Indoor positioning coordinate feature recognition method, system, equipment and medium

Abstract

The invention belongs to the technical field of indoor positioning, and particularly relates to an indoor positioning coordinate feature recognition method, system and device and a medium, which are used for judging whether positioning coordinates are credible or not, retaining point locations with higher credibility and abandoning point locations with lower credibility through the continuity of geographic attributes, thereby improving the accuracy of positioning points.

Description

Technical Field

[0001] This invention belongs to the field of indoor positioning technology, specifically relating to an indoor positioning coordinate feature recognition method, system, device, and medium. Background Technology

[0002] Currently, in the field of indoor positioning, Bluetooth positioning is generally based on the difference in signal strength of multiple Beacons to calculate indoor spatial coordinates, and the positioning accuracy is generally around 3 to 8 meters.

[0003] In areas with complex indoor spatial structures, positioning points calculated based on signal strength analysis often result in locations that are inaccessible, such as cabinets, walls, or desktops, due to a lack of indoor map information. Determining the regional attributes of the positioning point's location through spatial calculations can significantly reduce the likelihood of inaccurate placement. However, in real-time positioning, calculating the spatial intersection between the point and the vector map is a time-consuming and resource-intensive process, which cannot meet the requirements for real-time positioning. Summary of the Invention

[0004] To address the aforementioned problems, this application proposes an indoor positioning coordinate feature recognition method based on prior geographical knowledge. This method adds geographical attributes to positioning points and determines the reliability of positioning coordinates based on the consistency of these attributes. Points with higher reliability are retained, while those with lower reliability are discarded, thereby improving the accuracy of positioning. The technical solution is as follows:

[0005] An indoor positioning coordinate feature recognition method includes the following steps:

[0006] S1: Based on the floor plan of the interior building, collect geographic information data to form a geographic coding quick lookup table;

[0007] S2: Based on the geocoding quick lookup table, pre-store the passable attributes to form a passable chain;

[0008] S3: Generate a grid of points that covers the entire image with a fixed unit width;

[0009] S4: Determine the starting point, rotation angle, and cell length of the grid.

[0010] S5: Determine the row and column numbers of the grid point where the positioning point is located, obtain the grid point through the row and column numbers, and assign the grid attributes to the current point;

[0011] S6: Determine whether the current point is an impassable or passable point;

[0012] If the current point is classified as impassable, then discard that point.

[0013] If the current attribute point is a passable point, then the credibility of the current point is judged based on the passable chain and the attributes of the previous point. If no passable chain is found, it means that the credibility of the current point is low and should be discarded. If a passable chain is found, it means that the credibility of the current point is high. The current point is output and the point attributes are added to the cache for future use.

[0014] S7: When multiple points with low credibility appear, the attributes are reset, the currently untrusted points are converted into trusted points and output; repeat S5-S7.

[0015] Preferably, in step S1, based on the floor plan of the interior building, combined with the drawings and actual site conditions, geographic information data is collected, and the building components within the map are assigned type values ​​and encoded to form a geographic coding quick lookup table. Preferably, for spatial units and data entities that intersect, the data entities are divided according to the boundaries of the spatial units, and the several smaller blocks of data entities after division are encoded and assigned codes respectively;

[0016] Data segmentation: Based on the precision of the spatial grid, data entities are segmented into corresponding grid units according to longitude and latitude ranges;

[0017] Encoding and Assignment: Associating spatial grid cells with segmented data entities, assigning the code of each grid cell as a field to the attribute table of the data entity, and compiling a geocoding quick lookup table.

[0018] Preferably, in step S3, the dot matrix is ​​numbered by row and column, and the specific steps are as follows:

[0019] The row and column numbers are incremented from the bottom left corner (0, 0) to the right and upward. The geographic coordinates of the center point of each smallest unit grid are assigned, that is, the geographic coordinates corresponding to the center point are marked, and the influence range is determined. The influence range is the smallest unit grid centered on the center point.

