Positioning area identification method and positioning method based on beacon deployment information

Abstract

The present invention discloses a positioning area identification method based on beacon deployment information and a positioning method. The positioning area identification method based on beacon deployment information comprises constructing an undirected graph according to the category of positioning beacons and the physical distance between positioning beacons; performing connectivity analysis on the undirected graph to preliminarily form each connected component into a group; performing cluster analysis on each connected component to form a subgraph according to the deployment density and coverage of the positioning beacons; calculating the outer edges of all positioning beacons included in each subgraph to generate the boundary contour of the subgraph; and generating the applicable area range corresponding to different positioning technologies according to the calculated boundary contour.

Description

Technical Field

[0001] The present invention relates to the field of positioning technology, and in particular to a positioning area identification method and a positioning method based on beacon deployment information. Background Art

[0002] In modern positioning systems, in order to meet the needs of high-precision positioning indoors and outdoors, various types of positioning beacon devices are usually deployed, such as Bluetooth positioning beacons, UWB (ultra-wideband) positioning beacons, etc. Different types of positioning beacons have different coverage, positioning accuracy and applicable scenarios. The positioning method in the existing technology requires manual analysis of the deployment of positioning beacons to determine the positioning technology that should be used preferentially in different areas.

[0003] However, this method has the following problems: (1) High labor cost: Professionals are required to conduct a lot of on-site debugging and configuration, which is time-consuming and labor-intensive; (2) Low efficiency: Manual analysis is slow and cannot respond to changes in the deployment of positioning beacons in a timely manner; (3) Insufficient accuracy: Human judgment may be missed, resulting in improper selection of positioning technology and affecting positioning accuracy; (4) Lack of automation and intelligence: The existing system cannot automatically adjust the positioning strategy according to the actual deployment of positioning beacons and lacks dynamic adaptability. The existing technology cannot effectively identify the positioning technology that should be used preferentially in each map area based on the deployment information of positioning beacons, resulting in limited performance and user experience of the positioning system.

[0004] The above contents are only used to assist in understanding the technical solution of the present invention and do not constitute an admission that the above contents are prior art. Summary of the invention

[0005] The main purpose of the present invention is to provide a positioning area identification method and a positioning method based on beacon deployment information, aiming to solve the above-mentioned technical problems in the prior art.

[0006] To achieve the above object, the present invention provides a method for identifying a positioning area based on beacon deployment information, and the method for identifying a positioning area based on beacon deployment information comprises:

[0007] Construct an undirected graph according to the categories of positioning beacons and the physical distances between positioning beacons;

[0008] Performing connectivity analysis on the undirected graph, and initially forming each connected component into a group;

[0009] According to the deployment density and coverage of the positioning beacons, cluster analysis is performed on each connected component to form a subgraph;

[0010] For all positioning beacons included in each sub-image, calculating the outer edges to generate the boundary contour of the sub-image;

[0011] Based on the calculated boundary contour, the applicable area range corresponding to different positioning technologies is generated.

[0012] Preferably, in the positioning area identification method based on beacon deployment information, constructing an undirected graph according to the category of the positioning beacon and the physical distance between the positioning beacons includes:

[0013] For each type of positioning beacon, according to the physical distance between the positioning beacons, the positioning beacon pairs with physical distances within the preset coverage range are connected together, and the positioning beacon pairs with physical distances exceeding the preset range are not connected, forming an undirected graph.

[0014] Preferably, in the positioning area identification method based on beacon deployment information, performing cluster analysis on each connected component to form a subgraph according to the deployment density and coverage of the positioning beacon includes:

[0015] Determine the neighborhood radius and minimum number of sample points based on the deployment density and coverage of positioning beacons;

[0016] According to the neighborhood radius and the minimum number of sample points, each connected component is clustered to form a subgraph.

[0017] Preferably, in the positioning area identification method based on beacon deployment information, performing cluster analysis on each connected component to form a subgraph according to the neighborhood radius and the minimum number of sample points includes:

[0018] For each connected component, take each positioning beacon as the center and count the number of positioning beacons within the neighborhood radius;

[0019] When the number of positioning beacons is greater than or equal to the minimum number of sample points, the positioning beacon is marked as a core positioning beacon, and the core positioning beacon and the positioning beacons within its neighborhood radius are placed in the corresponding subgraph;

[0020] When the number of positioning beacons is less than the minimum number of sample points, the positioning beacon is marked as a non-core positioning beacon, and other positioning beacons continue to be used as centers until all core positioning beacons are marked.

