A star-based centimeter-level enhanced positioning method based on B2b precise ephemeris
By constructing a time-series forecasting model based on B2b precise ephemeris and using BeiDou short message transmission of model parameters, the user end performs carrier phase observation correction, solving the communication efficiency and coverage problems of global centimeter-level positioning in existing technologies, and achieving second-level convergence and high-precision positioning.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- HUBEI LUOJIA LAB
- Filing Date
- 2026-03-23
- Publication Date
- 2026-06-09
AI Technical Summary
Existing technologies have significant shortcomings in terms of communication efficiency, convergence speed, model prediction capabilities, and service coverage, making it difficult to achieve global centimeter-level positioning accuracy, especially in areas without terrestrial communication network coverage.
By constructing a time series forecasting model based on B2b precise ephemeris, and using BeiDou short message transmission of model parameters, the user terminal combines B2b precise ephemeris and clock difference data to correct carrier phase observations, thereby achieving precise positioning.
It achieves global centimeter-level positioning without the need for terrestrial communication networks, reducing convergence time from minutes to seconds, and positioning accuracy to 2-5 centimeters. Its coverage extends to areas without terrestrial communication signals, such as the open sea and deserts, while saving more than 90% of communication traffic.
Smart Images
Figure CN122172242A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of satellite navigation and precise positioning technology, and in particular to a satellite-based centimeter-level augmented positioning method based on B2b precise ephemeris. Background Technology
[0002] High-precision satellite navigation and positioning is a core supporting technology for key infrastructures such as modern intelligent transportation, precision agriculture, surveying and mapping, and disaster monitoring. Currently, mainstream centimeter-level positioning schemes mainly rely on ground-based augmentation systems. These systems deploy multiple highly stable reference stations on the ground to collect raw GNSS observation data in real time, calculate carrier phase ambiguity and generate differential correction values, and then broadcast the correction information to user terminals through mobile communication networks (such as 4G / 5G and the Internet), thereby achieving centimeter-level positioning.
[0003] However, ground-based augmentation systems have significant limitations: First, their service range is limited by the density of base station deployment and the coverage of the communication network, making them difficult to deploy in vast deserts, plateaus, oceans, polar regions, or war zones; second, maintaining a large-scale base station network requires high construction and maintenance costs and is susceptible to natural disasters, power outages, or human sabotage; third, existing RTK (Real-Time Kinematic) services typically require several seconds to tens of seconds to complete ambiguity fixation, which is still insufficient for high-speed dynamic carriers (such as drones and autonomous vehicles).
[0004] To overcome these limitations, a Satellite-Based Augmentation System (SBAS) can be used. However, traditional SBAS (such as WAAS in the United States and EGNOS in Europe) are mainly geared towards aviation safety applications, providing meter-level accuracy, which cannot meet centimeter-level requirements. While next-generation global precise point positioning technologies can achieve global coverage, their convergence time is as long as 10–30 minutes, and they rely on high-bandwidth internet transmission for precise products (such as IGS final orbit / clock bias), making them unsuitable for environments with low communication resources.
[0005] In summary, existing technologies have significant shortcomings in terms of communication efficiency, convergence speed, model prediction capabilities, and service coverage. Summary of the Invention
[0006] This application provides a satellite-based centimeter-level augmented positioning method based on B2b precise ephemeris, to overcome the shortcomings of the aforementioned related technologies. The technical solution is as follows: Firstly, this application provides a satellite-based centimeter-level augmented positioning method based on B2b precise ephemeris, applied to a user terminal, the method comprising: Receive short messages sent by BeiDou satellites and obtain time series forecast models for each GNSS satellite based on the short messages; Determine the GNSS satellites observed at the current epoch, and receive B2b precise ephemeris and clock bias data for each observed satellite; Collect carrier single-difference phase observations for each observed satellite within the current epoch; The single-difference correction forecast value for the corresponding observed satellite within the current epoch is calculated using the time series forecast model of each observed satellite. Based on the predicted value of the single-difference correction, the corresponding carrier single-difference phase observation value is corrected to obtain the corrected carrier single-difference phase observation value; Precise positioning is achieved by combining the B2b precise ephemeris and clock bias data corresponding to each observation satellite with the corrected carrier single-difference phase observation value, and the positioning result of the user terminal in the current epoch is obtained. The time series forecast model is constructed based on observation data of each GNSS satellite from the reference station during historical periods.