[0020] Preferably, in step S4, the starting point of the grid is the first point at the lower left corner of the grid, the rotation angle is the rotation angle of the grid relative to the X-axis, and the cell length is the side length of each smallest cell in the grid.

[0021] Preferably, in step S5, the row and column numbers of the grid point where the positioning point is located are determined using the following formula, and the grid point is obtained through the row and column numbers. The grid attributes are then assigned to the current point (x, y).

[0022] x=(x1-x2)*cos(angle)-(y1-y2)*sin(angle)+x2

[0023] y=(y1-y2)*cos(angle)+(x1-x2)*sin(angle)+y2

[0024] colIdx=(int)((x-x2) / cellSize)

[0025] rowIdx=(int)((y2-y) / cellSize),

[0026] in,

[0027] (x2, y2) is the starting point for calculating the grid coordinates, and angle is the rotation angle of the grid relative to the X-axis.

[0028] (x1, y1) are the coordinates of the current point, cellSize is the length of the grid cell, (colIdx, rowIdx) are the row and column numbers of the grid point to which the point belongs, and int indicates taking the maximum value.

[0029] Preferably, data retrieval and matching include place name and address search, grid code search, and building name search.

[0030] An indoor positioning coordinate feature recognition system includes a data acquisition unit, a data processing unit, a data storage unit, a control unit, and a display unit;

[0031] The data acquisition unit: based on the floor plan of the indoor building, collects geographic information data, forms a geographic coding quick lookup table, and sends the data to the data processing unit and the data storage unit;

[0032] Data storage unit: Store geocoded quick lookup tables, pre-store accessible attributes to form accessible chains;

[0033] The data processing unit: generates a grid matrix covering the entire image with a fixed cell width; determines the starting point, rotation angle, and cell length of the grid matrix; determines the row and column number of the grid point where the positioning point is located, obtains the grid point through the row and column number, and assigns the grid attributes to the current point;

[0034] Control unit: Determines whether the current point is impassable or passable;

[0035] Display unit: Displays the judgment result in real time.

[0036] An electronic device includes at least one processor and a memory communicatively connected to the processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform the method of this application.

[0037] A computer storage medium storing a computer program that, when executed by a processor, implements the method described in this application.

[0038] Compared with the prior art, the beneficial effects of this application are as follows:

[0039] 1. This patent proposes an indoor positioning coordinate feature recognition method based on geographical prior knowledge. Geographical attributes are added to the positioning point. By the coherence of the geographical attributes, the reliability of the positioning coordinates is determined. Points with higher reliability are retained, and points with lower reliability are discarded, thereby improving the accuracy of the positioning point.

[0040] 2. This patent retains points with higher reliability and discards points with lower reliability, thereby improving the accuracy of the positioning points. This can improve the tracking effect of hazardous chemical enterprises and has broad application prospects. Attached Figure Description

[0041] Figure 1 This is an indoor geographic map. Detailed Implementation

[0042] To make the contents of this patent easier to understand, the following detailed description of this patent is provided in conjunction with the accompanying drawings.

[0043] Reference Figure 1 Indoor positioning coordinate feature recognition methods based on prior geographical knowledge include:

[0044] S1: Based on the floor plan of the interior building, combined with CAD drawings and actual site conditions, collect geographic information data, assign type values ​​to the building components (referring to geographic entities such as office furniture such as tables and chairs, and buildings such as walls and floors) in the map, and form a geographic code quick lookup table.

[0045] S2: Based on the geocoding quick lookup table, pre-store the passable attributes to form passable chains, such as meeting room 1-corridor-meeting room 2 (10001-10002-10003), workstation-corridor-restroom, etc.

[0046] S3: Generate a grid of points covering the entire map with a fixed unit width. Number the points in rows and columns (the row and column numbers are incremented from the bottom left corner (0, 0) to the right and upwards). Assign geographic coordinates to the center point of each smallest unit of the grid (mark the geographic coordinates corresponding to the center point) and determine its influence range (the influence range is the grid of the smallest unit centered on the center point).

