GNSS (Global Navigation Satellite System) network RTK (Real Time Kinematic) differential data broadcasting method and system based on user position sharing

Abstract

The invention provides a GNSS (Global Navigation Satellite System) network RTK (Real Time Kinematic) differential data broadcasting method and system based on user position sharing, aiming at improving the resource utilization efficiency and the positioning service precision of a network RTK system. According to the method, after a user sends out a differential data request, an existing broadcast product is searched within a certain range, if differential data meeting conditions do not exist, a new broadcast source is dynamically generated according to the initial position of the user, and the error is calculated through a regional ionosphere and troposphere error model and the correlation between the error and the distance and the elevation. Determining a coverage range of the broadcast source; and if the differential data meeting the condition exists, directly sharing the broadcast source. According to the method, resource waste caused by the fact that no user grid point exists in traditional grid broadcasting is avoided, and meanwhile the problem that troposphere correction numbers are inconsistent due to user elevation difference in a single-layer grid mode is solved by dynamically adjusting generation and sharing of broadcasting sources.

Description

Technical Field

[0001] The present invention belongs to the field of satellite navigation and positioning technology, and specifically relates to a global navigation satellite system (GNSS) network real-time kinematic (RTK) positioning technology, and more particularly to a GNSS network RTK differential data broadcasting method based on dynamic generation and sharing of user positions. Background Art

[0002] GNSS network RTK technology generates differential correction data from joint observations across a network of base stations and transmits it to users in real time. This correction is used to correct for ionospheric and tropospheric delay errors, as well as satellite orbit and clock errors, achieving centimeter-level high-precision positioning. It is widely used in fields such as geographic information collection, unmanned driving, engineering surveying, and precision agriculture. However, traditional RTK differential data dissemination methods have significant limitations. The one-to-one user dissemination method requires individual differential data calculation for each user, resulting in a linear increase in system computational and communication load with the number of users, making it difficult to support large-scale users. The ground-based grid-based dissemination method generates virtual reference stations (VRS) using a fixed grid. While this reduces the need for individual computation, differential data still needs to be generated for grid points without users, resulting in wasted resources. Furthermore, a single-layer grid is not suitable for areas with significant elevation differences, which can lead to inconsistent tropospheric corrections. The layered grid dissemination method improves service performance in areas with varying elevations by using multiple layers of grids, but this increases computational and management complexity, and some low-elevation grids may still have no user coverage, wasting resources. In addition, although the regional broadcasting method based on inter-station interpolation reduces the amount of data, the interpolation accuracy decreases when the base stations are sparse or the user elevation changes significantly. It also lacks dynamic adjustment and data sharing mechanisms and cannot efficiently cope with complex environments and multi-user needs.

[0003] Existing methods as a whole lack the ability to adapt to the dynamic distribution of users and elevation differences, making it difficult to strike a balance between resource utilization efficiency and service performance. Summary of the Invention

[0004] This paper addresses the resource waste, poor adaptability to elevation differences, and inefficient service delivery issues inherent in existing GNSS network RTK differential data dissemination methods. By proposing a GNSS network RTK differential data dissemination method based on the dynamic generation and sharing of user locations, this method dynamically generates differential data dissemination sources by combining user locations with a regional error model and enables the sharing of existing differential data, effectively improving system resource utilization and positioning service performance.

[0005] The present invention proposes a GNSS network RTK differential data broadcasting method based on the dynamic generation and sharing of user positions. The method dynamically generates a broadcast source through user position requests, combines the regional ionospheric and tropospheric error models to calculate the correlation between the error, distance and elevation, and determines the coverage range of the broadcast source. At the same time, if qualified differential data already exists within the target range, the existing broadcast source is directly shared, thereby avoiding the waste of resources of grid points without users, solving the problem of inconsistent tropospheric correction numbers caused by elevation differences, and significantly improving the performance of network RTK differential broadcast services in complex multi-user environments. The method is suitable for scenarios with a large number of users on the ground and in low-altitude areas.