[0007] In one alternative embodiment of the first aspect, the construction process of the time series forecasting model includes the following steps: The observation data of each GNSS satellite from the reference station within multiple epochs of the historical period are obtained, and the carrier phase observation value of each GNSS satellite within each epoch is obtained. An ionospherically-free array was constructed and inter-satellite single-difference calculations were performed to obtain the carrier single-difference phase observation values for each GNSS satellite; For each GNSS satellite, the single-difference correction for each epoch is calculated by combining the coordinates of the reference station and the carrier single-difference phase observation. Time-varying characteristic analysis is performed based on single-difference corrections, which are expressed as the sum of time-varying parameters and time-invariant parameters. The time-varying parameters in the single-difference correction are separated, and the time-varying parameters in each epoch are determined based on the B2b precise ephemeris and clock difference data of each GNSS satellite. Linear fitting is performed based on the single-difference correction and time-varying parameters within each epoch to obtain the time series forecast model for the corresponding GNSS satellite.
[0008] In one alternative of the first aspect, the time-invariant parameters include ambiguity parameters and tropospheric delay errors, and the time-varying parameters include satellite orbit errors and satellite clock errors.
[0009] In one alternative embodiment of the first aspect, the method further includes: After the reference station constructs the time series forecast model for each GNSS satellite, it encodes the time series forecast model for each GNSS satellite and generates a short message containing the model parameters of the time series forecast model for each GNSS satellite. The base station sends the short message to any BeiDou satellite so that the short message can be forwarded to the user terminal via the BeiDou satellite.
[0010] In one alternative embodiment of the first aspect, the frame structure of the short message includes the following global fields: Synchronization head, observation time, number of each type of GNSS satellite observed, reference satellite number of each type of GNSS satellite observed, satellite number of each GNSS satellite, model parameters of the time series forecast model for each GNSS satellite, and check code; The model parameters of the time series forecasting model include the intercept of the fitted line and the slope of the fitted line.
[0011] Secondly, this application also provides a satellite-based centimeter-level augmentation positioning device based on B2b precise ephemeris, comprising: The data acquisition module is used to receive short messages sent by BeiDou satellites and obtain time series forecast models for each GNSS satellite based on the short messages; The data acquisition module is also used to determine the GNSS satellites observed at the current epoch and to receive B2b precise ephemeris and clock bias data for each observed satellite. The data acquisition module is also used to acquire the carrier single-difference phase observation values of each observation satellite within the current epoch; The correction calculation module is used to calculate the single-difference correction forecast value of the corresponding observation satellite within the current epoch using the time series forecast model of each observation satellite; The positioning enhancement module is used to correct the corresponding carrier single-difference phase observation value based on the single-difference correction prediction value, so as to obtain the corrected carrier single-difference phase observation value. The positioning enhancement module is also used to perform precise positioning based on the B2b precise ephemeris and clock difference data corresponding to each observation satellite, combined with the corrected carrier single-difference phase observation value, to obtain the positioning result of the user terminal in the current epoch. The time series forecast model is constructed based on observation data of each GNSS satellite from the reference station during historical periods.
[0012] In an alternative embodiment of the second aspect, the apparatus further includes a model building module for building the time series forecasting model, the building process comprising the following steps: The observation data of each GNSS satellite from the reference station within multiple epochs of the historical period are obtained, and the carrier phase observation value of each GNSS satellite within each epoch is obtained. An ionospherically-free array was constructed and inter-satellite single-difference calculations were performed to obtain the carrier single-difference phase observation values for each GNSS satellite; For each GNSS satellite, the single-difference correction for each epoch is calculated by combining the coordinates of the reference station and the carrier single-difference phase observation. Time-varying characteristic analysis is performed based on single-difference corrections, which are expressed as the sum of time-varying parameters and time-invariant parameters. The time-varying parameters in the single-difference correction are separated, and the time-varying parameters in each epoch are determined based on the B2b precise ephemeris and clock difference data of each GNSS satellite. Linear fitting is performed based on the single-difference correction and time-varying parameters within each epoch to obtain the time series forecast model for the corresponding GNSS satellite.
