GNSS augmentation positioning method and system based on custom RTCM message

Abstract

The application discloses a GNSS enhanced positioning method based on self-defined RTCM electric text and belongs to the field of GNSS high-precision navigation and positioning. The method comprises the following steps: a data processing center generates and broadcasts a standard RTCM electric text used by a conventional network RTK at the same time, and generates a self-defined RTCM electric text containing various GNSS enhanced information, wherein the enhanced information comprises high-precision regional atmospheric correction information, ionospheric flicker flag information, regional atmospheric model configuration and quality indexes. After a user positioning terminal receives the self-defined RTCM electric text, the quality indexes are used to evaluate the advantages and disadvantages of a current observation environment, and a positioning second-order polynomial model is adaptively optimized, so that the positioning precision and reliability are effectively improved, especially during an ionosphere active period. The application solves the technical problems that traditional enhanced service information is single and cannot transmit refined quality control information to a terminal, and provides a strong guarantee for the stable application of high-precision GNSS service under various conditions.

Description

Technical Field

[0001] This invention belongs to the field of GNSS high-precision navigation and positioning, specifically relating to a GNSS enhanced positioning method and system based on a custom RTCM message, which is suitable for improving the performance of positioning terminals in atmospheric disturbance environments. Background Technology

[0002] Enhanced positioning services of the Global Navigation Satellite System (GNSS), such as Real-Time Kinematic (RTK), are widely used in surveying, transportation, agriculture, and other fields. These services typically rely on a network of one or more Continuously Operating Reference Stations (CORS). By analyzing network data, high-precision error correction information, such as atmospheric corrections, is calculated and broadcast to the user's positioning terminal via standard formats such as RTCM.

[0003] The Radio Technical Commission for Maritime Services (RTCM) standard message is a widely supported and universally accepted format within the industry. However, with the development of GNSS technology and the increasing demand for higher accuracy and reliability positioning, existing open standard messages have shown limitations in certain aspects:

[0004] 1. Insufficient atmospheric information expression capability: The ionospheric correction messages (such as types 1030 and 1031) used in the RTCM standard for network RTK technology are mainly for the Global Positioning System (GPS) and Global Navigation Satellite System (GLONASS), and the technical means are limited, making it difficult to meet the needs of multi-system fusion and more refined atmospheric modeling.

[0005] 2. Lack of detailed description of data quality: Currently, we are in a year of high solar activity, and intense ionospheric activity will severely affect GNSS signal propagation, thereby reducing the quality of CORS network observation data and the reliability of positioning services. Traditional RTCM messages mainly broadcast error corrections, but rarely provide information on the quality assessment of these corrections themselves. Even if the user positioning terminal receives the corrections, it cannot know whether the current corrections were calculated under a stable or turbulent space environment, making it difficult to adopt optimal stochastic models and data processing strategies at the terminal side to address potential risks.

[0006] Therefore, the types of information and quality descriptions that current standard RTCM messages can carry are insufficient to enable users to effectively evaluate and optimally utilize the received augmentation information in complex environments, especially those with active ionospheres, thus limiting further improvements in positioning performance. Summary of the Invention

[0007] The purpose of this invention is to address the problems of traditional augmentation services having limited information and being unable to deliver refined quality control information to terminals, as well as the insufficient positioning accuracy and reliability of existing GNSS augmentation services under complex space weather conditions. This invention provides a GNSS augmentation positioning method based on a custom RTCM message. By applying for a dedicated message number (4051) from the RTCM Association, a new RTCM message format is defined. While generating and broadcasting the message information used by conventional network RTK, the data processing center also generates a custom RTCM message containing various GNSS augmentation information. This augmentation information includes not only high-precision regional atmospheric (tropospheric and ionospheric) correction information, but also innovatively introduces quality control indicators such as ionospheric scintillation marker information and regional atmospheric model configuration. This enables the delivery of richer and more refined augmentation correction and quality control information to the positioning terminal, thereby significantly improving the positioning accuracy, reliability, and robustness under various conditions, especially in severe space weather environments.

[0008] According to one aspect of the present invention, a GNSS-enhanced positioning method based on a custom RTCM message is provided, comprising:

[0009] Based on real-time acquired data from the continuously operating reference station network and the location information from the user's positioning terminal, regional atmospheric error modeling is performed to obtain regional atmospheric correction information.

[0010] By introducing an accuracy factor, the accuracy of regional atmospheric correction information is classified and quantified to obtain regional atmospheric correction accuracy information.

[0011] Ionospheric scintillation information is calculated based on the satellite signal strength and phase changes received by each reference station in the continuously operating reference station network.

[0012] The regional atmospheric correction information, ionospheric scintillation information, and regional atmospheric correction accuracy information are supplemented and encoded into the standard RTCM message to obtain a custom RTCM message.

[0013] The user's real-time location information is obtained by performing location calculations based on the custom RTCM message and the standard RTCM message.

[0014] Furthermore, the following second-order polynomial model is used for regional atmospheric error modeling:

[0015]

[0016] in, At the user location or base station location Ionospheric delay at that location It's latitude. It's longitude. These are the coordinates of the region's center. These are model coefficients. It is model error.