[0021] Preferably, in the positioning area identification method based on beacon deployment information, the step of calculating the outer edges of all positioning beacons included in each sub-graph to generate the boundary contour of the sub-graph includes:

[0022] Take the positioning beacon with the smallest A axis value in the sub-graph as the starting positioning beacon and add it to the boundary set corresponding to the sub-graph;

[0023] Taking the starting positioning beacon as a reference, traverse the other positioning beacons in the subgraph, and calculate the angle between the line connecting each positioning beacon and the starting positioning beacon and the positive direction of the A coordinate axis;

[0024] Selecting the positioning beacon with the smallest calculated angle as the next starting positioning beacon and adding it to the boundary set corresponding to the subgraph until the next starting positioning beacon found is the position of the first starting positioning beacon;

[0025] The location beacons in the boundary set corresponding to the sub-graph are connected to form a boundary outline of the sub-graph.

[0026] Preferably, in the positioning area identification method based on beacon deployment information, the step of constructing an undirected graph according to the category of the positioning beacons and the physical distance between the positioning beacons includes:

[0027] In response to changes in the deployment of the positioning beacons, an undirected graph is constructed according to the categories of the positioning beacons and the physical distances between the positioning beacons;

[0028] Accordingly, the step of generating applicable area ranges corresponding to different positioning technologies according to the calculated boundary contours includes:

[0029] According to the calculated boundary contour, the applicable area range corresponding to different positioning technologies is updated.

[0030] In order to achieve the above object, the present invention also provides a positioning method, the positioning method comprising:

[0031] The positioning area identification method based on beacon deployment information is used to determine the positioning technology corresponding to different areas;

[0032] Positioning is performed based on the positioning technology corresponding to the area.

[0033] In order to achieve the above object, the present invention also provides a positioning area identification device based on beacon deployment information, and the positioning area identification device based on beacon deployment information includes:

[0034] A construction unit, used for constructing an undirected graph according to the categories of the positioning beacons and the physical distances between the positioning beacons;

[0035] an analysis unit, configured to perform connectivity analysis on the undirected graph and preliminarily form each connected component into a group;

[0036] A clustering unit, used to perform cluster analysis on each connected component to form a subgraph according to the deployment density and coverage of the positioning beacons;

[0037] A calculation unit, configured to calculate outer edges of all positioning beacons included in each sub-image to generate a boundary contour of the sub-image;

[0038] The recognition unit is used to generate applicable area ranges corresponding to different positioning technologies according to the calculated boundary contours.

[0039] In order to achieve the above object, the present invention further provides a computer device, the computer device comprising:

[0040] at least one processor; and,

[0041] a memory communicatively connected to the at least one processor; wherein,

[0042] The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the above-mentioned positioning area identification method based on beacon deployment information and / or the above-mentioned positioning method.

[0043] In order to achieve the above-mentioned purpose, the present invention also provides a computer-readable storage medium storing a computer program, characterized in that when the computer program is executed by a processor, it implements the above-mentioned positioning area identification method based on beacon deployment information and / or the above-mentioned positioning method.

[0044] The present invention has at least the following beneficial effects:

[0045] The method for identifying a positioning area based on beacon deployment information provided by the present invention constructs an undirected graph according to the type of positioning beacons and the physical distance between positioning beacons; performs connectivity analysis on the undirected graph to preliminarily form each connected component into a group; performs cluster analysis on each connected component to form a subgraph according to the deployment density and coverage of the positioning beacons; calculates the outer edges of all positioning beacons included in each subgraph to generate the boundary contour of the subgraph; generates the applicable area range corresponding to different positioning technologies according to the calculated boundary contour, so that the analysis of positioning beacon data and the identification of positioning areas can be automatically completed without manual intervention, which greatly reduces the labor cost;

[0046] Furthermore, by being able to accurately identify the positioning technology that should be used preferentially in each area, the overall accuracy and reliability of the positioning system are improved;

[0047] Furthermore, when the beacon deployment changes, the positioning area division can be automatically updated, which has good dynamic adaptability;

[0048] Furthermore, large-scale beacon data processing and analysis can be completed quickly, improving the operating efficiency of the system.

[0049] Furthermore, the present invention provides an accurate regional division basis for the positioning fusion algorithm, which helps to effectively integrate different positioning technologies and improve user experience.