[0047] S4: Determine the starting point of the grid (the first point at the bottom left corner of the grid), rotation angle (the angle of rotation of the grid relative to the X-axis, see angle in the figure), cell length (the side length of each smallest cell in the grid), and other parameters.

[0048] S5: During real-time positioning (i.e., obtaining the positioning coordinates of the target in real time), the row and column numbers of the grid point where the positioning point is located are determined by the following formula, and the grid point is obtained by the row and column numbers, and the grid attributes are assigned to the current point.

[0049] x=(x1-x2)*cos(angle)-(y1-y2)*sin(angle)+x2

[0050] y=(y1-y2)*cos(angle)+(x1-x2)*sin(angle)+y2

[0051] colIdx=(int)((x-x2) / cellSize)

[0052] rowIdx=(int)((y2-y) / cellSize), where,

[0053] (x2, y2) is the starting point for the grid coordinates.

[0054] angle is the rotation angle of the grid relative to the X-axis.

[0055] (x1, y1) are the coordinates of the current point.

[0056] cellSize is the length of the grid cell.

[0057] (colIdx, rowIdx) represent the row and column numbers of the grid point to which the point belongs.

[0058] S6: If the current point is classified as impassable, then discard the point.

[0059] S7: If the current attribute point is a passable point, then based on the passable chain and the attributes of the previous point, determine the credibility of the current point. If no passable chain is found, it means that the credibility of the current point is low and should be discarded. If a passable chain is found, it means that the credibility of the current point is high. Output the current point and add the point attributes to the cache for future use.

[0060] S8: When multiple points with low credibility appear, the attributes are reset, and the currently untrusted points are converted into trusted points and output.

[0061] S9: Repeat S5.

[0062] An indoor positioning coordinate feature recognition system includes a data acquisition unit, a data processing unit, a data storage unit, a control unit, and a display unit;

[0063] The data acquisition unit: based on the floor plan of the indoor building, collects geographic information data, forms a geographic coding quick lookup table, and sends the data to the data processing unit and the data storage unit;

[0064] Data storage unit: Store geocoded quick lookup tables, pre-store accessible attributes to form accessible chains;

[0065] The data processing unit: generates a grid matrix covering the entire image with a fixed cell width; determines the starting point, rotation angle, and cell length of the grid matrix; determines the row and column number of the grid point where the positioning point is located, obtains the grid point through the row and column number, and assigns the grid attributes to the current point;

[0066] Control unit: Determines whether the current point is impassable or passable;

[0067] Display unit: Displays the judgment result in real time.

[0068] An electronic device includes at least one processor and a memory communicatively connected to the processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform the method of this application.

[0069] A computer storage medium storing a computer program that, when executed by a processor, implements the method described in this application.

[0070] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), memory bus DRAM (RDRAM), and interface DRAM (DRDRAM), etc.

[0071] In the description of this specification, references to terms such as "some embodiments," "other embodiments," and "ideal embodiments" indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, the illustrative descriptions of the above terms do not necessarily refer to the same embodiments or examples.

Claims

1. A method for indoor positioning coordinate feature recognition, characterized in that, Includes the following steps: S1: Based on the floor plan of the interior building, collect geographic information data to form a geographic coding quick lookup table; S2: Based on the geocoding quick lookup table, pre-store the passable attributes to form a passable chain; S3: Generate a grid of points that covers the entire image with a fixed unit width; S4: Determine the starting point, rotation angle, and cell length of the grid. S5: Determine the row and column numbers of the grid point where the positioning point is located, obtain the grid point through the row and column numbers, and assign the grid attributes to the current point; S6: Determine whether the current point is an impassable or passable point; If the current point is classified as impassable, then discard that point. If the current attribute point is a passable point, then the credibility of the current point is judged based on the passable chain and the attributes of the previous point. If no passable chain is found, it means that the credibility of the current point is low and should be discarded. If a passable chain is found, it means that the credibility of the current point is high. The current point is output and the point attributes are added to the cache for future use. S7: When multiple points with low credibility appear, the attributes are reset, and the currently untrusted points are converted into trusted points and output. Repeat S5-S7.