[0017] Furthermore, based on the custom RTCM message and the standard RTCM message, a location calculation is performed to obtain the user's real-time location information, including:

[0018] Standard positioning is performed using standard RTCM messages to obtain standard positioning results;

[0019] Based on the model coefficients of the second-order polynomial model, the ionospheric delay correction value for each satellite is calculated to obtain the decoded custom RTCM message.

[0020] The weights of continuously operating reference station network data and regional atmospheric correction information are dynamically allocated to obtain a positioning solution stochastic model that matches the continuously operating reference station network data and regional atmospheric correction accuracy information.

[0021] Based on the decoded custom RTCM message and the location solution stochastic model, an atmospheric weighted least squares adjustment equation set is established to enhance the accuracy of the standard positioning results and obtain the user's real-time location information.

[0022] Furthermore, a precision factor is introduced, including:

[0023] Accuracy factors are generated based on historical research data and the posterior variance after regional atmospheric error modeling. These accuracy factors are then used to characterize the accuracy level of regional atmospheric correction information, resulting in graded and quantified regional atmospheric correction accuracy information.

[0024] Furthermore, the atmospheric weighted least squares adjustment equations are established as follows:

[0025]

[0026] in, It is the residual of the observed values. It is the atmospheric correction residual. These are observed values. It is an atmospheric correction value. It is the vector of parameters to be estimated. It is a design matrix. It is the observation weight matrix. It is an atmospheric correction weight matrix. It is a block-diagonal weight matrix.

[0027] Furthermore, the custom RTCM message includes a variety of preset sub-type messages; the sub-type messages include enhancement information for improving the positioning terminal's calculation performance, the enhancement information including regional atmospheric correction information, regional atmospheric correction accuracy information, and ionospheric scintillation information.

[0028] Furthermore, the regional atmospheric correction accuracy information includes at least one or more combinations of the following: regional atmospheric model configuration information, regional dry tropospheric delay information, regional wet tropospheric delay information, and regional ionospheric delay information.

[0029] Furthermore, the regional atmospheric model configuration information includes the region ID, reference grid point latitude and longitude, number of grid points and step size; the regional tropospheric dry delay information includes a dry delay constant term and grid residuals; the regional tropospheric wet delay information includes a wet delay constant term and grid residuals; and the regional ionospheric delay information includes delay model coefficients and grid residuals for different satellites.

[0030] Furthermore, the ionospheric scintillation information includes the ionospheric TEC index, the number of visible satellites, and the ionospheric scintillation level indication.

[0031] According to one aspect of the present invention, a GNSS-enhanced positioning system based on a custom RTCM message is provided, comprising:

[0032] The data processing center is used to perform regional atmospheric error modeling based on real-time acquired data from the continuously operating reference station network and the location information from user positioning terminals, to obtain regional atmospheric correction information; introduce an accuracy factor to classify and quantify the accuracy of the regional atmospheric correction information, to obtain regional atmospheric correction accuracy information; calculate ionospheric scintillation information based on the satellite signal strength and phase changes received by each reference station in the continuously operating reference station network; and supplement the regional atmospheric correction information, ionospheric scintillation information, and regional atmospheric correction accuracy information into the standard RTCM message to obtain a custom RTCM message.

[0033] The user positioning terminal is used to perform positioning calculations based on the custom RTCM message and the standard RTCM message to obtain the user's real-time location information.

[0034] Compared with the prior art, the beneficial effects of the present invention are:

[0035] 1. This invention introduces enhanced information such as regional atmospheric correction information, ionospheric scintillation information, and regional atmospheric correction accuracy information into the RTCM message, so that the user positioning terminal no longer blindly uses the received correction data, but can "know not only what it is, but also why it is so", which greatly improves the positioning reliability under atmospheric interference.

[0036] 2. This invention proposes atmospheric error modeling, which helps users optimize their stochastic models and calculation processes at the positioning end. This effectively suppresses errors under unfavorable conditions such as high solar activity years, resulting in better positioning performance and greatly improving the availability and reliability of GNSS high-precision services in various application scenarios.

[0037] 3. This invention solves the problem of insufficient information carrying capacity of standard messages by using both custom RTCM messages and standard RTCM messages for positioning calculation. It can meet the needs of different network RTK technology routes and fully support multiple constellation systems such as GPS, GLONASS, BDS, and Galileo, and has good forward compatibility and scalability. Attached Figure Description

[0038] 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.

[0039] Figure 1 The flowchart of the GNSS enhanced positioning method based on a custom RTCM message provided by the present invention is shown.

[0040] Figure 2 A schematic diagram of the reference station network used in the experimental verification process provided by this invention.

[0041] Figure 3 This is a schematic diagram illustrating the comparison results of terminal fixation rates provided by the present invention. Detailed Implementation

[0042] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0043] Specifically, such as Figure 1As shown, this embodiment of the invention proposes a GNSS enhanced positioning method based on a custom RTCM message, including: performing regional atmospheric error modeling based on real-time acquired continuously operating reference station network data and user positioning terminal location information to obtain regional atmospheric correction information; introducing an accuracy factor and combining it with the posterior variance after regional atmospheric error modeling to classify and quantify the accuracy of the regional atmospheric correction information to obtain regional atmospheric correction accuracy information; analyzing the satellite signal strength and phase changes received by each reference station in the continuously operating reference station network to obtain ionospheric scintillation information; supplementing the regional atmospheric correction information, ionospheric scintillation information, and regional atmospheric correction accuracy information into the standard RTCM message to obtain a custom RTCM message; and performing positioning calculation based on the custom RTCM message and the standard RTCM message to obtain the user's real-time location information.