[0050] Furthermore, the present invention reduces interference between different beacon types and reduces positioning errors through reasonable beacon clustering and area division. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1 A schematic diagram of a first implementation of a positioning area identification method based on beacon deployment information provided by the present invention;

[0052] Figure 2 Schematic diagram of constructing an undirected graph for location beacons;

[0053] Figure 3 Constructing a schematic diagram of an undirected graph for a location beacon after connected component identification and clustering refinement;

[0054] Figure 4 A schematic diagram of generating boundary contours for the outer edges of all positioning beacons in a sub-image according to the present invention;

[0055] Figure 5 A schematic diagram of a first implementation of a positioning method provided by the present invention;

[0056] Figure 6 A schematic diagram of an embodiment of a positioning area identification device based on beacon deployment information provided by the present invention;

[0057] Figure 7 A schematic diagram of a computer device according to the present invention.

[0058] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings in conjunction with the embodiments. DETAILED DESCRIPTION

[0059] The technical solution of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of the embodiments. The present invention will be described in detail below with reference to the accompanying drawings and in conjunction with the embodiments. It should be noted that the embodiments of the present invention and the features in the embodiments can be combined with each other without conflict.

[0060] In the embodiments of the present invention, the term "and / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B may represent three situations: A exists alone, A and B exist at the same time, and B exists alone. The character " / " generally indicates that the associated objects before and after are in an "or" relationship.

[0061] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence.

[0062] In the embodiments of the present invention, the term "plurality" refers to two or more than two, and other quantifiers are similar.

[0063] In the present invention, unless otherwise specified, the directional words used, such as "up, down, top, bottom", usually refer to the directions shown in the drawings, or to the components themselves in the vertical, perpendicular or gravity directions; similarly, for ease of understanding and description, "inside and outside" refer to the inside and outside relative to the outline of each component itself, but the above-mentioned directional words are not used to limit the present invention.

[0064] In order to make the purpose, technical scheme and advantages of the embodiments of the present invention clearer, the embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings. However, it can be understood by those skilled in the art that in the embodiments of the present invention, many technical details are proposed in order to enable the reader to better understand the present invention. However, even without these technical details and various changes and modifications based on the following embodiments, the technical scheme claimed in the present invention can also be implemented. The division of the following embodiments is for the convenience of description and should not constitute any limitation on the specific implementation of the present invention. The various embodiments can be combined and referenced with each other under the premise of no contradiction.

[0065] In order to solve the above problems, the present embodiment relates to a positioning area identification method based on beacon deployment information, which can be applied to computer devices. The computer devices can be electronic devices with data processing capabilities such as desktop computers, tablet computers, notebooks, etc. In other embodiments, they can also be other electronic devices with data processing capabilities, and no specific restrictions are made here.

[0066] The following is an explanation of the implementation details of the positioning area identification method based on beacon deployment information of the first embodiment of the present invention. The following content is only the implementation details provided for the convenience of understanding and is not necessary for the implementation of this solution.

[0067] The specific process of this implementation is as follows: Figure 1 As shown, specifically including:

[0068] Step S100, constructing an undirected graph according to the types of positioning beacons and the physical distances between positioning beacons;

[0069] It should be understood that positioning beacons are used to accurately determine the location of target objects. Positioning beacons can be divided into ultra-wideband (UWB) beacons, Bluetooth positioning beacons, etc.

[0070] Specifically, for each type of positioning beacons, based on the physical distance between the positioning beacons, the positioning beacon pairs whose physical distance is within the preset coverage range are connected together, and the positioning beacon pairs whose physical distance exceeds the preset range are not connected, so as to form an undirected graph.

[0071] When constructing an undirected graph, a positioning beacon is used as a node of the graph. Taking the positioning beacons including ultra-wideband beacons and Bluetooth positioning beacons as an example, when constructing an undirected graph, ultra-wideband beacon pairs whose physical distances are within the preset coverage range of all ultra-wideband beacons are connected together, and ultra-wideband beacon pairs whose physical distances exceed the preset range are not connected. Bluetooth beacon pairs whose physical distances are within the preset coverage range of all Bluetooth beacons are connected together, and Bluetooth beacon pairs whose physical distances exceed the preset range are not connected.

[0072] For example, ultra-wideband beacons include {A1, A2, A3, ...}, and Bluetooth positioning beacons include {B1, B2, B3, ...}. When constructing an undirected graph, when the physical distance between two nodes in {A1, A2, A3, ...} is within a preset range, the two nodes are connected; when the physical distance between two nodes in {B1, B2, B3, ...} is within a preset range, the two nodes are connected.

