RTK Service Grid Layer Matching Method and Device Based on User Behavior Characteristics

Abstract

The present invention provides a method and apparatus for matching RTK service grid layers based on user behavior characteristics, which solves the technical problem of the conflict between the positioning service requirements of a large number of existing users and the grid service quality. The method includes: obtaining data access authorizations for different RTK service grids to establish a VRS service data synchronization process, forming RTK service layers corresponding to the grids, and establishing a mapping relationship between the layers and the speed; receiving positioning information periodically fed back by a positioning terminal to form corresponding sequential positioning data; regularly forming the average speed of the positioning terminal according to the sequential positioning data; determining the layer and grid nodes according to the average speed, and broadcasting corresponding VRS service data to the positioning terminal. The VRS service data is hierarchically managed by the grid layer according to service quality and corresponding levels, and the speed characteristics feedback that maps user behavior or application scenarios is used to measure the scale of the user's service quality requirements, so as to form corresponding-level VRS service data for timely broadcasting.

Description

Technical Field

[0001] The present invention relates to the technical field of GNSS navigation and positioning, and particularly relates to a method and device for matching RTK service grid layers based on user behavior characteristics. Background Art

[0002] Currently, the network RTK service (RTK, Real-Time Kinematic, real-time dynamic carrier phase relative positioning technology) widely used in various high-precision real-time positioning mainly adopts the virtual reference station technology (virtual reference station, VRS). The principle of this technology is that the data center receives the observation data of each reference station in the reference station network and the approximate coordinates of the user (or rover) in real time; and based on the coordinate position of the user, a virtual reference station is generated near it, and the spatial distance-related errors such as tropospheric and ionospheric delays at the virtual reference station are modeled to generate VRS virtual observations, and then the differential correction numbers in the standard format at the virtual reference station are sent to the user, so as to achieve the real-time high-precision positioning of the user. As described above, this mode depends on establishing two-way communication with the user. After that, the service software calculates according to the user's approximate position in the system to obtain the corresponding virtual reference station information and then broadcasts it to the user, which requires a large amount of calculation and service performance, and the concurrency ability is very low.

[0003] Therefore, another service method has emerged, that is, the fixed grid VRS technology, which serves users through grid-based VRS data (that is, a grid composed of a virtual reference station matrix is formed at a certain longitude and latitude interval, and virtual reference station data is fixedly generated at the grid nodes through the VRS technology. The RTK positioning terminal user uses the virtual reference station data of the grid node that is closest to the grid node in the grid). For RTK positioning users, the closer the position of the positioning terminal is to the coordinate position of the grid node providing the VRS service data, the higher the positioning service accuracy. This means that the higher the grid density, the higher the positioning service accuracy, while the positioning service range of each grid node is smaller, and at the same time, the denser the grid, the higher the performance requirements for computing resources.

[0004] In practical applications, there are significant differences in the positioning service accuracy requirements of different types of users. For example, surveying and mapping users generally require high positioning accuracy, but do not move quickly and do not pay much attention to the continuity of the positioning service. On the other hand, vehicle positioning and navigation users generally require relatively low positioning accuracy, but are in a fast-moving state and pay more attention to the continuity of the positioning service. To meet the needs of some users, only using high-density grids for positioning service response will result in high operating costs and decreased operation and maintenance stability. Summary of the Invention

[0005] In view of the above problems, an embodiment of the present invention provides a method and apparatus for RTK service grid layer matching based on user behavior characteristics, which solves the technical problem of the conflict between the positioning service requirements of a large number of existing users and the grid service quality.

[0006] The method for RTK service grid layer matching based on user behavior characteristics according to an embodiment of the present invention includes:

[0007] Obtain data access authorizations for different RTK service grids, establish a VRS service data synchronization process, form an RTK service layer for the corresponding grid, and establish a mapping relationship between the layer and the speed;

[0008] Receive the positioning information periodically fed back by the positioning terminal to form corresponding sequential positioning data;

[0009] Regularly form the average speed of the positioning terminal according to the sequential positioning data;

[0010] Determine the layer and grid nodes according to the average speed, and broadcast the corresponding VRS service data to the positioning terminal.