[0006] In order to solve the above problems, the technical solution proposed by the present invention includes the following steps: Step 1: Receive user differential data request and resolve user location; Step 2: Check the existing differential data source list to see if there is a new user data source that meets the requirements. If so, directly send the data of the data source to the user. If not, proceed to step 3. Determine whether the old user data source is within the valid range. If so, directly connect the user to the old user data source. If not, treat the old user data source as a new user data source. Step 3: Calculate the total error correction at the rover based on the user's position and broadcast it to the user via the communication network. The user makes corrections upon receiving the corrections, and thus obtains a high-precision positioning result. Calculate the coverage of the differential data source based on the total error correction. Then, add the coordinates of the base station, the coverage of the differential data source, and the latest user service time to the existing differential data source list, and send the data to the current requesting user. Step 4: Update the differential data source list and resource management. For the broadcast sources not covered by the user request, recycle the resources according to the temporal and spatial distribution rules.

[0007] Furthermore, parsing the user's location includes: Parse the differential data request sent by the user and obtain its position in the three-dimensional geocentric rectangular coordinate system , converted to geodetic coordinates :

[0008] in is the radius of the reference ellipsoid, and then the Gauss-Krüger projection formula is used to calculate the user plane coordinates and elevation .

[0009] Furthermore, the existing differential data source list is searched to see if there is a new user data source that meets the requirements, including: Obtain the base station position for each new user data source one by one The distance between the coverage area and the plane and elevation difference , calculate the plane distance between the user and the reference station and the elevation difference between the user and the base station :

[0010]

[0011] Determine whether the new user data source meets the following conditions:

[0012] If the above conditions are met, the data of the new user data source is directly sent to the user, and the processing ends. If multiple new user data sources that meet the conditions are found, the best one is selected and sent to the user. If no data source that meets the requirements is found, go to step 3.

[0013] Furthermore, in step 3, the error is first calculated using the area-weighted linear interpolation method, which is based on the interpolation of the three nearest reference stations. The entire reference station network coverage area is divided into several triangular sub-areas, each of which corresponds to a reference station. , directly use the triangle area formula to calculate its area , then the area weight can be obtained:

[0014] in , are the areas of the sub-regions and the total area corresponding to the three reference stations respectively, , , are the weights of the three sub-regions, then the error interpolation formula of the mobile station is:

[0015]

[0016]

[0017] in, , , are the ionospheric correction, tropospheric correction and satellite orbit correction of the mobile station user position, , , are the ionospheric corrections for the three sub-regions, , , are the tropospheric corrections for the three sub-regions, , , are the satellite orbit correction numbers for the three sub-regions; The total error correction at the mobile station is : .

[0018] Furthermore, the coverage of the differential data source is calculated as follows: First, calculate the average of the error corrections for all satellites in the same set of corrections:

[0019]

[0020] Where n represents the number of satellites; Once the maximum allowable ionospheric error and tropospheric error are determined, the effective plane range is calculated. and elevation range for:

[0021]

[0022] is the maximum allowable ionospheric error, is the maximum allowable tropospheric error.

[0023] Furthermore, the error of the error correction number is related to the plane distance and elevation difference The relationship is:

[0024]

[0025] in, is the plane distance from the differential data source, that is, the difference between the plane distances of the mobile station user position and the corresponding coordinates of the differential data source, is the elevation difference from the differential data source, i.e., the elevation difference between the rover user position and the corresponding coordinates of the differential data source; is the plane distance from the differential data source The error value of the ionospheric error correction number using the differential data source is Height difference from differential data source The error value of the tropospheric error correction number using this differential data source.

[0026] Furthermore, in step 4, for each data source in the differential data source list, it is determined whether it is covered by the user request within a certain period of time. The time difference of the final request service is:

[0027] in, Indicates the current time of the computer. The latest user service time; if the maximum time difference is set to ,when The data source is recycled.

[0028] Furthermore, the resources mentioned in step 4 refer to the resources consumed for interpolation calculation, encoding, and storage of the differential correction numbers in step 3, including memory usage and CPU usage for generating the differential correction numbers.

[0029] The present invention also provides a GNSS network RTK differential data broadcasting system based on user location sharing, comprising a memory and a processor, wherein the memory stores a differential data broadcasting program that can be run on the processor, and the differential data broadcasting program is a computer program. When the processor executes the differential data broadcasting program, the GNSS network RTK differential data broadcasting method based on user location sharing as described in the above scheme is implemented.