[0044] Specifically, the CORS station network or data processing center generates a custom-formatted RTCM message based on real-time or near-real-time CORS network observation data. This message, with message number 4051, contains several preset sub-type messages. These sub-type messages include enhancement information to improve the performance of the positioning terminal's calculations. This enhancement information includes at least: regional atmospheric correction information, regional atmospheric correction accuracy information, and ionospheric scintillation information. The custom RTCM message is broadcast to one or more user positioning terminals via a data link. The user positioning terminals perform standard positioning using the standard RTCM message to obtain the standard positioning result. Simultaneously, they receive and decode the custom RTCM message, optimizing their internal positioning calculation algorithm based on the enhancement information contained in the custom RTCM message, thereby enhancing the accuracy of the standard positioning result and obtaining more accurate and reliable location information.

[0045] Specifically, global navigation satellite systems, such as GPS, GLONASS, BDS, and Galileo, are not user positioning terminals, but rather satellite infrastructure that provides core observation signals for the entire positioning system (including continuously operating reference stations, data processing centers, and user positioning terminals).

[0046] Specifically, CORS network data is GNSS observation data, which is the data source for subsequent regional atmospheric error modeling; regional atmospheric correction information (ionospheric delay and tropospheric delay correction) is used to correct errors caused by atmospheric disturbances during the propagation of GNSS signals; the positioning calculation at the user end needs to be based on GNSS observation data and combined with the enhancement information (atmospheric correction and quality control information) in the RTCM message.

[0047] Specifically, this invention applied for a proprietary message number (4051) from the RTCM Association, defining a new RTCM message format. The core of this method lies in the fact that, while generating and broadcasting message information used by conventional network RTK, the CORS (Continuously Operating Reference Station) data processing center also generates a custom RTCM message containing various GNSS enhancement information. This enhancement information not only includes high-precision regional atmospheric (tropospheric and ionospheric) correction information, but also innovatively introduces quality control indicators such as ionospheric scintillation marker information and regional atmospheric model configuration.

[0048] Specifically, the custom-formatted RTCM message in step 1 uses the RTCM3 standard protocol framework structure, and the specific message structure is shown in Table 1.

[0049] Table 1. Structure of Custom 4051 Messages

[0050]

[0051] Specifically, based on the enhanced information content of the custom RTCM message in step 1, new message types are designed, as shown in Table 2. It should be noted that the custom RTCM message is a supplement to the standard RTCM message. For example, existing RTCM messages such as track, clock difference, and VTEC model messages are directly reused and no longer designed separately.

[0052] Table 2 Message Types for Custom 4051 Messages

[0053]

[0054]

[0055] Specifically, based on the enhanced information content of the custom RTCM message in step 1, the data types are defined as shown in Table 3:

[0056] Table 3 Data Types of Custom 4051 Messages

[0057] DF number DF Name DF range DF resolution Data types Notes DF002 Message DF003 Reference Site ID 0-4095 uint12 The reference station ID is determined by the service provider. Its primary purpose is to link all message data to its unique source. In situations where multiple services may use the same data link frequency, it helps distinguish between expected and unexpected data. It also helps accommodate multiple reference stations within a single data link transmission. In reference network applications, the reference station ID plays a crucial role because it serves as the link between a specific reference station's observation messages and auxiliary information contained in other messages, ensuring proper functioning. Therefore, service providers should ensure that reference station IDs are unique throughout the network and only reallocate IDs when absolutely necessary. Service providers may need to coordinate the allocation of reference station IDs with other service providers in their region to avoid conflicts. This can be particularly critical for devices accessing multiple services, depending on the specific services and information distribution methods. DF004 GNSS epoch time (TOW) 0-604,799,999ms 1ms uint30 GPS epoch time is measured in milliseconds and begins at the start of a GPS week, which starts at midnight GMT on Saturday night / Sunday morning, measured in GPS time (not UTC). DF025 Antenna reference point ECEF-X ±13,743,895.3471m 0.0001m int38 The X-coordinate of the antenna reference point is based on the ITRF epoch given in the year of the ITRF implementation. DF026 Antenna reference point ECEF-Y ±13,743,895.3471m 0.0001m int38 The antenna reference point Y-coordinate is based on the ITRF epoch given in the ITRF implementation year. DF027 Antenna reference point ECEF-Z ±13,743,895.3471m 0.0001m int38 The Z-coordinate of the antenna reference point is based on the ITRF epoch given in the year of ITRF implementation. DF141 Reference station indicator 0-1 1 bit(1) 0 - Real physical reference station; 1 - Non-physical or computationally generated reference station. Note: Non-physical or computationally generated reference stations are usually calculated based on information from a network of reference stations. Different methods have been developed over the years. Non-physical or computationally generated reference stations are sometimes trademarked and may not be compatible. Examples of these names include "virtual reference station," "pseudo-reference station," and "personalized reference station." DF387 Number of satellites 0-255 1 uint8 Number of satellites DF388 Multi-message indicator 0-1 1 bit(1) Indicators used to transmit messages with the same message number and epoch time: 0 - the last message in the sequence; 1 - multiple messages are being transmitted. DF516 Regional reference latitude ±90.0° 0.01° int14 The regional reference latitude specifies the Northern Hemisphere as positive latitude and the Southern Hemisphere as negative latitude. DF517 Regional reference longitude ±180.0° 0.01° int15 The regional reference longitude designates the Eastern Hemisphere as positive longitude and the Western Hemisphere as negative longitude. DF518 Regional latitude step 0.1°~3.2° 0.01° uint9 DF519 Regional longitude step 0.1°~3.2° 0.01° uint9 DF520 Dry delay constant 0~8.192 0.004 uint11 DF521 Grid residuals of tropospheric dry delay ±1.024 0.004 int9 DF522 Wetness constant 0~1.024 0.004 uint8 DF523 Grid residuals of tropospheric wet delay ±0.248 0.004 int7 DF524 Unit weight error 0~10.20TECU 0.08 uint7 DF525 Model coefficients C00 ±327.64TECU 0.08 int13 DF526 Model coefficients C11 ±32.766 TECU / degree2 0.008 int14 DF527 Model coefficients C01 / C10 ±65.528 TECU / degree 0.016 int13 DF528 Model coefficient variance ±5.08 0.08 int7 DF529 Grid residuals of ionospheric delay ±10.20 0.08 int8 DF530 Baseline length 0~819.2km 0.1km uint13 Distance from interpolation point to main reference station