[0013] In one alternative of the second aspect, the time-invariant parameters include ambiguity parameters and tropospheric delay errors, and the time-varying parameters include satellite orbit errors and satellite clock errors.
[0014] Thirdly, this application also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the method provided by the first aspect of this application or any implementation thereof.
[0015] Fourthly, this application also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method provided by the first aspect of this application or any implementation thereof.
[0016] The beneficial effects of the technical solution provided in this application include at least the following: In this embodiment, a time series forecast model for each GNSS satellite is constructed using a base station. The user terminal only needs to receive BeiDou short messages to obtain model parameters. Combined with B2b precise ephemeris, clock difference data, and carrier single-difference phase observations, global centimeter-level positioning without the need for a terrestrial communication network is achieved.
[0017] In terms of convergence performance, the embodiments of this application use single-difference corrections to correct carrier phase observations to a “precise pseudorange”, eliminating the long convergence process of traditional precise single-point positioning. The user terminal can achieve centimeter-level accuracy in the first epoch, and the convergence time is improved from minutes to seconds or even instantaneous, which is significantly better than existing satellite-based technologies.
[0018] In terms of coverage, since it relies solely on low-bandwidth short message transmission, the embodiments of this application can still provide stable and continuous high-precision services in areas without terrestrial mobile communication signals, such as the open sea, deserts, and deep mountains, greatly expanding the application scope.
[0019] In terms of positioning accuracy, the user end inherits the accuracy of the base station, with a measured horizontal accuracy of 2-5 cm and an elevation accuracy of 5-10 cm, which is comparable to the performance of ground-based augmentation network RTK.
[0020] In terms of resource consumption, compared to traditional RTK which requires continuous occupation of the communication channel, the embodiments of this application only transmit a small amount of data during the initialization phase, saving more than 90% of communication traffic and significantly reducing user costs and network load.
[0021] In addition, after initialization, the user terminal mainly relies on the local forecast model and is not sensitive to momentary interruptions in the communication link. Even if short messages are temporarily unavailable, it can still maintain high accuracy. The system's robustness is far higher than that of traditional solutions that rely on continuous communication. Attached Figure Description
[0022] To more clearly illustrate the technical solutions in this application or related technologies, the drawings used in the description of the embodiments or related technologies will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0023] Figure 1 This is a flowchart illustrating a satellite-based centimeter-level augmented positioning method based on B2b precise ephemeris provided in an embodiment of this application. Figure 2 This is a schematic diagram of the structure of a satellite-based centimeter-level augmented positioning device based on B2b precise ephemeris provided in an embodiment of this application; Figure 3 This is a schematic diagram of the structure of the electronic device provided in the embodiments of this application. Detailed Implementation
[0024] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.
[0025] The terms "comprising" and "having," and any variations thereof, in the specification, claims, and accompanying drawings of this application are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or modules is not limited to the steps or modules listed, but may optionally include steps or modules not listed, or may optionally include other steps or modules inherent to such process, method, product, or apparatus.
[0026] It should be noted that the terms "first" and "second" used in this application are merely to distinguish similar objects and do not represent a specific ordering of the objects. It is understood that "first" and "second" can be interchanged in a specific order or sequence where permitted. It should be understood that the objects distinguished by "first" and "second" can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in an order other than those described or illustrated herein.
[0027] It should be noted that with the full completion of the BeiDou-3 global system, its B2b frequency point has begun to provide users with high-precision orbit and clock difference information, with an update frequency of 1–5 minutes and an accuracy better than 5 cm (orbit) and 0.1 ns (clock difference). This capability makes it possible to build new satellite-based augmentation services. Although PPP fusion positioning can be performed using B2b ephemeris, the ground center still needs to continuously broadcast correction data streams, resulting in high communication overhead and insufficient exploitation of time-varying patterns in historical data.