[0011] In an embodiment of the present invention, the forming of the RTK service layer for the corresponding grid and establishing the mapping relationship between the layer and the speed includes:

[0012] Establish an RTK service layer according to the VRS service data source;

[0013] Map the service quality according to the grid node density in the layer;

[0014] Form a service level through the mapping of the speed range and the layer.

[0015] In an embodiment of the present invention, the formation of the sequential positioning data includes:

[0016] When the user goes online, provide the VRS service data adapted in the default layer to the user's positioning terminal according to the default service level;

[0017] Receive the positioning information regularly fed back by the positioning terminal to obtain reliable positioning data;

[0018] Establish a sequential data queue for the positioning data.

[0019] In an embodiment of the present invention, the formation of the average speed includes:

[0020] Calculate the average speed within a specified duration according to the sequential positioning data.

[0021] In an embodiment of the present invention, the determining of the layer and grid nodes according to the average speed and broadcasting the VRS service data to the positioning terminal includes:

[0022] Determine the VRS service data of the grid nodes adapted in the service level corresponding layer according to the speed interval where the average speed is located, and broadcast it to the positioning terminal of the user.

[0023] In one embodiment of the present invention, it further includes:

[0024] Project the grid nodes in each RTK service layer onto a virtual layer within a local area to form an RTK service virtual layer for the key local area, and form an additional service level according to the virtual layer.

[0025] The RTK service grid layer matching device based on user behavior characteristics according to the embodiment of the present invention includes:

[0026] A memory for storing the program code of the processing process of the above-mentioned RTK service grid layer matching method based on user behavior characteristics;

[0027] A processor for executing the program code.

[0028] The RTK service grid layer matching device based on user behavior characteristics according to the embodiment of the present invention includes:

[0029] A layer establishment module for obtaining data access authorization for different RTK service grids to establish a VRS service data synchronization process, forming an RTK service layer for the corresponding grid, and establishing a mapping relationship between the layer and the speed;

[0030] A feedback processing module for receiving the positioning information periodically fed back by the positioning terminal to form corresponding sequential positioning data;

[0031] A feature processing module for regularly forming the average speed of the positioning terminal according to the sequential positioning data;

[0032] A feature recognition module for determining the layer and grid nodes according to the average speed, and broadcasting the corresponding VRS service data to the positioning terminal.

[0033] In one embodiment of the present invention, it further includes:

[0034] An additional layer establishment module for projecting the grid nodes in each RTK service layer onto a virtual layer within a local area to form an RTK service virtual layer for the key local area, and forming an additional service level according to the virtual layer.

[0035] RTK Service Grid Layer Matching Method and Device Based on User Behavior Characteristics in Embodiments of the Present Invention The RTK service grid layer matching method in embodiments of the present invention realizes the response guarantee of positioning service quality and level according to user behavior. The VRS service data is hierarchically managed by service quality and corresponding levels through the grid layer, and the speed characteristics feedback mapping user behavior or application scenarios are used to measure the scale of user demand for service quality, forming the timely broadcast of VRS service data at corresponding levels. It ensures that the VRS service data belonging to different business services can maximize data utilization and user coverage while balancing service costs. Description of the Drawings

[0036] Figure 1 The figure shows a schematic flowchart of an RTK service grid layer matching method based on user behavior characteristics in an embodiment of the present invention.

[0037] Figure 2 The figure shows a schematic architecture diagram of an RTK service grid layer matching device based on user behavior characteristics in an embodiment of the present invention. Detailed Embodiments

[0038] To make the objectives, technical solutions and advantages of the present invention clearer and more understandable, the present invention will be further described below with reference to the accompanying drawings and specific embodiments. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of them. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the scope of protection of the present invention.

[0039] An RTK service grid layer matching method based on user behavior characteristics in an embodiment of the present invention is as Figure 1 shown. In Figure 1 , this embodiment includes:

[0040] Step 100: Obtain data access authorizations for different RTK service grids, establish a VRS service data synchronization process, form an RTK service layer for the corresponding grid, and establish a mapping relationship between the layer and the speed.