[0058] Specifically, the core principle behind the data processing center's generation of enhanced information is to model spatial correlation errors (primarily atmospheric corrections, which can also be understood as atmospheric delays) within the region using CORS network data. An effective method is to use a low-order surface model to fit the spatial variation characteristics of atmospheric corrections in the geographic coordinate system. The data processing center aggregates real-time GNSS observation data from all CORS stations within its coverage area. Since the precise coordinates of each reference station are known, path-related errors, mainly tropospheric and ionospheric delays, can be separated from the raw observations through differential processing and other methods. To provide regional, continuously covered atmospheric correction services to user positioning terminals, a low-order surface model is used to fit the geographic spatial distribution characteristics of these error terms.

[0059] Specifically, for ionospheric delay, regional atmospheric error is modeled by its variation with latitude and longitude within a specific region, represented by the following second-order polynomial model:

[0060] (1)

[0061] in, At the user location or base station location Ionospheric delay at that location Indicates latitude, Indicates longitude. These are the coordinates of the region's center. The model coefficients were calculated by the CORS Network Data Processing Center using least squares adjustment. It is model error.

[0062] Specifically, the user positioning terminal obtains its location coordinates through the following two steps: First, the data processing center substitutes the coordinates of each reference station and the coordinates of the regional center into equation (1), and calculates the optimal model coefficients of the region at that moment using the least squares method. These coefficients are then encoded into a custom RTCM message for broadcast. The coordinates of each reference station are given; then, the user positioning terminal receives and decodes the message, extracts the model coefficients and the coordinates of the regional center, and substitutes its own coordinates into equation (1) to solve for the ionospheric delay at the current location, which is used to correct the observation equation (equation 2) to improve the positioning accuracy. The coordinates of the user's location.

[0063] Specifically, tropospheric delay, especially its wet delay component, can also be expressed and broadcast using a similar model or gridded approach.

[0064] In a preferred embodiment of the present invention, in order to reduce the amount of data to be broadcast, a gridded approach is adopted, that is, a regional constant term (DF522) and residual values ​​(DF523) at each grid point are broadcast, and the user positioning terminal can obtain the correction value at its position by interpolation.

[0065] Specifically, the assessment of atmospheric correction information quality includes: after performing the least squares solution of the above model coefficients, a key quality indicator is obtained—unit weighted mean square error. This reflects the goodness of fit of the model to actual observation data. This value (corresponding to DF527) and the variance of the model coefficients (corresponding to DF528) are broadcast together, providing a direct basis for users to assess the overall accuracy of the current ionospheric model. Furthermore, for correction information such as tropospheric corrections, this invention introduces a "Precision Factor," which quantifies the precision of corrections based on historical data statistical analysis and the posterior variance of the second-order polynomial model, serving as a more intuitive and easier-to-use quality descriptor.

[0066] Specifically, the monitoring and flag generation of ionospheric scintillation includes: the data processing center analyzes the satellite signal strength and phase changes received by each reference station within the network (real-time monitoring of the signal carrier-to-noise ratio (C / N0) and phase of each reference station to all visible satellites), and calculates ionospheric scintillation indices, such as the S4 index (amplitude scintillation index) and the ROTI index (TEC rate of change index), to quantify the intensity of ionospheric activity. When the S4 index of a satellite is detected to generally exceed a preset threshold at multiple stations, the system determines that the satellite signal is severely interfered with and its quality has degraded. It then sets the corresponding ionospheric scintillation flag in the custom RTCM message and issues a warning to the user's positioning terminal. At this time, a message with message number 4051 and subtype H is generated, and the "Ionospheric Scintillation Level" field corresponding to the satellite is set to "1", indicating that scintillation has occurred.

[0067] Specifically, regional atmospheric correction information refers to ionospheric and tropospheric information used for network RTK, including baseline length, reference satellite indication, atmospheric corrections for the tilt paths of each satellite, and their accuracy. The specific message content is shown in Table 4.