[0028] Meanwhile, the BeiDou system's unique short message communication function provides a distinctive advantage for information exchange in low-bandwidth scenarios. Traditional enhancement services require the continuous transmission of a large number of correction values, but the short message channel has limited capacity and cannot support high-frequency data streams. Therefore, how to transmit sufficient information within a single short message to support subsequent multi-epoch high-precision positioning has become a technical challenge.
[0029] The present application will now be described in detail with reference to specific embodiments.
[0030] Next, combine Figure 1 This application introduces a satellite-based centimeter-level augmented positioning method based on B2b precise ephemeris, provided by an embodiment of this application. For details, please refer to... Figure 1 , Figure 1 This diagram illustrates a flow chart of a satellite-based centimeter-level augmentation positioning method based on B2b precise ephemeris, provided in an embodiment of this application. Figure 1 As shown, the method includes the following steps: S101 receives short messages from BeiDou satellites and obtains time series forecast models for each GNSS satellite based on the short messages; S102, determine the GNSS satellites observed at the current epoch, and receive B2b precise ephemeris and clock bias data for each observed satellite; S103, collect the carrier single-difference phase observation values of each observed satellite within the current epoch; S104, the single-difference correction forecast value of the corresponding observation satellite within the current epoch is calculated by the time series forecast model of each observation satellite; S105, Based on the predicted value of the single-difference correction, correct the corresponding carrier single-difference phase observation value to obtain the corrected carrier single-difference phase observation value; S106. Based on the B2b precise ephemeris and clock difference data corresponding to each observation satellite, combined with the corrected carrier single-difference phase observation value, precise positioning is performed to obtain the positioning result of the user terminal in the current epoch.
[0031] In some embodiments, a time series forecast model for each GNSS satellite can be constructed using a reference station at any time period prior to S101, including the following steps: First, the observation data of each GNSS satellite from the reference station within multiple epochs of the historical period are obtained, and the carrier phase observation value of each GNSS satellite within each epoch is obtained. The observation method is expressed as follows: ; in, The carrier phase observation value of satellite s at frequency i for reference station r; The geometric distance between the base station r and the satellite s; The frequency-dependent ionospheric delay factor; For ionospheric delay, For tropospheric delay; The speed of light; The receiver clock bias of reference station r; For satellite clock bias; The carrier wavelength; For integer ambiguity; For the phase hardware delay of the receiver; For the phase hardware delay of the satellite; This is multipath error; To observe noise.
[0032] Furthermore, in order to eliminate the most significant and difficult-to-model ionospheric delay error, an ionospheric-free combination was constructed to eliminate the first-order ionospheric term in the observation equation, and inter-satellite single difference was calculated to obtain the carrier single difference phase observation value of each GNSS satellite.
[0033] It should be noted that when performing inter-satellite single-difference calculation, the difference between the observed carrier phase of GNSS satellite s and any reference satellite q is calculated to obtain the carrier single-difference phase observation value of GNSS satellite s.
[0034] Next, given the known precise coordinates of the base station, the single-difference correction for satellite s at each epoch can be calculated using these coordinates, along with the satellite's B2b precise ephemeris and clock bias data. This includes: For each GNSS satellite s, the single-difference correction for each epoch is calculated by combining the coordinates of the reference station and the carrier single-difference phase observations, and is expressed as follows: ; Subsequently, time-varying characteristic analysis was performed based on the single-difference correction. The single-difference correction was expressed as the sum of the time-varying parameter and the time-invariant parameter, as shown in the formula: ; in, This represents the single-difference correction for satellite s; Indicates satellite orbital error; This indicates satellite clock bias under ionospheric conditions. Indicates tropospheric delay error; This represents the ambiguity parameter under the condition of no ionosphere combination.
[0035] Specifically, the time-invariant parameters obtained from time-varying feature analysis include ambiguity parameters. and tropospheric delay error Among them, the ambiguity parameter remains constant when no cycle slip occurs; the tropospheric delay error changes slowly in a short period of time (such as within a few minutes) and can be regarded as a quasi-constant, or it can be processed using a random walk model. Overall, the time-invariant parameter can be regarded as an invariant parameter.