[0041] Those skilled in the art can understand that when different RTK service systems use common reference station data to provide different VRS data services, they will each form a dynamically maintained virtual reference station (VRS) set, covering the corresponding service area and forming an RTK service grid. The virtual reference station set can be projected as grid nodes on a plane grid within the coordinate space of the service area, representing the coordinate positions and layout densities of the virtual reference stations. The VRS service data at the grid nodes usually includes periodically formed differential correction data. Access and synchronization of the VRS service data in each RTK service system are obtained through authorization. By integrating the VRS service data, a complete coverage area composed of the service areas of each RTK service grid is established, and an RTK service layer corresponding to each RTK service grid within the complete coverage area is established. Each layer respectively reflects the layout density of the virtual reference stations and the positioning service accuracy in the existing RTK service grid. The service quality is quantified by the grid node density in each layer, and the service level is quantified by establishing a mapping relationship between the speed interval and each layer.

[0042] Step 200: Receive the positioning information periodically fed back by the positioning terminal to form corresponding sequential positioning data.

[0043] The positioning terminal periodically feeds back its own positioning information to the server that uses the RTK service layer for RTK services. Through the positioning information, the server can identify terminal information including but not limited to the positioning time, positioning coordinates, and positioning quality, etc., and then form a sequential positioning data queue for each positioning terminal.

[0044] Step 300: Regularly form the average speed of the positioning terminal according to the sequential positioning data.

[0045] Calculate the average speed within the unit time in the RTK service coverage area using the time interval and coordinate spacing of the sequential positioning data to form a judgment on the movement azimuth, movement elevation, movement speed, and movement trend of the positioning terminal carrier.

[0046] Step 400: Determine the layer and grid nodes according to the average speed, and broadcast the corresponding VRS service data to the positioning terminal.

[0047] Map the RTK service layer to the average speed interval of the positioning terminal. Provide layer switching according to the change of the average speed, adapt to the adjacent grid nodes in the layer, and push the VRS service data of the grid nodes to the positioning terminal to ensure that the positioning terminal can obtain VRS service data that meets the speed or positioning service quality requirements.

[0048] The RTK service grid layer matching method based on user behavior characteristics in the embodiments of the present invention realizes the response guarantee of positioning service quality and level according to user behavior. Through the grid layer, the VRS service data is hierarchically managed according to service quality and corresponding levels, and the speed characteristics feedback of mapping user behavior or application scenarios is used to measure the scale of user demand for service quality, so as to form the timely broadcast of VRS service data at corresponding levels. It ensures that the VRS service data belonging to different business services can maximize data utilization rate and user coverage while balancing service costs.

[0049] As Figure 1 shown, in an embodiment of the present invention, step 100 includes:

[0050] Step 110: Establish an RTK service layer according to the source of VRS service data.

[0051] In an embodiment of the present invention, a virtual reference station in the same grid of a positioning service provider and the VRS service data provided by it form a corresponding RTK service layer, as well as the VRS service data of the grid nodes in the layer. Corresponding numbers of RTK service layers are formed according to the source of VRS service data.

[0052] Step 120: Map the service quality according to the grid node density in the layer.

[0053] The grid node density is calibrated according to the number of grid nodes in the unit coverage area. The positioning service quality that the VRS service data can achieve is mapped by using the grid node density.

[0054] Step 130: Form a service level through the mapping of the speed interval and the layer.

[0055] The service level is established by delimiting the speed interval, and the service level is mapped with the layer identifier to establish the data response association between the speed characteristic and the service quality.

[0056] The RTK service grid layer matching method based on user behavior characteristics in the embodiments of the present invention establishes an association relationship among the VRS service data, service level and service quality of different data sources through the layer, so that while establishing the basis for measuring user behavior, the compatibility between the VRS service data space and the coordinate space is ensured through coordinate normalization.

[0057] As Figure 1 shown, in an embodiment of the present invention, step 200 includes:

[0058] Step 210: When the user goes online, provide the VRS service data adapted in the default layer to the user's positioning terminal according to the default service level.

[0059] As an initialization process, after the user goes online, they are switched to the default layer according to the default service level, and the VRS service data formed by the adjacent grid nodes in the default layer is adapted according to the coordinates fed back by the user's positioning terminal. The service level is usually intermediate among the provided service levels, and the VRS service data in the corresponding default layer provides medium accuracy for positioning services.