[0068] Table 4 Ionospheric and tropospheric information for custom 4051 messages

[0069] Data fields DF number Data types Number of digits Notes MessageNumber DF002 12 "4051”==111111010011 MessageType uint8 8 1: Ionosphere and troposphere ReferenceStationID DF003 uint12 12 Reference-StationIndicator DF141 bit(1) 1 InterpolationPointECEF-X DF025 int38 38 InterpolationPointECEF-Y DF026 int38 38 InterpolationPointECEF-Z DF027 int38 38 GNSSEpochTime(TOW) DF004 uint30 30 Each GNSS system specific No. of Satellite (NSAT) DF387 uint8 8 Number of satellites BaselineLength DF530 uint13 13 0~819.2km MultipleMessageBit DF388 bit(1) 1 0: The last message in the sequence; 1: Multiple messages are being transmitted. GNSSSatelliteSystem uint3 3 Satellite system sequence: 0: GPS, 1: GLONASS, 2: GALILEO, 3: BDS, 4: QZSS GNSSSatellitePRN uint7 7 0-127 Reference-SatelliteIndicator bit(1) 1 1: Reference satellite; 0: Non-reference satellite GNSSSatelliteSlantTroposphericWetDelay int11 11 ±1023 mm. If the absolute value of the tilted tropospheric wet delay exceeds 1023 mm, then 1023 mm is used. GNSSSatelliteSlantTroposphericSigma uint10 10 The tropospheric sigma ranges from 1 to 1000 mm. If there is no sigma value, it is represented by 0. If the sigma value exceeds 1000 mm, it is set to 1023. GNSSSatelliteSlantIonosphericDelay int14 14 ±8191 mm. If the absolute value of the tilted ionospheric delay exceeds 8191 mm, then 8191 mm is used. GNSSSatelliteSlantIonosphericSigma uint10 10 The ionospheric sigma ranges from 1 to 1000 mm. If there is no sigma value, it is represented by 0. If the sigma exceeds 1000 mm, it is set to 1023. TOTAL 199+56×NSAT The maximum number of NSATs is 256.

[0070] Specifically, the regional atmospheric correction accuracy information includes at least one or more of the following combinations: regional atmospheric model configuration information, including region ID, reference grid point latitude and longitude, number of grid points and step size, etc.; regional tropospheric dry delay information, including dry delay constant terms and grid residuals; regional tropospheric wet delay information, including wet delay constant terms and grid residuals; and regional ionospheric delay information, including delay model coefficients and grid residuals for different satellites. The specific content of the regional atmospheric model configuration information is shown in Table 5.

[0071] Table 5. Regional Atmospheric Model Configuration Information for Custom Message 4051

[0072] Data fields DF number Data types Number of digits Notes MessageNumber DF002 12 "4051”==111111010011 MessageType uint8 8 2: Regional Configuration Information RegionID uint10 10 Each region has a unique number. No. ofGridPoints uint10 10 No. ofLatitudeGridPoint uint8 8 No. of LongitudeGridPoint uint8 8 RegionalReferenceLatitude DF516 int14 14 ±90.0° Regional Reference Longitude DF517 int15 15 ±180.0° RegionalLatitudeStepLength DF518 uint9 9 0.1°~3.2° Regional Longitude Step Length DF519 uint9 9 0.1°~3.2° TOTAL 103

[0073] Specifically, the details of the regional tropospheric dry delay information are shown in Table 6.

[0074] Table 6 Regional Tropospheric Delay Information for Custom Message 4051

[0075] Data fields DF number Data types Number of digits Notes MessageNumber DF002 uint12 12 "4051”==111111010011 MessageType uint8 8 3: Tropospheric delay information GNSSEpochTime(TOD) uint17 17 Within a day, 0-86399 PrecisionFactor uint4 4 0: Unknown 1: <= 0.010m 2: <= 0.020m 3: <= 0.040m 4: <= 0.080m 5: <= 0.160m 6: <= 0.320m 7: > 0.320m DryDelayConstant DF520 uint11 11 0~8.192m GridResidual DF521 int9 9 ±1.024 TOTAL 52+9×n n: Number of grid points

[0076] Specifically, the details of the regional tropospheric wet delay information are shown in Table 7.

[0077] Table 7 Regional Tropospheric Wet Delay Information for Custom 4051 Messages

[0078] Data fields DF number Data types Number of digits Notes MessageNumber DF002 uint12 12 "4051”==111111010011 MessageType uint8 8 4: Tropospheric wet delay information GNSSEpochTime(TOH) uint12 12 Hourly seconds, 0-3599 PrecisionFactor uint4 4 0: Unknown 1: <= 0.010m 2: <= 0.020m 3: <= 0.040m 4: <= 0.080m 5: <= 0.160m 6: <= 0.320m 7: > 0.320m WetComponentConstant DF522 uint8 8 0~1.024m GridResidual DF523 int7 7 ±0.248 TOTAL 44+7×n n: Number of grid points

[0079] Specifically, the details of the regional ionospheric delay information are shown in Table 8.