[0030] The present invention also provides a storage medium, which is a computer-readable storage medium and stores a differential data broadcasting program. The differential data broadcasting program is a computer program. When the differential data broadcasting program is executed by a processor, it implements the GNSS network RTK differential data broadcasting method based on user position sharing as described in the above technical solution.

[0031] Compared with the prior art, the present invention has the following significant advantages: 1) Efficient Resource Utilization: Dynamically generating and sharing broadcast sources avoids wasted resources at grid points without user coverage, improving computational and storage efficiency. Dynamically generated broadcast sources are updated in real time, including parameters such as ionospheric and tropospheric corrections, satellite orbit errors, and clock errors. For broadcast sources not covered by user requests, the system reclaims resources based on temporal and spatial distribution patterns, improving overall resource utilization.

[0032] 2) Accurate Elevation Adaptation: The broadcast range is calculated based on user location and elevation information, addressing the difficulty of a single-layer grid in handling elevation differences and ensuring positioning accuracy. The coverage of the broadcast source is determined by combining regional ionospheric and tropospheric error models and calculating the correlation between error, distance, and elevation to ensure that all users within the coverage area meet positioning accuracy requirements.

[0033] 3) Dynamic and Flexibility: Differential data is generated based on real-time user distribution and needs, enabling dynamic adaptation and precise service. When multiple users make requests in the same area, the system can share broadcast data, eliminating the need to generate differential data for each user, significantly reducing computational and communication loads. As users move around, the system can adjust the broadcast source coverage in real time and dynamically optimize the generation and sharing strategies for differential data.

[0034] 4) Support for large numbers of users: It can support large-scale users in ground and low-altitude areas, significantly improving the GNSS network RTK service capabilities in multi-user environments.

[0035] 5) Improved service efficiency: By sharing broadcast sources and optimizing differential data broadcast strategies, computing and bandwidth overheads are reduced to meet the real-time service needs of massive users. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 This is a flow chart of an embodiment of the present invention.

[0037] Figure 2 This is a technical flowchart of user-shared differential data source generation in an embodiment of the present invention.

[0038] Figure 3 Schematic diagram of software platform and site distribution in an embodiment of the present invention.

[0039] Figure 4 This is a simulated user distribution diagram in an embodiment of the present invention.

[0040] Figure 5 This is a schematic diagram of the concurrent CPU usage of 10,005 simulated terminals in an embodiment of the present invention.

[0041] Figure 6 This is a schematic diagram of the concurrent memory usage of 10,005 simulated terminals in an embodiment of the present invention. DETAILED DESCRIPTION

[0042] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0043] Existing technologies mainly use fixed grid, single-layer grid or layered grid broadcasting methods, which have the following problems: 1) Waste of resources: In grid-based broadcasting, grid points without user coverage still need to generate and maintain differential data, resulting in a waste of computing and storage resources.

[0044] 2) Poor altitude adaptability: In areas with significant elevation differences, a single-layer grid cannot effectively resolve differences in user tropospheric corrections, affecting positioning accuracy.

[0045] 3) Insufficient dynamism: As user distribution changes dynamically, grid division and broadcast strategies are difficult to adapt in real time, resulting in reduced service efficiency.

[0046] 4) Insufficient support for large-scale users: The one-to-one broadcasting method cannot meet the real-time service needs of massive users, while the grid-based broadcasting method has bandwidth and computing load bottlenecks.

[0047] Based on the above problems, the present invention proposes a GNSS network RTK differential data broadcasting method and system based on dynamic generation and sharing of user positions, aiming to improve the resource utilization efficiency and positioning service accuracy of the network RTK system. Receive user differential data request and resolve the user's position (step 1); search the existing differential data source list to see if there is a source that meets the requirements. If it exists, it is sent directly; if not, a new source is generated. During the user's movement, the user will search the existing data source for a differential data source based on the position (step 2). If no data source that meets the requirements is found, step (3) is entered; according to the user's position, differential data is obtained, and the correlation between distance and elevation and error correction accuracy is calculated based on the ionosphere and troposphere error model, and the difference between ionosphere error and troposphere error is limited to within 1cm (an indicator that needs to be determined for network RTK positioning accuracy), and the coverage range of the differential data source is given and added to the existing differential data source list (step 3); update the differential data source list and resource management. For broadcast sources that are not covered by the user request, the system can recycle resources according to the time and space distribution rules to improve the overall resource utilization (step 4). See Figure 1 The present invention specifically comprises the following steps: Step 1: Parsing user coordinate data and performing projection transformation Parse the differential data request sent by the user and obtain its position in the three-dimensional geocentric rectangular coordinate system , converted to geodetic coordinates :

[0048] in is the radius of the reference ellipsoid. Then the Gauss-Krüger projection formula is used to calculate the user plane coordinates and elevation .