[0036] Specifically, time-varying parameters include satellite orbital errors. and satellite clock bias Time-varying parameters are the main source of changes in single-difference corrections, and the changes in time-varying parameters are regular and smooth. The time-varying parameters within each epoch can be determined by the B2b precise ephemeris and clock difference data of GNSS satellites.
[0037] Therefore, a time series forecast model for the corresponding GNSS satellite can be constructed by linear fitting of the single-difference correction and time-varying parameters for each epoch (e.g., data from 300 epochs), as expressed by the formula: ; in, For the first The single-difference correction for each epoch, where a represents the intercept of the fitted line of the time series forecast model and b represents the slope of the fitted line of the time series forecast model.
[0038] The time series forecast model for each GNSS satellite can be constructed based on the process of building the time series forecast model according to the above embodiments.
[0039] In some embodiments, after constructing the time series forecast model for each GNSS satellite, the model parameters of the time series forecast model can be sent to the user terminal via BeiDou short message service, including the following steps: The time series forecast model of each GNSS satellite is encoded, that is, the information containing the model parameters of the time series forecast model is encoded into a short message according to the pre-designed binary encoding format, and a short message containing the model parameters of the time series forecast model of each GNSS satellite is generated. The base station sends the short message to any BeiDou satellite so that the short message can be forwarded to the user terminal via the BeiDou satellite.
[0040] Specifically, the frame structure of the short message includes the following global fields: Synchronization header (16 bits), observation time (17 bits), number of each type of GNSS satellite observed (4 bits), reference satellite number of each type of GNSS satellite observed (5 bits), satellite number of each GNSS satellite (5 bits), model parameters of the time series forecast model of each GNSS satellite, and check code (16 bits). The model parameters of the time series forecast model include the intercept of the fitted line (8 bits) and the slope of the fitted line (8 bits).
[0041] It should be noted that the types of GNSS satellites include, but are not limited to, GPS satellites, BeiDou Navigation Satellite System (BDS) satellites, Galileo satellites, etc.; each GNSS satellite has a number that is a unique identification number (Pseudo-Random Noise Code, PRN), which the receiver can identify to determine which satellite it is tracking; the reference satellite is a benchmark satellite in the corresponding GNSS system selected when positioning based on GNSS satellites, which can be used to calculate inter-satellite differences.
[0042] The above encoding methods can significantly save bandwidth and meet the requirements for short message transmission.
[0043] For example, when broadcasting 5 BDS satellites and 3 GPS satellites, the total number of bits in the broadcast short message is: 16 (synchronization header) + 17 (time) + 4 (number of GPS satellites) + 4 (number of BDS satellites) + 5 (GPS reference satellites) + 5 (BDS reference satellites) + (5+8+8)×3 (number of GPS satellites) + (5+8+8)×5 (BDS satellites) + 16 (CRC) = 249 bits (approximately 32 bytes). The size, range, and resolution of each field are shown in Table 1.
[0044] Table 1 Binary Encoding Field Information
[0045] In some embodiments, in S101, the user terminal can receive short messages sent by the BeiDou satellite, parse the short messages, and obtain the model parameters of the time series forecast model for each GNSS satellite, so that the user terminal can directly use the time series forecast model for calculation locally.
[0046] In S102, the GNSS satellites observed by the user terminal at the current epoch can be determined, and the B2b precise ephemeris and clock bias data of the observed satellites can be easily obtained.
[0047] In S103, the user terminal can easily obtain the carrier single-difference phase observation value of the observed satellite s within the current epoch based on the observation data, expressed as: .
[0048] In S104, using the time series forecast model of the corresponding observed satellite s, the single-difference correction forecast value for the current epoch with respect to observed satellite s can be calculated locally at the user end, expressed as: .
[0049] Subsequently, in S105, the carrier single-difference phase observation value calculated in S103 can be used to predict the single-difference correction value. To perform the correction, apply the following formula: ; in, This represents the corrected carrier single-difference phase observation.
[0050] The user terminal can perform the above steps S102-S105 on each observed GNSS satellite to obtain the corrected carrier single-difference phase observation value of the corresponding GNSS satellite.
[0051] In S106, precise positioning can be achieved by combining the B2b precise ephemeris and clock bias data corresponding to each observation satellite with the corrected carrier single-difference phase observation value, and then the positioning result of the user terminal in the current epoch can be calculated.