[0080] Table 8 Regional Ionospheric Delay Information for Custom 4051 Messages

[0081] Data fields DF number Data types Number of digits Notes MessageNumber DF002 uint12 12 "4051”==111111010011 MessageType uint8 8 5: Ionospheric delay information GNSSEpochTime(TOD) uint17 17 Within a day, 0-86399 MultipleMessageBit DF393 bit(1) 1 GNSSSatelliteSystem uint3 3 Satellite system sequence: 0: GPS, 1: GLONASS, 2: GALILEO, 3: BDS, 4: QZSS GNSSSatellitePRN uint7 7 0-127 UnitWeightMeanSquareError DF524 uint7 7 0~10.20TECU ModelCoefficientC00 DF525 int13 13 ±327.64TECU ModelCoefficientC11 DF526 int14 14 <![CDATA[±32.766 TECU / degree 2 > ModelCoefficientC01 / C10 DF527 int13 13 ±65.528 TECU / degree ModelCoefficientType uint3 3 0: Constant term 1: First-order model (3) 2: First-order model (4) 3: Second-order model (6) ModelCoefficientVariance DF528 int7 7 ±5.08, (1+m)×m / 2 GridResidual DF529 int8 8 ±10.20 TOTAL 98 + 7 × (1 + m) × m / 2 + 8 × n m: Number of model coefficients; n: Number of grid points

[0082] Specifically, ionospheric scintillation information refers to ionospheric scintillation markers used in network RTK, including the ionospheric TEC index, the number of visible satellites, and ionospheric scintillation level indications. Details are shown in Table 9.

[0083] Table 9 Ionospheric scintillation flag messages in custom 4051 messages

[0084] Data fields DF number Data types Number of digits Notes MessageNumber DF002 uint12 12 "4051”==111111010011 MessageType uint8 8 7: Satellite Ionospheric Scintillation Indicator ReferenceStationID DF003 uint12 12 GNSSEpochTime(TOW) DF004 uint30 30 Each GNSS system specific No. of Satellite (NSAT) DF387 uint8 8 Number of satellites IonosphericTECIndex uint4 4 MultipleMessageBit DF388 bit(1) 1 0 - Last message in the sequence; 1 - Multiple messages are being transmitted. GNSSSatelliteSystem uint3 3 Satellite system sequence: 0: GPS, 1: GLONASS, 2: GALILEO, 3: BDS, 4: QZSS GNSSSatellitePRN uint7 7 0-127 IonosphericScintillationLevel uint3 3 0: No ionospheric scintillation; 1: Ionospheric scintillation; 2-7: Retained TOTAL 75+NSAT×13 The maximum number of NSATs is 127.

[0085] Specifically, the core principle of user positioning using augmented information is to employ an atmospheric-weighted RTK solution model (second-order polynomial model) combined with an adaptive stochastic model. The standard double-difference carrier phase observation equation can be expressed as:

[0086] (2)

[0087] in, It is a double difference operator. It is the geometric distance between the star stations. It is ionospheric delay. (Not explicitly stated in the equations, but the principle is similar) is tropospheric delay. It's the blurriness throughout the week. It is the wavelength of the carrier phase. This is noise in the phase observations. In traditional RTK, the atmospheric error term... and It is assumed that this can be eliminated under short baseline conditions.

[0088] Specifically, the positioning solution stochastic model dynamically allocates the weights of GNSS observations, namely the data from the continuously operating reference station network (double-difference carrier phase and pseudorange observations) and atmospheric correction pseudo-observations (regional atmospheric correction information), and finally obtains a weighted matrix (weight matrix P) that matches the quality of the continuously operating reference station network data and the accuracy of regional atmospheric correction information, which is the positioning solution stochastic model.

[0089] Specifically, in network RTK, the user's positioning end uses the received correction information to reduce atmospheric errors, and introduces the atmospheric correction information broadcast by the data service center as pseudo-observations with random constraints into the least squares adjustment equations:

[0090] (3)

[0091] in, and It is the double-difference atmospheric correction value calculated by the user positioning terminal based on the custom RTCM message content. and This is the residual error of the aforementioned corrections. The key lies in the variance of the atmospheric error. and It is not set directly to 0, but is determined by the quality indicators (such as "accuracy factor" and "unit weight error") in the custom RTCM message.

[0092] Specifically, when a message contains an "ionospheric scintillation marker" for a particular satellite, the user positioning terminal dynamically adjusts the weights of all observations from that satellite (i.e., increasing the variance of the scintillation satellite observations and decreasing their weights). Its stochastic model (i.e., the weight matrix of the observation equation) (The P matrix in Formula 5) will significantly increase the variance of the satellite's related observations, for example:

[0093] (4)

[0094] in, Satellites affected by scintillation The variance of the observed values, It is the standard deviation of its satellite observations unaffected by flicker. It is a relatively large penalty factor. This adaptive stochastic model significantly reduces the impact of disturbed observation data on the adjustment solution, thereby protecting the solution results from contamination and improving the success rate of ambiguity resolution and the reliability and accuracy of the final positioning results.

[0095] Specifically, the broadcasting of the custom RTCM message includes: the data processing center packages the enhanced information generated in the above steps, such as model coefficients, grid residuals, precision factors, and flashing indicators, into a custom RTCM message with message number 4051 according to the formats defined in Tables 1 to 9, and broadcasts it to user positioning terminals within the service area via standard data link protocols such as NTRIP. Among these, the model coefficients and grid residuals correspond to regional atmospheric correction information. The core content of the regional atmospheric correction information includes ionospheric information and tropospheric information (dry delay and wet delay), which are specifically represented by the model coefficients and grid residuals.