[0073] In addition, when the deployment of positioning beacons changes, the applicable area ranges corresponding to different positioning technologies can be updated in a timely manner. Specifically, in response to changes in the deployment of positioning beacons, an undirected graph is constructed according to the types of positioning beacons and the physical distances between positioning beacons.

[0074] Step S200, performing connectivity analysis on the undirected graph, and preliminarily forming each connected component into a group;

[0075] It should be understood that connectivity analysis is an analytical method used to evaluate the degree of connection between nodes in a graph (which can be a variety of network structures such as geographic networks, communication networks, circuit networks, etc.). Its core is to determine whether there is a path from one node to another in the graph, as well as the characteristics of these paths, such as length, number, etc. A connected component is a maximal connected subgraph of an undirected graph. By performing connectivity analysis on the constructed undirected graph, each connected component is identified. Each connected component is formed into a group, so that the clustering area of ​​the beacons is preliminarily divided, and the beacons that may physically affect each other are grouped together.

[0076] like Figure 2 As shown, Figure 2 The dotted lines connecting a2 and a5, a4 and a6 are beyond the preset range, so a2 and a5, a4 and a6 cannot be connected. Figure 2 There are other positioning beacon pairs that cannot be connected, such as a3 and a5, which are not listed one by one. Figure 2 The positioning beacons in the graph are divided into two groups, Group 1 and Group 2. The maximum distance is set to separate Group 1 and Group 2 to simulate the coverage relationship of the actual signal and ensure that the graph structure reflects the effective communication range of the positioning beacon.

[0077] Step S300, performing cluster analysis on each connected component to form a subgraph according to the deployment density and coverage of the positioning beacons;

[0078] It should be noted that after the connected component identification, only the clustering area of ​​the positioning beacons can be preliminarily divided. There are also some special cases where a small number of positioning beacons may connect multiple groups of positioning beacons into the same group. Figure 3 After the connectivity analysis, Figure 3 The location beacons a1 to a8 will form the same group, but in fact the physical distances between the location beacons in {a1, a2, a3, a4} and the location beacons in {a5, a6, a7} are large, and they are not suitable to be connected as a group. Therefore, it is necessary to further cluster each connected component to form a subgraph.

[0079] Further cluster analysis can identify areas with higher density and effectively handle noise points. Figure 3 In the figure, further analysis of this connected component can yield two clusters, cluster 1 and cluster 2. Cluster 1 includes {a1, a2, a3, a4, a8}, and cluster 2 includes {a5, a6, a7}. This can further refine the clustering results and identify more accurate beacon-dense areas.

[0080] Specifically, step S300 includes step S310 and step S320 .

[0081] Step S310, determining the neighborhood radius and the minimum number of sample points according to the deployment density and coverage of the positioning beacons;

[0082] Step 320: Perform cluster analysis on each connected component to form a subgraph according to the neighborhood radius and the minimum number of sample points.

[0083] Specifically, for each connected component, each positioning beacon is taken as the center, and the number of positioning beacons within the neighborhood radius is counted; when the number of positioning beacons is greater than or equal to the minimum number of sample points, the positioning beacon is marked as a core positioning beacon, and the core positioning beacon and the positioning beacons within its neighborhood radius are placed in the corresponding subgraph; when the number of positioning beacons is less than the minimum number of sample points, the positioning beacon is marked as a non-core positioning beacon, and other positioning beacons continue to be taken as the center until all core positioning beacons are marked.

[0084] The minimum number of sample points can be set according to specific needs, for example, according to the division accuracy.

[0085] It should be noted that the positioning beacons in the area are divided into multiple sub-graphs, and each sub-graph corresponds to a positioning technology.

[0086] Example: The region includes sub Figure 1 ,son Figure 2 ,son Figure 3 , and sub Figure 4 ,son Figure 1 Kazuko Figure 4 Corresponding to Bluetooth positioning technology, Figure 2 Kazuko Figure 3 Corresponding to ultra-wideband positioning technology, when the mobile terminal enters the sub Figure 1 When the mobile terminal enters a corresponding area, there may be multiple positioning results generated by different positioning methods. At this time, it is necessary to determine which positioning technology to select based on which sub-map area the specific area entered by the mobile terminal belongs to. If the area A entered by the mobile terminal belongs to sub-map area Figure 1 If the area is covered by Bluetooth, then choose Bluetooth positioning technology to avoid interference from other types of beacons.