[0049] Step 2: Find an existing data source Step 2.1 Obtaining new user data sources In the existing differential data source list, obtain the base station position of each data source one by one The distance between the plane and its coverage area and elevation difference Calculate the plane distance between the user and the base station and the elevation difference between the user and the base station :

[0050]

[0051] Determine whether the data source meets the following conditions:

[0052] If a single data source that meets the requirements is found, the data from that source is directly sent to the user, and the process ends. If multiple sources are found, the optimal source is selected, and the source with the shortest planar distance is the optimal source. If no data source that meets the requirements is found, proceed to step 3.

[0053] Step 2.2 Obtaining old user data sources Similar to step 2.1, compare the data source currently selected by the user to see if it is within the valid range, that is, the plane distance is less than , the height difference is less than If the user is within the range, the service is provided directly (i.e., the user is directly connected to the old user data source). If the user is not ...), Step 3: Generate a new differential data source Step 3.1 Generate error correction number Based on user location Calculating ionospheric corrections , tropospheric correction number and satellite orbit corrections , the generation of error correction numbers depends on the reference station observation data and its error model.

[0054]

[0055] The present invention uses the area-weighted linear interpolation method (LIM) to calculate the error, which is based on the three nearest reference stations. Divide the entire base station network coverage area into several triangular sub-areas, each sub-area corresponds to a base station, and , directly use the triangle area formula to calculate its area The area weight is calculated as follows:

[0056] in , are the areas of the sub-regions and the total area corresponding to the three reference stations respectively, , , are the weights of the three sub-regions, then the error interpolation formula of the mobile station is:

[0057]

[0058]

[0059] in, , , are the ionospheric correction, tropospheric correction and satellite orbit correction of the mobile station user position, , , are the ionospheric corrections for the three sub-regions, , , are the tropospheric corrections for the three sub-regions, , , are the satellite orbit correction numbers for the three sub-regions; The total error correction at the mobile station is :

[0060] Calculated error correction number , broadcast to users through the communication network, users make corrections after receiving it, and then obtain high-precision positioning results.

[0061] Step 3.2 Calculate the coverage of the differential data source The ionospheric linear interpolation model is based on the assumption that ionospheric gradients are essentially consistent within a certain range. The gradient consistency is essentially linearly related to the absolute value of the ionospheric error correction. In this invention, the effective range of the ionospheric correction is determined based on the absolute value of the ionospheric correction. First, the average correction value for all satellites (n) in the same correction set is calculated:

[0062]

[0063] The relationship between the error of the error correction number and the distance is:

[0064]

[0065] in is the plane distance from the differential data source The error value of the ionospheric error correction number using the differential data source. Height difference from differential data source The error value of the tropospheric error correction number using the differential data source; is the plane distance from the differential data source (in kilometers. Each differential data source is a collection of error corrections calculated for a specific location. Usually, because errors have spatial correlation, but this spatial correlation decreases with increasing distance, if the same error correction is used for other locations with this specific location as the center, an inconsistent error will be introduced. The larger the radius, that is, the longer the distance, the greater the error. When this error affects positioning accuracy and performance, it cannot be used). is the elevation difference from the differential data source (i.e., the difference between the elevation of the mobile station user position and the elevation of the corresponding coordinates of the differential data source, in meters).

[0066] Once the maximum allowable ionospheric error and tropospheric error are determined, the effective plane range can be calculated. and elevation range :

[0067]

[0068] is the maximum allowable ionospheric error, is the maximum allowable tropospheric error. According to the accuracy requirements of network RTK positioning, the interpolation error between the ionosphere and troposphere usually needs to be controlled within 1cm. Therefore, the effective plane range of the data source can be calculated based on the above formula and elevation range .

