data broadcasting step involves dynamically determining the effective duration of the differential correction data based on the orbital altitude of the low-Earth orbit satellite. The effective duration is significantly shorter than that of the BeiDou satellite correction data. The correction data of the BeiDou satellite and the low-Earth orbit satellite are encoded into RTCM message format and broadcast to the user terminal. The user-side RTK solution process involves receiving the correction values, correcting local BeiDou satellite and low-orbit satellite observations, performing joint RTK solution, and verifying that the ambiguity is fixed.

2. The method according to claim 1, characterized in that, In the steps of constructing the joint observation model and estimating the inter-system bias, the estimation of the inter-system bias uses a higher time update rate than the estimation of the bias within the BeiDou system.

3. The method according to claim 1, characterized in that, In the steps of constructing the joint observation model and estimating the inter-system bias, an extended Kalman filter is used. Its state vector includes receiver position, receiver clock error, inter-system bias, and zenith tropospheric delay. The corresponding component of the process noise covariance matrix set for the inter-system bias has a value that is significantly greater than the process noise of the bias estimation within the BeiDou system, so as to track the rapid changes in the inter-system bias.

4. The method according to claim 1, characterized in that, In the step of calculating the adaptive weighted differential correction, the adaptive weighting factor of the low-orbit satellite is determined according to the preset interval of its orbital altitude. When the orbital altitude is in different intervals, a corresponding weighting coefficient is assigned. The weighting design is based on the difference in observation noise characteristics caused by the short signal propagation path of the low-orbit satellite.

5. The method according to claim 1, characterized in that, In the step of broadcasting correction data, the effective duration of the differential correction data of the low-orbit satellite is dynamically adjusted according to its orbital altitude. Its value is positively correlated with the orbital altitude and is significantly shorter than the effective duration of the correction data of the Beidou satellite.

6. The method according to claim 1, characterized in that, In the step of fusion RTK solution at the user end, an adaptive ambiguity search strategy is adopted to take advantage of the rapid change in the geometry of low-Earth orbit satellites. This includes shortening the observation arc length of the ambiguity search when the elevation angle change rate of the low-Earth orbit satellite exceeds a preset threshold, so as to accelerate convergence.

7. The method according to claim 1, characterized in that, The low-Earth orbit constellation adopts the Walker constellation configuration, with its orbital inclination set within a preset range. It forms a heterogeneous fusion system with the BeiDou-3 satellite navigation system, achieving geometric complementarity.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, it implements a network RTK differential correction number generation method based on the fusion of BeiDou and low-orbit constellations as described in any one of claims 1 to 7.

9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by the processor, it implements a network RTK differential correction number generation method based on the fusion of BeiDou and low-orbit constellations as described in any one of claims 1 to 7.

10. A computer program product, comprising a computer program, characterized in that: When the computer program is executed by the processor, it implements a network RTK differential correction number generation method based on the fusion of BeiDou and low-orbit constellations as described in any one of claims 1 to 7.

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