[0087] Step S400, for all positioning beacons included in each sub-graph, calculating the outer edges to generate the boundary contour of the sub-graph;

[0088] Specifically, the positioning beacon with the smallest value of the A coordinate axis in the sub-graph is taken as the starting positioning beacon and added to the boundary set corresponding to the sub-graph; the starting positioning beacon is used as a reference to traverse other positioning beacons in the sub-graph, and the angle between the line connecting each positioning beacon and the starting positioning beacon and the positive direction of the A coordinate axis is calculated; the positioning beacon with the smallest calculated angle is selected as the next starting positioning beacon and added to the boundary set corresponding to the sub-graph until the next starting positioning beacon found is the position of the first starting positioning beacon; the positioning beacons in the boundary set corresponding to the sub-graph are connected to form the boundary outline of the sub-graph. The A coordinate axis can be, but is not limited to, the x-axis, and can also be the y-axis, which can be set as needed.

[0089] The calculation formula of the angle is:

[0090] ; (1)

[0091] in, is the vector from the starting location beacon to the point currently under consideration;

[0092] is a unit vector in the positive direction of the x-axis.

[0093] by Figure 4 For example, Figure 4 c2 is the point with the smallest horizontal coordinate and is used as the first starting positioning beacon. The angle between the line connecting the remaining positioning beacons and c2 and the positive direction of the x-axis is calculated by the above calculation formula (1). The angle between the line connecting c3 to c2 and the positive direction of the A coordinate axis is the smallest. Then c3 is used as the next starting positioning beacon and c3 is a boundary positioning beacon.

[0094] Take c3 as the starting positioning beacon, and calculate the angle between the line connecting the remaining positioning beacons and c3 and the positive direction of the x-axis using the above calculation formula (1). The angle between the line connecting c6 and c11 to c3 and the positive direction of the A coordinate axis is the smallest. Then c11 is used as the next starting positioning beacon, and c6 and c11 are boundary positioning beacons.

[0095] ………And so on, until the next starting positioning beacon is c1.

[0096] Step S500: Generate applicable area ranges corresponding to different positioning technologies according to the calculated boundary contours.

[0097] It should be noted that when the deployment of positioning beacons changes, the applicable area ranges of different positioning technologies can be updated in a timely manner. By accurately identifying the positioning technology that should be used preferentially in each area, the overall accuracy and reliability of the positioning system are improved.

[0098] The method for identifying a positioning area based on beacon deployment information provided by the present invention constructs an undirected graph according to the category of positioning beacons and the physical distance between positioning beacons; performs connectivity analysis on the undirected graph to preliminarily form each connected component into a group; performs cluster analysis on each connected component to form a subgraph according to the deployment density and coverage of the positioning beacons; calculates the outer edges of all positioning beacons included in each subgraph to generate the boundary contour of the subgraph; generates applicable area ranges corresponding to different positioning technologies according to the calculated boundary contour, so that the analysis of positioning beacon data and the identification of positioning areas can be automatically completed without human intervention, thereby greatly reducing labor costs.

[0099] In order to solve the above problems, the present embodiment relates to a positioning method, which can be applied to a computer device. The computer device can be an electronic device with data processing capabilities, such as a desktop computer, a tablet computer, a notebook, etc. In other embodiments, it can also be other electronic devices with data processing capabilities, and no specific restrictions are made here.

[0100] The implementation details of the positioning method according to the first embodiment of the present invention are described below. The following content is only the implementation details provided for the convenience of understanding and is not necessary for implementing this solution.

[0101] The specific process of this implementation is as follows: Figure 5 As shown, specifically including:

[0102] Step S600, using the above-mentioned positioning area identification method based on beacon deployment information to determine the positioning technology corresponding to different areas;

[0103] Step S700: performing positioning according to the positioning technology corresponding to the area.

[0104] In order to achieve the above object, the present invention also provides a positioning area identification device based on beacon deployment information, such as Figure 6 As shown, the positioning area identification device based on beacon deployment information includes a construction unit 810, an analysis unit 820, a clustering unit 830, a calculation unit 840, and an identification unit 850.

[0105] The construction unit 810 is used to construct an undirected graph according to the type of the positioning beacon and the physical distance between the positioning beacons. It should be understood that the positioning beacon is used to accurately determine the position of the target object, and the positioning beacon can be divided into ultra-wideband (UWB) beacons, Bluetooth positioning beacons, etc. according to the type.