[0069] Step 3.3 Create a differential data source list According to the requirements for differential data in the previous steps, the data source needs to include the coordinates of the base station and the effective plane range. and elevation range , the latest user service time . Therefore, the data source definition is as follows:

[0070] Then add the new data source to the differential data source list and send the data to the current requesting user.

[0071] Step 4: Update the differential data source list and resource management For each data source in the differential data source list, determine whether it is covered by the user request within a certain period of time. The time difference of the last request service is:

[0072] in, Indicates the current time of the computer; if the maximum time difference is set to , this value can be set according to actual needs, and can be set to 300 seconds. The data source is then recycled and resources are released. The resources here refer to the resources consumed by the interpolation calculation, encoding, and storage of the differential correction numbers in step 3.1, including the memory occupied and the CPU occupied by generating the differential correction numbers.

[0073] The effectiveness of the present invention's method was verified by simulating users to broadcast services using a GNSS network RTK system deployed in a certain city. A comparative analysis was conducted on the resource usage and effectiveness of the broadcast service system with the same number of users: 1) Software platform and site distribution see Figure 3 ; 2) The server status is as follows: Table 1 Server Description

[0074] 3) User-side simulation software see Figure 4 : The simulation generates 10,005 user locations, which are then used as rover users to connect to the server and check the CPU and memory usage.

[0075] The test server has 10005 concurrent users and checks the CPU usage (e.g. Figure 5 ) and memory usage (as shown in Figure 6 shown).

[0076] 4) The comparison of methods is shown in the following table: Table 2 Comparison of various methods

[0077] As can be seen from the table, when the number of users is 1,000, the conventional VRS broadcast method requires the server to generate 10,000 differential data sources, resulting in the highest CPU and interpolation usage. The conventional grid broadcast method only requires the generation of 2,000 grids, significantly reducing CPU and memory usage. This method, which shares differential data sources based on user locations, only requires the generation of 200 differential data sources, only 1 / 10 the equivalent of an equidistant grid. Memory and CPU usage are also minimal, almost 1 / 10 that of the VRS broadcast method, significantly conserving server resources.

[0078] In summary, the present invention significantly reduces the resource overhead of differential data generation and broadcasting, improves the positioning service performance in complex terrain and multi-user environments, and is suitable for network RTK differential broadcasting services with a large number of users in ground and low-altitude areas.

[0079] During specific implementation, the above process can be automatically executed using computer software technology, and the system device that runs the method process of the present invention should also be within the scope of protection of the present invention.

[0080] In a second aspect, an embodiment of the present invention further provides a GNSS network RTK differential data broadcasting system based on user location sharing, comprising a memory and a processor, wherein the memory stores a differential data broadcasting program that can be run on the processor, and the differential data broadcasting program is a computer program. When the processor executes the differential data broadcasting program, it implements the GNSS network RTK differential data broadcasting method based on user location sharing as described in the above scheme.

[0081] In a third aspect, an embodiment of the present invention further provides a storage medium, which is a computer-readable storage medium on which a differential data broadcasting program is stored. The differential data broadcasting program is a computer program. When the differential data broadcasting program is executed by a processor, it implements the GNSS network RTK differential data broadcasting method based on user position sharing as described in the above technical solution.

[0082] The specific embodiments described herein are merely illustrative of the spirit of the present invention. Persons skilled in the art may make various modifications, additions, or substitutions to the described specific embodiments without departing from the spirit of the present invention or exceeding the scope of the appended claims.

Claims

1. A method for broadcasting GNSS network RTK differential data based on user location sharing, characterized in that: The steps include: Step 1: Receive user differential data request and resolve user location; Step 2: Check the existing differential data source list to see if there is a new user data source that meets the requirements. If so, directly send the data of the data source to the user. If not, proceed to step 3. Determine whether the old user data source is within the valid range. If so, directly connect the user to the old user data source. If not, treat the old user data source as a new user data source. Step 3: Calculate the total error correction at the rover based on the user's position and broadcast it to the user via the communication network. The user makes corrections upon receiving the corrections, and thus obtains a high-precision positioning result. Calculate the coverage of the differential data source based on the total error correction. Then, add the coordinates of the base station, the coverage of the differential data source, and the latest user service time to the existing differential data source list, and send the data to the current requesting user. Step 4: Update the differential data source list and resource management. For the broadcast sources not covered by the user request, recycle the resources according to the temporal and spatial distribution rules.