[0096] Specifically, the model coefficients correspond to the coefficients of the second-order polynomial model. For example, the ionospheric delay model coefficients; the delay model coefficients of regional ionospheric delay information are the core parameters for calculating atmospheric delay corrections at any location within the region. The grid residuals, corresponding to the grid residuals of regional dry tropospheric delay, regional wet tropospheric delay, and regional ionospheric delay, are supplementary correction terms for the fitting accuracy of the atmospheric correction model, used to improve the refinement of local atmospheric corrections, and are also key components of regional atmospheric correction information.

[0097] Specifically, the scintillation flag corresponds to ionospheric scintillation information, which includes core content such as ionospheric scintillation level indication and a list of satellites affected by scintillation. When ionospheric scintillation interference with satellite signals is detected, an "ionospheric scintillation flag" (such as the "Ionospheric Scintillation Level" field in subtype H messages) is set in the custom RTCM message. This flag directly corresponds to the "scintillation level indication" in the "ionospheric scintillation information" and is a key piece of information conveying scintillation risk to the user's positioning terminal; the two are equivalent.

[0098] Specifically, the precision factor corresponds to the regional atmospheric correction precision information, which is a quantitative description of the reliability of atmospheric corrections, including precision classification, unit weight mean square error, model coefficient variance, etc. The precision factor is the core quantitative indicator of this information. The precision factor is generated by combining historical research data and the current model posterior variance (such as the "Precision Factor" field in the tropospheric dry delay message, with classification standards of "Level 1 ≤ 0.010m, Level 2 ≤ 0.020m", etc.), directly characterizing the precision level of regional atmospheric correction information. It is a core component of regional atmospheric correction precision information, and the two correspond to each other.

[0099] Specifically, the user positioning terminal's adaptive positioning calculation includes: the user positioning terminal is the ultimate beneficiary of the method of this invention, and its internal positioning calculation engine is designed to understand and utilize the enhanced information in the 4051 message. Specifically, as follows:

[0100] (1) Message decoding and correction calculation

[0101] The user positioning terminal receives and decodes 4051 messages. For example, upon receiving an ionospheric delay message for a two-dimensional polynomial model, it extracts the model coefficients. And based on its current approximate location The ionospheric delay correction value for each satellite is calculated using formula (1). Similarly, other correction information, such as tropospheric corrections, is calculated and interpolated accordingly.

[0102] (2) Constructing an adaptive stochastic model

[0103] The user positioning terminal constructs a stochastic model for positioning calculation (i.e., the weight matrix of the observations). In this case, a fixed or weighting method based solely on satellite elevation angle is no longer used. Instead, dynamic and adaptive adjustments are made based on the quality indicators in Message 4051. Simultaneously, the variance of atmospheric correction spurious observations is directly determined by their corresponding accuracy indicators.

[0104] (3) Positioning solution and ambiguity fixation

[0105] Based on the aforementioned adaptive stochastic model, the user positioning terminal establishes an atmospheric weighted least squares adjustment equation set. This observation equation set includes the original GNSS double-difference observation equations and atmospheric corrected pseudo-observation equations, and its matrix form can be expressed as follows:

[0106] (5)

[0107] in, It is the residual of the observed values. It is the atmospheric correction residual. These are observed values. It is an atmospheric correction value. It is the observation weight matrix. It is an atmospheric correction weight matrix; It is the vector of parameters to be estimated (including position corrections and floating-point ambiguity). It is a design matrix. It is a block diagonal weight matrix constructed based on an adaptive stochastic model. By solving this system of equations, a more accurate and reliable floating-point solution can be obtained.

[0108] Subsequently, the floating-point solution and its covariance matrix are input into the ambiguity resolution module. Since the stochastic model more realistically reflects the actual accuracy of the observations and corrections, the success rate and reliability of ambiguity fixation are significantly improved, and finally, high-precision fixed solution coordinates are output. Among them, the ambiguity resolution module is an integer ambiguity resolution algorithm module built into the user positioning terminal. Its core function is to solve the GNSS double-difference integer ambiguity (floating-point solution) into an integer solution, which is a key link in achieving high-precision positioning. The covariance matrix is ​​used to characterize the accuracy level of the parameters to be estimated (user position correction, ambiguity floating-point value) and the correlation between the parameters. The covariance matrix refers to the P matrix in formula (5).

[0109] Specifically, the embodiments of the present invention have been verified with actual data, wherein the CORS station distribution used is as follows: Figure 2 As shown, data from six base stations were selected and processed. Then, the standard RTCM message for extracting differential information and the custom RTCM message for GNSS enhancement information mentioned in this patent were simultaneously broadcast to the user positioning terminal. After 24 hours of continuous testing, the results processed by the user positioning terminal are as follows: Figure 3 As shown. From Figure 3 It can be seen that after the assistance of GNSS augmentation information, the user positioning end has a better solution effect, and the fixation rate can exceed 95% for 24 hours, which proves the effectiveness of this solution.

[0110] Based on the above embodiments, the present invention provides a GNSS enhanced positioning system based on a custom RTCM message, which is used to execute a GNSS enhanced positioning method based on a custom RTCM message in the above method embodiments.

[0111] The system includes: a set of CORS stations (3 or more) and a data processing center: generating a custom RTCM message with message number 4051 and broadcasting the custom RTCM message with message number 4051 to the user positioning terminal; at least one user positioning terminal: receiving and parsing the custom RTCM message and using the enhanced information therein to optimize the positioning calculation.