[0060] Step 220: Receive the positioning information regularly fed back by the positioning terminal to obtain reliable positioning data.

[0061] In an embodiment of the present invention, the positioning information fed back by the positioning terminal adopts the GGA (GPS positioning data message) encapsulation format of NMEA0183, including information such as the longitude, latitude, altitude, positioning time, and positioning quality indication of the positioning device, which can be used to determine the current position and positioning accuracy. The reliable positioning data is obtained by filtering the GGA positioning information according to the positioning accuracy identifier in the positioning information, such as the coordinates in a specific coordinate system and the positioning time. The time interval of the regular feedback of the positioning terminal varies according to the terminal type, ranging from 1 to 5 seconds.

[0062] Step 230: Establish a chronological data queue for the positioning data.

[0063] After the user goes online, they continuously receive the positioning information regularly fed back by the terminal, and cache the obtained reliable positioning data into the data queue chronologically. Ensure that the chronological length of the queue is greater than the regular demand length.

[0064] Specifically, based on the GGA positioning information uploaded by the user's positioning terminal, select the positioning results that are fixed solutions and the HDOP value ≤ 1.0 (the digit after "E" in the GGA positioning information represents the positioning quality, where 4 represents a fixed solution, that is, the carrier phase ambiguity of this positioning result is fixed, and the positioning accuracy is high; at the same time, the HDOP value ≤ 1.0 indicates that the number and distribution of received satellites are good. Both conditions are met, indicating that the credibility of this positioning result is high and can be adopted), and arrange them continuously in chronological order.

[0065] The RTK service grid layer matching method based on user behavior characteristics in the embodiment of the present invention forms an effective acquisition and filtering of the positioning terminal information through the feedback mechanism of RTK technology, forms a quantitative basis for the continuous behavior characteristics of the service object, and ensures the timeliness and accuracy of the quantification of behavior characteristics.

[0066] As Figure 1 shown, in an embodiment of the present invention, step 300 includes:

[0067] Step 310: Calculate the average speed within a specified duration according to the chronological positioning data.

[0068] The specified duration can be set according to the user identifier. The specified duration can be a continuous specified duration or a specified duration with an interval rule. The average speed of the positioning terminal is periodically formed according to the specified duration.

[0069] In an embodiment of the present invention, the calculation of the average speed is as follows:

[0070] - Set the specified duration. In the embodiment of the present invention, it is set to 15 minutes.

[0071] - Determine the geocentric geodetic coordinate data at the start and end times of the specified duration in the sequential positioning data according to the specified duration, and convert the (latitude), (longitude), and h (geodetic height) in the geocentric geodetic coordinate data into the geocentric earth-fixed rectangular coordinates x, y, and z using the following formula.

[0072]

[0073]

[0074]

[0075] Among them, N is the radius of curvature of the prime vertical circle of the reference ellipsoid, and e is the eccentricity of the ellipsoid. They have the following relationship with the semi-major axis a and semi-minor axis b of the reference ellipsoid:

[0076]

[0077] The geodetic height h in the geocentric geodetic coordinate system has the following relationship with the above sea level altitude H (where is the geoid height. Both H and are included in the GGA information uploaded by the user positioning terminal):

[0078] - Form the total spatial displacement value between the start and end times using the following formula based on the geocentric earth-fixed rectangular coordinates x, y, and z at the start and end times of the specified duration :

[0079] Among them, is to The total value of the overall spatial displacement between the start and end times.

[0080] - Form the average speed for a specified duration according to the following formula :

[0081] where is and is the specific time difference at the moment.

[0082] The RTK service grid layer matching method based on user behavior characteristics in the embodiments of the present invention uses geophysical principles to form a quantitative inference of the velocity characteristics in the three-dimensional space, ensuring the accuracy and real-time nature of the key characteristics directly related to user behavior.

[0083] As Figure 1 shown, in an embodiment of the present invention, step 400 includes:

[0084] Step 410: Determine the VRS service data of the adapted grid nodes in the service level corresponding layer according to the velocity interval where the average speed is located and broadcast it to the user's positioning terminal.