[0052] The above correction process transforms carrier observations, which contain complex errors and unfixed ambiguities, into an equivalent highly accurate "pseudorange" observation. This is because the predicted correction... Almost all common errors and ambiguities are eliminated, making the corrected observations... It primarily reflects the geometric distance between the satellite and the user.
[0053] It should be noted that the method provided in this application creatively constructs a new paradigm of hybrid enhanced services through a base station preprocessing and user-end post-correction model. In the process of constructing the time series forecast model, by decomposing the corrections into time-varying and time-invariant parameters and modeling the time-varying parameters to form the time series forecast model, the user end can maintain high accuracy for a long time after receiving the pre-constructed time series forecast model, thus eliminating the dependence on continuous differential data streams. The user end can correct the carrier phase using the forecast corrections, cleverly circumventing the problem of real-time fixation of carrier phase ambiguity, transforming the problem into a pseudorange positioning problem that does not require convergence, achieving a balance between positioning speed and accuracy. Furthermore, this application fully utilizes the characteristics of short message communication, transmitting only the model parameters of the time series forecast model, rather than a continuous stream of observations, making satellite-based centimeter-level services possible under low bandwidth conditions.
[0054] The following are device embodiments of this application, which can be used to execute the method embodiments of this application. For details not disclosed in the device embodiments of this application, please refer to the method embodiments of this application.
[0055] Please see below. Figure 2 The image below is a schematic diagram of a satellite-based centimeter-level augmentation positioning device based on B2b precise ephemeris, provided as an exemplary embodiment of this application. The device includes: The data acquisition module is used to receive short messages sent by BeiDou satellites and obtain time series forecast models for each GNSS satellite based on the short messages; The data acquisition module is also used to determine the GNSS satellites observed at the current epoch and to receive B2b precise ephemeris and clock bias data for each observed satellite. The data acquisition module is also used to acquire the carrier single-difference phase observation values of each observation satellite within the current epoch; The correction calculation module is used to calculate the single-difference correction forecast value of the corresponding observation satellite within the current epoch using the time series forecast model of each observation satellite; The positioning enhancement module is used to correct the corresponding carrier single-difference phase observation value based on the single-difference correction prediction value, so as to obtain the corrected carrier single-difference phase observation value. The positioning enhancement module is also used to perform precise positioning based on the B2b precise ephemeris and clock difference data corresponding to each observation satellite, combined with the corrected carrier single-difference phase observation value, to obtain the positioning result of the user terminal in the current epoch. The time series forecast model is constructed based on observation data of each GNSS satellite from the reference station during historical periods.
[0056] In some embodiments, the apparatus further includes a model building module for building the time series forecasting model, the building process including the following steps: The observation data of each GNSS satellite from the reference station within multiple epochs of the historical period are obtained, and the carrier phase observation value of each GNSS satellite within each epoch is obtained. An ionospherically-free array was constructed and inter-satellite single-difference calculations were performed to obtain the carrier single-difference phase observation values for each GNSS satellite; For each GNSS satellite, the single-difference correction for each epoch is calculated by combining the coordinates of the reference station and the carrier single-difference phase observation. Time-varying characteristic analysis is performed based on single-difference corrections, which are expressed as the sum of time-varying parameters and time-invariant parameters. The time-varying parameters in the single-difference correction are separated, and the time-varying parameters in each epoch are determined based on the B2b precise ephemeris and clock difference data of each GNSS satellite. Linear fitting is performed based on the single-difference correction and time-varying parameters within each epoch to obtain the time series forecast model for the corresponding GNSS satellite.
[0057] It should be noted that the apparatus provided in the above embodiments, when executing a satellite-based centimeter-level augmentation positioning method based on B2b precise ephemeris, is only illustrated by the division of the above functional modules. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. Furthermore, the apparatus and method embodiments provided in the above embodiments belong to the same concept, and their implementation process is detailed in the method embodiments, which will not be repeated here.
[0058] This application also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the steps of any of the methods described above.
[0059] Please see Figure 3 This is a structural block diagram of an electronic device provided in an embodiment of this application.