[0112] Finally, it should be noted that the above specific embodiments are merely representative examples of the present invention. Obviously, the present invention is not limited to the above specific embodiments and many variations are possible. Any simple modifications, equivalent changes, and alterations made to the above specific embodiments based on the technical essence of the present invention should be considered within the protection scope of the present invention.

Claims

1. A GNSS-enhanced positioning method based on a custom RTCM message, characterized in that, include: Based on real-time acquired data from the continuously operating reference station network and the location information from the user's positioning terminal, regional atmospheric error modeling is performed to obtain regional atmospheric correction information. By introducing an accuracy factor, the accuracy of regional atmospheric correction information is classified and quantified to obtain regional atmospheric correction accuracy information. Ionospheric scintillation information is calculated based on the satellite signal strength and phase changes received by each reference station in the continuously operating reference station network. Regional atmospheric correction information, ionospheric scintillation information, and regional atmospheric correction accuracy information are supplemented and encoded into the standard RTCM message to obtain a custom RTCM message. The custom RTCM message includes a variety of preset sub-type messages. The sub-type messages include enhancement information for improving the positioning terminal's calculation performance. The enhancement information includes regional atmospheric correction information, regional atmospheric correction accuracy information, and ionospheric scintillation information. The message number of the custom RTCM message is 4051. The user's real-time location information is obtained by performing location calculations based on the custom RTCM message and the standard RTCM message.

2. The GNSS enhanced positioning method based on a custom RTCM message according to claim 1, characterized in that, The following second-order polynomial model is used for regional atmospheric error modeling: ， in, At the user location or base station location Ionospheric delay at that location It's latitude. It's longitude. These are the coordinates of the region's center. These are model coefficients. It is model error.

3. The GNSS enhanced positioning method based on a custom RTCM message according to claim 2, characterized in that, Based on the custom RTCM message and the standard RTCM message, the user's real-time location information is obtained through location calculation, including: Standard positioning is performed using standard RTCM messages to obtain standard positioning results; Based on the model coefficients of the second-order polynomial model, the ionospheric delay correction value for each satellite is calculated to obtain the decoded custom RTCM message. The weights of continuously operating reference station network data and regional atmospheric correction information are dynamically allocated to obtain a positioning solution stochastic model that matches the continuously operating reference station network data and regional atmospheric correction accuracy information. Based on the decoded custom RTCM message and the location solution stochastic model, an atmospheric weighted least squares adjustment equation set is established to enhance the accuracy of the standard positioning results and obtain the user's real-time location information.

4. The GNSS enhanced positioning method based on a custom RTCM message according to claim 1, characterized in that, Introducing a precision factor, including: Accuracy factors are generated based on historical research data and the posterior variance after regional atmospheric error modeling. These accuracy factors are then used to characterize the accuracy level of regional atmospheric correction information, resulting in graded and quantified regional atmospheric correction accuracy information.

5. A GNSS enhanced positioning method based on a custom RTCM message according to claim 3, characterized in that, The established atmospheric weighted least squares adjustment equations are as follows: ， in, It is the observation residual. It is the atmospheric correction residual. These are observed values. It is an atmospheric correction value. It is the vector of parameters to be estimated. It is a design matrix. It is the observation weight matrix. It is an atmospheric correction weight matrix. It is a block-diagonal weight matrix.

6. The GNSS enhanced positioning method based on a custom RTCM message according to claim 1, characterized in that, The regional atmospheric correction accuracy information includes at least one or more of the following combinations: regional atmospheric model configuration information, regional dry tropospheric delay information, regional wet tropospheric delay information, and regional ionospheric delay information.

7. A GNSS enhanced positioning method based on a custom RTCM message according to claim 6, characterized in that, The regional atmospheric model configuration information includes the region ID, reference grid point latitude and longitude, number of grid points and step size; the regional tropospheric dry delay information includes a dry delay constant term and grid residuals; the regional tropospheric wet delay information includes a wet delay constant term and grid residuals; and the regional ionospheric delay information includes delay model coefficients and grid residuals for different satellites.

8. A GNSS enhanced positioning method based on a custom RTCM message according to claim 1, characterized in that, The ionospheric scintillation information includes the ionospheric TEC index, the number of visible satellites, and the ionospheric scintillation level indication.

9. A GNSS-enhanced positioning system based on a custom RTCM message, characterized in that, include: The data processing center is used to perform regional atmospheric error modeling based on real-time acquired data from the continuously operating reference station network and the location information from user positioning terminals, and to obtain regional atmospheric correction information. By introducing an accuracy factor, the accuracy of regional atmospheric correction information is classified and quantified to obtain regional atmospheric correction accuracy information. Based on the satellite signal strength and phase changes received by each reference station within the continuously operating reference station network, ionospheric scintillation information is calculated. Regional atmospheric correction information, ionospheric scintillation information, and regional atmospheric correction accuracy information are then supplemented and encoded into a standard RTCM message to obtain a custom RTCM message. This custom RTCM message includes several preset sub-type messages. These sub-type messages include enhancement information for improving the positioning terminal's processing performance, including regional atmospheric correction information, regional atmospheric correction accuracy information, and ionospheric scintillation information. The message number of the custom RTCM message is 4051. The user positioning terminal is used to perform positioning calculations based on the custom RTCM message and the standard RTCM message to obtain the user's real-time location information.

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