[0085] In an embodiment of the present invention, the service level is determined according to the following velocity intervals:

[0086] If the average speed ≥ the velocity interval division threshold (for example, 10 m / s), it is considered that the positioning terminal is in a high-dynamic application scenario, and the VRS service data of the adapted grid nodes in the layer with a small grid density (for example, a spacing of 10 * 10 km) is broadcast to it, including differential correction data;

[0087] If the average speed < the velocity interval division threshold (for example, 10 m / s), it is considered that the positioning terminal is in a low-dynamic application scenario, and the system broadcasts the VRS service data of the adapted grid nodes in the layer with a large grid point density (for example, a spacing of 3 * 3 km) to it, including differential correction data.

[0088] In practical applications, the default service level in the initialization stage can be randomly selected.

[0089] In practical applications, the average speed is judged in a loop with a specified duration as the step length, and different positioning service characteristic requirements can be met according to user behavior characteristics.

[0090] The RTK service grid layer matching method based on user behavior characteristics in the embodiments of the present invention uses layers to distinguish the VRS service data within the same service coverage area in terms of service accuracy, ensuring that the differences in user behavior can obtain targeted service quality and effectively avoiding the excessive demand for computing power and communication resources by the service grid constructed by RTK technology when the user scale grows rapidly.

[0091] In an embodiment of the present invention, for the underlying data architecture of using the same-source general reference station data for each RTK service grid in the same area, it further includes:

[0092] Project the grid nodes in each RTK service layer onto a virtual layer in a local area to form an RTK service virtual layer for the key local area, and form additional service levels according to the virtual layer.

[0093] The additional RTK service virtual layer has a higher virtual reference station layout density and positioning service accuracy.

[0094] An RTK service grid layer matching device based on user behavior characteristics in an embodiment of the present invention includes:

[0095] A memory for storing the program code of the processing process of the RTK service grid layer matching method based on user behavior characteristics described in the above embodiments;

[0096] A processor for executing the program code of the processing process of the RTK service grid layer matching method based on user behavior characteristics described in the above embodiments.

[0097] The processor can adopt a DSP (Digital Signal Processor) digital signal processor, an FPGA (Field-Programmable Gate Array) field programmable gate array, an MCU (Microcontroller Unit) system board, an SoC (system on a chip) system board or a minimum system of a PLC (Programmable Logic Controller) including I / O.

[0098] An RTK service grid layer matching device based on user behavior characteristics in an embodiment of the present invention is as Figure 2 shown. In Figure 2 it, this embodiment includes:

[0099] A layer establishment module 10 for obtaining data access authorization for different RTK service grids to establish a VRS service data synchronization process, forming an RTK service layer for the corresponding grid, and establishing a mapping relationship between the layer and the speed;

[0100] The feedback processing module 20 is configured to receive the positioning information periodically fed back by the positioning terminal to form corresponding sequential positioning data;

[0101] The feature processing module 30 is configured to regularly form the average speed of the positioning terminal according to the sequential positioning data;

[0102] The feature recognition module 40 is configured to determine the layer and grid nodes according to the average speed, and broadcast the corresponding VRS service data to the positioning terminal.

[0103] As Figure 2 shown, in an embodiment of the present invention, the layer establishment module 10 includes:

[0104] The layer identification unit 11 is configured to establish an RTK service layer according to the VRS service data source;

[0105] The quality mapping unit 12 is configured to map the service quality according to the grid node density in the layer;

[0106] The registration mapping unit 13 is configured to form a service level through the mapping of the speed interval and the layer.

[0107] As Figure 2 shown, in an embodiment of the present invention, the feedback processing module 20 includes:

[0108] The service initialization unit 21 is configured to provide the VRS service data adapted in the default layer to the positioning terminal of the user according to the default service level after the user goes online;

[0109] The data sequentialization unit 22 is configured to receive the positioning information regularly fed back by the positioning terminal to obtain reliable positioning data;

[0110] The queue update unit 23 is configured to establish a sequential data queue of the positioning data.

[0111] As Figure 2 shown, in an embodiment of the present invention, the feature processing module 30 includes:

[0112] The feature quantization unit 31 is configured to calculate the average speed within a specified duration according to the sequential positioning data.