2. The method for broadcasting GNSS network RTK differential data based on user location sharing according to claim 1, characterized in that: Resolving the user's location includes: Parse the differential data request sent by the user and obtain its position in the three-dimensional geocentric rectangular coordinate system , converted to geodetic coordinates : in is the radius of the reference ellipsoid, and then the Gauss-Krüger projection formula is used to calculate the user plane coordinates and elevation .

3. The method for broadcasting GNSS network RTK differential data based on user location sharing according to claim 1, characterized in that: Search the existing differential data sources list to see if there are any new user data sources that meet the requirements, including: Obtain the base station position for each new user data source one by one The distance between the plane and its coverage area and elevation difference , calculate the plane distance between the user and the reference station and the elevation difference between the user and the base station : Determine whether the new user data source meets the following conditions: If the above conditions are met, the data of the new user data source is directly sent to the user, and the processing ends. If multiple new user data sources that meet the conditions are found, the best one is selected and sent to the user. If no data source that meets the requirements is found, go to step 3.

4. The method for broadcasting GNSS network RTK differential data based on user location sharing according to claim 1, wherein: In step 3, the error is first calculated using the area-weighted linear interpolation method. This interpolation method is based on the three nearest reference stations and divides the entire reference station network coverage area into several triangular sub-areas. Each sub-area corresponds to a reference station. , directly use the triangle area formula to calculate its area , then the area weight can be obtained: in , are the areas of the sub-regions and the total area corresponding to the three reference stations respectively, , , are the weights of the three sub-regions, then the error interpolation formula of the mobile station is: in, , , are the ionospheric correction, tropospheric correction and satellite orbit correction of the mobile station user position, , , are the ionospheric corrections for the three sub-regions, , , are the tropospheric corrections for the three sub-regions, , , are the satellite orbit correction numbers for the three sub-regions; The total error correction at the mobile station is : 。 5. The method for broadcasting GNSS network RTK differential data based on user location sharing according to claim 4, characterized in that: The coverage of the differential data source is calculated as follows: First, calculate the average of the error corrections for all satellites in the same set of corrections: Where n represents the number of satellites; Once the maximum allowable ionospheric error and tropospheric error are determined, the effective plane range is calculated. and elevation range for: is the maximum allowable ionospheric error, is the maximum allowable tropospheric error.

6. The method for broadcasting GNSS network RTK differential data based on user location sharing according to claim 5, characterized in that: Error correction number and plane distance and elevation difference The relationship is: in, is the plane distance from the differential data source, that is, the difference between the plane distances of the mobile station user position and the corresponding coordinates of the differential data source, is the elevation difference from the differential data source, i.e., the elevation difference between the rover user position and the corresponding coordinates of the differential data source; is the plane distance from the differential data source The error value of the ionospheric error correction number using the differential data source is Height difference from differential data source The error value of the tropospheric error correction number using this differential data source.

7. The method for broadcasting GNSS network RTK differential data based on user location sharing according to claim 1, characterized in that: In step 4, for each data source in the differential data source list, determine whether it is covered by the user request within a certain period of time. The time difference of the final request service is: in, Indicates the current time of the computer. The latest user service time; if the maximum time difference is set to ,when The data source is recycled.

8. The method for broadcasting GNSS network RTK differential data based on user location sharing according to claim 1, characterized in that: The resources mentioned in step 4 refer to the resources consumed for interpolation calculation, encoding, and storage of the differential correction numbers in step 3, including memory usage and CPU usage for generating the differential correction numbers.

9. A GNSS network RTK differential data broadcasting system based on user location sharing, comprising a memory and a processor, wherein the memory stores a differential data broadcasting program executable on the processor, the differential data broadcasting program being a computer program, characterized in that: When the processor executes the differential data broadcasting program, the GNSS network RTK differential data broadcasting method based on user position sharing according to any one of claims 1 to 8 is implemented.

10. A storage medium, wherein the storage medium is a computer-readable storage medium and stores a differential data broadcasting program, wherein the differential data broadcasting program is a computer program, characterized in that: When the differential data broadcasting program is executed by a processor, the GNSS network RTK differential data broadcasting method based on user position sharing according to any one of claims 1 to 8 is implemented.

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