[0106] Specifically, for each type of positioning beacons, based on the physical distance between the positioning beacons, the positioning beacon pairs whose physical distance is within the preset coverage range are connected together, and the positioning beacon pairs whose physical distance exceeds the preset range are not connected, so as to form an undirected graph.

[0107] When constructing an undirected graph, a positioning beacon is used as a node of the graph. Taking the positioning beacons including ultra-wideband beacons and Bluetooth positioning beacons as an example, when constructing an undirected graph, ultra-wideband beacon pairs whose physical distances are within the preset coverage range of all ultra-wideband beacons are connected together, and ultra-wideband beacon pairs whose physical distances exceed the preset range are not connected. Bluetooth beacon pairs whose physical distances are within the preset coverage range of all Bluetooth beacons are connected together, and Bluetooth beacon pairs whose physical distances exceed the preset range are not connected.

[0108] For example, ultra-wideband beacons include {A1, A2, A3, ...}, and Bluetooth positioning beacons include {B1, B2, B3, ...}. When constructing an undirected graph, when the physical distance between two nodes in {A1, A2, A3, ...} is within a preset range, the two nodes are connected; when the physical distance between two nodes in {B1, B2, B3, ...} is within a preset range, the two nodes are connected.

[0109] In addition, when the deployment of positioning beacons changes, the applicable area ranges corresponding to different positioning technologies can be updated in a timely manner. Specifically, in response to changes in the deployment of positioning beacons, an undirected graph is constructed according to the types of positioning beacons and the physical distances between positioning beacons.

[0110] The analysis unit 820 is used to perform connectivity analysis on the undirected graph, and preliminarily form each connected component into a group. It should be understood that connectivity analysis is an analysis method for evaluating the degree of connection between nodes in a graph (which can be a variety of network structures such as a geographical network, a communication network, a circuit network, etc.). Its core is to determine whether there is a path from one node to another in the graph, and the characteristics of these paths, such as length, number, etc. The connected component is a maximal connected subgraph of the undirected graph. By performing connectivity analysis on the constructed undirected graph, each connected component is identified. Each connected component is formed into a group, so that the aggregation area of ​​the beacon is preliminarily divided, and the beacons that may physically affect each other are grouped together.

[0111] like Figure 2 As shown, Figure 2 The dotted lines connecting a2 and a5, a4 and a6 are beyond the preset range, so a2 and a5, a4 and a6 cannot be connected. Figure 2 There are other positioning beacon pairs that cannot be connected, such as a3 and a5, which are not listed one by one. Figure 2 The positioning beacons in the graph are divided into two groups, Group 1 and Group 2. The maximum distance is set to separate Group 1 and Group 2 to simulate the coverage relationship of the actual signal and ensure that the graph structure reflects the effective communication range of the positioning beacon.

[0112] The clustering unit 830 is used to perform cluster analysis on each connected component to form a subgraph according to the deployment density and coverage of the positioning beacons. It should be noted that after the connected component identification, only the clustering area of ​​the positioning beacons can be preliminarily divided. There are also some special cases where a small number of positioning beacons may connect multiple groups of positioning beacons into the same group. For example Figure 3 After the connectivity analysis, Figure 3 The location beacons a1 to a8 will form the same group, but in fact the physical distances between the location beacons in {a1, a2, a3, a4} and the location beacons in {a5, a6, a7} are large, and they are not suitable to be connected as a group. Therefore, it is necessary to further cluster each connected component to form a subgraph.

[0113] Further cluster analysis can identify areas with higher density and effectively handle noise points. Figure 3 In the figure, further analysis of this connected component can yield two clusters, cluster 1 and cluster 2. Cluster 1 includes {a1, a2, a3, a4, a8}, and cluster 2 includes {a5, a6, a7}. This can further refine the clustering results and identify more accurate beacon-dense areas.

[0114] The calculation unit 840 is used to calculate the outer edge of all the positioning beacons included in each sub-graph to generate the boundary contour of the sub-graph. Specifically, the positioning beacon with the smallest value of the A coordinate axis in the sub-graph is taken as the starting positioning beacon and added to the boundary set corresponding to the sub-graph; based on the starting positioning beacon, the other positioning beacons in the sub-graph are traversed to calculate the angle between each positioning beacon and the line connecting the starting positioning beacon and the positive direction of the A coordinate axis; the positioning beacon with the smallest calculated angle is selected as the next starting positioning beacon and added to the boundary set corresponding to the sub-graph until the next starting positioning beacon found is the position of the first starting positioning beacon; the positioning beacons in the boundary set corresponding to the sub-graph are connected to form the boundary contour of the sub-graph. The A coordinate axis can be, but is not limited to, the x-axis, and can also be the y-axis, which can be set as needed.