[0113] As Figure 2 shown, in an embodiment of the present invention, the feature recognition module 40 includes:

[0114] The feature response unit 41 is configured to broadcast the VRS service data of the grid nodes adapted in the layer corresponding to the service level to the positioning terminal of the user according to the speed interval where the average speed is located.

[0115] In an embodiment of the present invention, it further includes:

[0116] An additional layer creation module is used to project the grid nodes in each RTK service layer to a virtual layer within a local area, forming an RTK service virtual layer for the key local area, and forming an additional service level according to the virtual layer.

[0117] As described above, only the preferred specific embodiments of the present invention are provided, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by those skilled in the art within the technical scope disclosed by the present invention should be covered by the protection scope of the present invention. Therefore, the protection scope of the present invention should be subject to the protection scope of the claims.

Claims

1. A method for matching RTK service grid layers based on user behavior characteristics, characterized in that, Including: Obtain data access authorization for different RTK service grids to establish a VRS service data synchronization process, form RTK service layers corresponding to the grids, each RTK service layer respectively reflects the virtual reference station layout density and positioning service accuracy in the existing RTK service grid, and establish a mapping relationship between each RTK service layer and speed; Receive the positioning information periodically fed back by the positioning terminal to form corresponding sequential positioning data; Regularly form the average speed of the positioning terminal according to the sequential positioning data; Determine the layer and grid nodes according to the average speed, and broadcast the VRS service data of the corresponding grid nodes to the positioning terminal.

2. The RTK service grid layer matching method based on user behavior characteristics according to claim 1, wherein The forming of the RTK service layer corresponding to the grid and the establishment of the mapping relationship between the layer and speed include: Establish an RTK service layer according to the VRS service data source; Map the service quality according to the grid node density in the layer; Form service levels by mapping the speed range and the layer.

3. The RTK service grid layer matching method based on user behavior characteristics according to claim 1, wherein, The formation of the sequential positioning data includes: After the user goes online, provide the VRS service data adapted in the default layer to the user's positioning terminal according to the default service level; Receive the positioning information regularly fed back by the positioning terminal to obtain reliable positioning data; Establish a sequential data queue of the positioning data.

4. The RTK service grid layer matching method based on user behavior characteristics according to claim 1, wherein The formation of the average speed includes: Calculate the average speed within a specified duration according to the sequential positioning data.

5. The RTK service grid layer matching method based on user behavior characteristics according to claim 1, wherein The determining of the layer and grid nodes according to the average speed and the broadcasting of the VRS service data to the positioning terminal include: Determine the VRS service data of the grid nodes adapted in the layer corresponding to the service level according to the speed range where the average speed is located, and broadcast it to the user's positioning terminal.

6. The RTK service grid layer matching method based on user behavior characteristics according to claim 1, wherein, Also including: Project the grid nodes in each RTK service layer onto a virtual layer in a local area to form an RTK service virtual layer for the key local area, and form additional service levels according to the virtual layer.

7. An RTK service grid layer matching device based on user behavior characteristics, characterized in that, Including: A memory for storing the program code of the processing process of the RTK service grid layer matching method based on user behavior characteristics as described in any one of claims 1 to 6; A processor for executing the program code.

8. An RTK service grid layer matching device based on user behavior characteristics, characterized in that, Including: A layer establishment module for obtaining data access authorization for different RTK service grids to establish a VRS service data synchronization process, forming RTK service layers corresponding to the grids, each RTK service layer respectively reflecting the virtual reference station layout density and positioning service accuracy in the existing RTK service grid, and establishing a mapping relationship between each RTK service layer and speed; A feedback processing module for receiving the positioning information periodically fed back by the positioning terminal to form corresponding sequential positioning data; A feature processing module for regularly forming the average speed of the positioning terminal according to the sequential positioning data; A feature recognition module for determining the layer and grid nodes according to the average speed, and broadcasting the VRS service data of the corresponding grid nodes to the positioning terminal.

9. The RTK service grid layer matching device based on user behavior characteristics according to claim 8, wherein, Also including: An additional layer establishment module for projecting the grid nodes in each RTK service layer onto a virtual layer in a local area to form an RTK service virtual layer for the key local area, and forming additional service levels according to the virtual layer.

Images