[0060] like Figure 3 As shown, the electronic device includes a processor and a memory.
[0061] In this embodiment, the processor is the control center of the computer system, and can be a processor of a physical machine or a processor of a virtual machine. The processor may include one or more processing cores, such as a 4-core processor, an 8-core processor, etc. The processor can be implemented using at least one hardware form of DSP (Digital Signal Processing), FPGA (Field-Programmable Gate Array), or PLA (Programmable Logic Array).
[0062] A processor can also include a main processor and a coprocessor. The main processor is used to process data in the wake-up state and is also called the CPU (Central Processing Unit). The coprocessor is a low-power processor used to process data in the standby state.
[0063] The memory may include one or more computer-readable storage media, which may be non-transitory. The memory may also include high-speed random access memory and non-volatile memory, such as one or more disk storage devices or flash memory devices. In some embodiments of this application, the non-transitory computer-readable storage media in the memory are used to store at least one instruction, which is executed by a processor to implement the methods in the embodiments of this application.
[0064] In some embodiments, the electronic device further includes a peripheral device interface and at least one peripheral device. The processor, memory, and peripheral device interface are connected via a bus or signal line. Each peripheral device is connected to the peripheral device interface via a bus, signal line, or circuit board. Specifically, the peripheral device includes: a display screen, a camera, and audio circuitry. The peripheral device interface can be used to connect at least one I / O (Input / Output) related peripheral device to the processor and memory.
[0065] In some embodiments of this application, the processor, memory, and peripheral device interfaces are integrated on the same chip or circuit board; in other embodiments of this application, any one or two of the processor, memory, and peripheral device interfaces can be implemented on separate chips or circuit boards. This application does not specifically limit the implementation in this regard.
[0066] The electronic device structural block diagrams shown in the embodiments of this application do not constitute a limitation on the electronic device. The electronic device may include more or fewer components than shown, or combine certain components, or use different component arrangements.
[0067] This application also provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the steps of the methods in any of the foregoing embodiments. The computer-readable storage medium may include, but is not limited to, any type of disk, including floppy disks, optical disks, DVDs, CD-ROMs, microdrives, as well as magneto-optical disks, ROMs, RAMs, EPROMs, EEPROMs, DRAMs, VRAMs, flash memory devices, magnetic cards or optical cards, nanosystems (including molecular memory ICs), or any type of medium or device suitable for storing instructions and / or data.
[0068] 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 parts that contribute to the related technology, can be embodied in the form of software products. 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.
[0069] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application 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. Such 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 this application.
Claims
1. A satellite-based centimeter-level augmented positioning method based on B2b precise ephemeris, characterized in that, Applied to the user end, including: Receive short messages sent by BeiDou satellites and obtain time series forecast models for each GNSS satellite based on the short messages; Determine the GNSS satellites observed at the current epoch, and receive B2b precise ephemeris and clock bias data for each observed satellite; Collect carrier single-difference phase observations for each observed satellite within the current epoch; The single-difference correction forecast value for the corresponding observed satellite within the current epoch is calculated using the time series forecast model of each observed satellite. Based on the predicted value of the single-difference correction, the corresponding carrier single-difference phase observation value is corrected to obtain the corrected carrier single-difference phase observation value; Precise positioning is achieved by combining the B2b precise ephemeris and clock bias data corresponding to each observation satellite with the corrected carrier single-difference phase observation value, and the positioning result of the user terminal in the current epoch is obtained. The time series forecast model is constructed based on observation data of each GNSS satellite from the reference station during historical periods.
2. The satellite-based centimeter-level augmented positioning method based on B2b precise ephemeris as described in claim 1, characterized in that, The construction process of the time series forecasting model includes the following steps: The observation data of each GNSS satellite from the reference station within multiple epochs of the historical period are obtained, and the carrier phase observation value of each GNSS satellite within each epoch is obtained. An ionospherically-free array was constructed and inter-satellite single-difference calculations were performed to obtain the carrier single-difference phase observation values for each GNSS satellite; For each GNSS satellite, the single-difference correction for each epoch is calculated by combining the coordinates of the reference station and the carrier single-difference phase observation. Time-varying characteristic analysis is performed based on single-difference corrections, which are expressed as the sum of time-varying parameters and time-invariant parameters. The time-varying parameters in the single-difference correction are separated, and the time-varying parameters in each epoch are determined based on the B2b precise ephemeris and clock difference data of each GNSS satellite. Linear fitting is performed based on the single-difference correction and time-varying parameters within each epoch to obtain the time series forecast model for the corresponding GNSS satellite.