[0115] The calculation formula of the angle is:

[0116] ; (1)

[0117] in, is the vector from the starting location beacon to the point currently under consideration;

[0118] is a unit vector in the positive direction of the x-axis.

[0119] by Figure 4 For example, Figure 4 c2 is the point with the smallest horizontal coordinate and is used as the first starting positioning beacon. The angle between the line connecting the remaining positioning beacons and c2 and the positive direction of the x-axis is calculated by the above calculation formula (1). The angle between the line connecting c3 to c2 and the positive direction of the A coordinate axis is the smallest. Then c3 is used as the next starting positioning beacon and c3 is a boundary positioning beacon.

[0120] Take c3 as the starting positioning beacon, and calculate the angle between the line connecting the remaining positioning beacons and c3 and the positive direction of the x-axis using the above calculation formula (1). The angle between the line connecting c6 and c11 to c3 and the positive direction of the A coordinate axis is the smallest. Then c11 is used as the next starting positioning beacon, and c6 and c11 are boundary positioning beacons.

[0121] ………And so on, until the next starting positioning beacon is c1.

[0122] The identification unit 850 is used to generate applicable area ranges corresponding to different positioning technologies based on the calculated boundary contours. It should be noted that when the positioning beacon deployment changes, the applicable area ranges corresponding to different positioning technologies can be updated in a timely manner. By accurately identifying the positioning technology that should be used preferentially in each area, the overall accuracy and reliability of the positioning system are improved.

[0123] In order to achieve the above object, the present invention also provides a computer device, such as Figure 7 As shown, the computer device includes at least one processor 901; and a memory 902 communicatively connected to the at least one processor 901; wherein the memory 902 stores instructions executable by the at least one processor 901, and the instructions are executed by the at least one processor 901 so that the at least one processor 901 can execute the above-mentioned positioning area identification method based on beacon deployment information, and / or the above-mentioned positioning method.

[0124] Among them, the memory 902 and the processor 901 are connected in a bus manner, and the bus may include any number of interconnected buses and bridges, and the bus connects various circuits of one or more processors 901 and the memory 902 together. The bus can also connect various other circuits such as peripheral devices, voltage regulators, and power management circuits, which are all well known in the art, and therefore, are not further described herein. The bus interface provides an interface between the bus and the transceiver. The transceiver can be one element or multiple elements, such as multiple receivers and transmitters, providing a unit for communicating with various other devices on a transmission medium. The data processed by the processor 901 is transmitted on a wireless medium through an antenna, and further, the antenna also receives data and transmits the data to the processor 901.

[0125] The processor 901 is responsible for managing the bus and general processing, and can also provide various functions, including timing, peripheral interfaces, voltage regulation, power management and other control functions. The memory 902 can be used to store data used by the processor 901 when performing operations.

[0126] In order to achieve the above-mentioned purpose, the present invention provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the above-mentioned positioning area identification method based on beacon deployment information and / or the above-mentioned positioning method.

[0127] That is, those skilled in the art can understand that all or part of the steps in the above-mentioned implementation method can be completed by instructing the relevant hardware through a program, and the program is stored in a storage medium, including several instructions to enable a device (which can be a single-chip microcomputer, chip, etc.) or a processor to execute all or part of the steps of the method described in each implementation of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0128] Obviously, the embodiments described above are only some embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, ordinary technicians in this field can make other different forms of changes or modifications without creative work, which should fall within the scope of protection of the present invention.