2. The indoor positioning coordinate feature recognition method according to claim 1, characterized in that, In step S1, based on the floor plan of the interior building, combined with the drawings and the actual site conditions, geographic information data is collected, and the building components in the map are assigned type values ​​and codes to form a geographic code quick lookup table.

3. The indoor positioning coordinate feature recognition method according to claim 1, characterized in that, For spatial units and data entities that intersect, the data entities are divided according to the boundaries of the spatial units, and the resulting small blocks of data entities are encoded and assigned codes respectively. Data segmentation: Based on the precision of the spatial grid, data entities are segmented into corresponding grid units according to longitude and latitude ranges; Encoding and Assignment: Associating spatial grid cells with segmented data entities, assigning the code of each grid cell as a field to the attribute table of the data entity, and compiling a geocoding quick lookup table.

4. The indoor positioning coordinate feature recognition method according to claim 1, characterized in that, In step S3, the dot matrix is ​​numbered by row and column. The specific steps are as follows: The row and column numbers are incremented from the bottom left corner (0, 0) to the right and upward. The geographic coordinates of the center point of each smallest unit grid are assigned, that is, the geographic coordinates corresponding to the center point are marked, and the influence range is determined. The influence range is the smallest unit grid centered on the center point.

5. The indoor positioning coordinate feature recognition method according to claim 1, characterized in that, In step S4, the starting point of the grid is the first point at the bottom left corner of the grid, the rotation angle is the rotation angle of the grid relative to the X-axis, and the cell length is the side length of each smallest cell in the grid.

6. The indoor positioning coordinate feature recognition method according to claim 1, characterized in that, In step S5, the row and column numbers of the grid point where the positioning point is located are determined using the following formula, and the grid point is obtained through the row and column numbers. The grid attributes are then assigned to the current point (x, y). x=(x1-x2)*cos(angle)-(y1-y2)*sin(angle)+x2 y=(y1-y2)*cos(angle)+(x1-x2)*sin(angle)+y2 colIdx=(int)((x-x2) / cellSize) rowIdx=(int)((y2-y) / cellSize), in, (x2, y2) is the starting point for calculating the grid coordinates, and angle is the rotation angle of the grid relative to the X-axis. (x1, y1) are the coordinates of the current point, cellSize is the length of the grid cell, (colIdx, rowIdx) are the row and column numbers of the grid point to which the point belongs, and int indicates taking the maximum value.

7. The indoor positioning coordinate feature recognition method according to claim 1, characterized in that, Data retrieval and matching include place name and address search, grid code search, and building name search.

8. An indoor positioning coordinate feature recognition system according to any one of claims 1-7, characterized in that, It includes a data acquisition unit, a data processing unit, a data storage unit, a control unit, and a display unit; The data acquisition unit: based on the floor plan of the indoor building, collects geographic information data, forms a geographic coding quick lookup table, and sends the data to the data processing unit and the data storage unit; Data storage unit: Store geocoded quick lookup tables, pre-store accessible attributes to form accessible chains; The data processing unit: generates a grid of dots covering the entire image with a fixed unit width; Determine the starting point, rotation angle, and cell length of the grid; determine the row and column number of the grid point where the positioning point is located, obtain the grid point through the row and column number, and assign the grid attributes to the current point; Control unit: Determines whether the current point is impassable or passable; Display unit: Displays the judgment results in real time.

9. An electronic device, characterized in that, The method includes at least one processor and a memory communicatively connected to the processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform the method according to any one of claims 1-7.

10. A computer storage medium storing a computer program, characterized in that, When the program is executed by the processor, it implements the method described in any one of claims 1-7.

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