3. The satellite-based centimeter-level augmented positioning method based on B2b precise ephemeris according to claim 2, characterized in that, The time-invariant parameters include ambiguity parameters and tropospheric delay errors, while the time-varying parameters include satellite orbit errors and satellite clock errors.
4. The satellite-based centimeter-level augmentation positioning method based on B2b precise ephemeris according to claim 2, characterized in that, The method further includes: After the reference station constructs the time series forecast model for each GNSS satellite, it encodes the time series forecast model for each GNSS satellite and generates a short message containing the model parameters of the time series forecast model for each GNSS satellite. The base station sends the short message to any BeiDou satellite so that the short message can be forwarded to the user terminal via the BeiDou satellite.
5. The satellite-based centimeter-level augmented positioning method based on B2b precise ephemeris according to claim 4, characterized in that, The frame structure of the short message includes the following global fields: Synchronization head, observation time, number of each type of GNSS satellite observed, reference satellite number of each type of GNSS satellite observed, satellite number of each GNSS satellite, model parameters of the time series forecast model for each GNSS satellite, and check code; The model parameters of the time series forecasting model include the intercept of the fitted line and the slope of the fitted line.
6. A satellite-based centimeter-level augmentation positioning device based on B2b precise ephemeris, characterized in that, include: The data acquisition module is used to receive short messages sent by BeiDou satellites and obtain time series forecast models for each GNSS satellite based on the short messages; The data acquisition module is also used to determine the GNSS satellites observed at the current epoch and to receive B2b precise ephemeris and clock bias data for each observed satellite. The data acquisition module is also used to acquire the carrier single-difference phase observation values of each observation satellite within the current epoch; The correction calculation module is used to calculate the single-difference correction forecast value of the corresponding observation satellite within the current epoch using the time series forecast model of each observation satellite; The positioning enhancement module is used to correct the corresponding carrier single-difference phase observation value based on the single-difference correction prediction value, so as to obtain the corrected carrier single-difference phase observation value. The positioning enhancement module is also used to perform precise positioning based on the B2b precise ephemeris and clock difference data corresponding to each observation satellite, combined with the corrected carrier single-difference phase observation value, to obtain the positioning result of the user terminal in the current epoch. The time series forecast model is constructed based on observation data of each GNSS satellite from the reference station during historical periods.
7. A satellite-based centimeter-level augmentation positioning device based on B2b precise ephemeris as described in claim 6, characterized in that, The device further includes a model building module, which is used to build the time series forecasting model. The building process includes the following steps: The observation data of each GNSS satellite from the reference station within multiple epochs of the historical period are obtained, and the carrier phase observation value of each GNSS satellite within each epoch is obtained. An ionospherically-free array was constructed and inter-satellite single-difference calculations were performed to obtain the carrier single-difference phase observation values for each GNSS satellite; For each GNSS satellite, the single-difference correction for each epoch is calculated by combining the coordinates of the reference station and the carrier single-difference phase observation. Time-varying characteristic analysis is performed based on single-difference corrections, which are expressed as the sum of time-varying parameters and time-invariant parameters. The time-varying parameters in the single-difference correction are separated, and the time-varying parameters in each epoch are determined based on the B2b precise ephemeris and clock difference data of each GNSS satellite. Linear fitting is performed based on the single-difference correction and time-varying parameters within each epoch to obtain the time series forecast model for the corresponding GNSS satellite.
8. A satellite-based centimeter-level augmentation positioning device based on B2b precise ephemeris according to claim 7, characterized in that, The time-invariant parameters include ambiguity parameters and tropospheric delay errors, while the time-varying parameters include satellite orbit errors and satellite clock errors.
9. 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 the steps of the method as described in any one of claims 1 to 5.
10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1 to 5.