Claims

1. A positioning area identification method based on beacon deployment information, characterized in that: include: Construct an undirected graph according to the categories of positioning beacons and the physical distances between positioning beacons; Performing connectivity analysis on the undirected graph, and initially forming each connected component into a group; According to the deployment density and coverage of the positioning beacons, cluster analysis is performed on each connected component to form a subgraph; For all positioning beacons included in each sub-image, calculating the outer edges to generate the boundary contour of the sub-image; Generate applicable area ranges corresponding to different positioning technologies based on the calculated boundary contours; The step of calculating the outer edges of all the positioning beacons included in each sub-graph to generate the boundary contour of the sub-graph comprises: Take the positioning beacon with the smallest A axis value in the sub-graph as the starting positioning beacon and add it to the boundary set corresponding to the sub-graph; Taking the starting positioning beacon as a reference, traverse the other positioning beacons in the subgraph, and calculate the angle between the line connecting each positioning beacon and the starting positioning beacon and the positive direction of the A coordinate axis; Selecting the positioning beacon with the smallest calculated angle as the next starting positioning beacon and adding it to the boundary set corresponding to the subgraph until the next starting positioning beacon found is the position of the first starting positioning beacon; The location beacons in the boundary set corresponding to the sub-graph are connected to form a boundary outline of the sub-graph.

2. The method for identifying a positioning area based on beacon deployment information according to claim 1, characterized in that: The step of constructing an undirected graph according to the type of the positioning beacons and the physical distance between the positioning beacons includes: For each type of positioning beacons, based on the physical distance between the positioning beacons, the positioning beacon pairs with physical distances within the preset coverage range are connected together, and the positioning beacon pairs with physical distances beyond the preset range are not connected, forming an undirected graph.

3. The method for identifying a positioning area based on beacon deployment information according to claim 1, characterized in that: The method of performing cluster analysis on each connected component to form a subgraph according to the deployment density and coverage of the positioning beacon includes: Determine the neighborhood radius and minimum number of sample points based on the deployment density and coverage of positioning beacons; According to the neighborhood radius and the minimum number of sample points, each connected component is clustered to form a subgraph.

4. The method for identifying a positioning area based on beacon deployment information according to claim 3, characterized in that: The step of performing cluster analysis on each connected component to form a subgraph according to the neighborhood radius and the minimum number of sample points includes: For each connected component, take each positioning beacon as the center and count the number of positioning beacons within the neighborhood radius; When the number of positioning beacons is greater than or equal to the minimum number of sample points, the positioning beacon is marked as a core positioning beacon, and the core positioning beacon and the positioning beacons within its neighborhood radius are placed in the corresponding subgraph; When the number of positioning beacons is less than the minimum number of sample points, the positioning beacon is marked as a non-core positioning beacon, and other positioning beacons continue to be used as centers until all core positioning beacons are marked.

5. The method for identifying a positioning area based on beacon deployment information according to claim 1, characterized in that: The step of constructing an undirected graph according to the category of the positioning beacons and the physical distance between the positioning beacons includes: In response to changes in the deployment of the positioning beacons, an undirected graph is constructed according to the categories of the positioning beacons and the physical distances between the positioning beacons; Accordingly, the step of generating applicable area ranges corresponding to different positioning technologies according to the calculated boundary contours includes: According to the calculated boundary contour, the applicable area range corresponding to different positioning technologies is updated.

6. A positioning method, characterized in that: include: Determine the positioning technology corresponding to different areas by using the positioning area identification method based on beacon deployment information as described in any one of claims 1 to 5; Positioning is performed based on the positioning technology corresponding to the area.

7. A positioning area identification device based on beacon deployment information, characterized in that: include: A construction unit, used for constructing an undirected graph according to the categories of the positioning beacons and the physical distances between the positioning beacons; an analysis unit, configured to perform connectivity analysis on the undirected graph and preliminarily form each connected component into a group; A clustering unit, used to perform cluster analysis on each connected component to form a subgraph according to the deployment density and coverage of the positioning beacons; A calculation unit, configured to calculate outer edges of all positioning beacons included in each sub-image to generate a boundary contour of the sub-image; The recognition unit is used to generate applicable area ranges corresponding to different positioning technologies according to the calculated boundary contours; Wherein, the computing unit is further used for: Take the positioning beacon with the smallest A axis value in the sub-graph as the starting positioning beacon and add it to the boundary set corresponding to the sub-graph; Taking the starting positioning beacon as a reference, traverse the other positioning beacons in the subgraph, and calculate the angle between the line connecting each positioning beacon and the starting positioning beacon and the positive direction of the A coordinate axis; Selecting the positioning beacon with the smallest calculated angle as the next starting positioning beacon and adding it to the boundary set corresponding to the subgraph until the next starting positioning beacon found is the position of the first starting positioning beacon; The location beacons in the boundary set corresponding to the sub-graph are connected to form a boundary outline of the sub-graph.

8. A computer device, characterized in that: include: at least one processor; as well as, a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the positioning area identification method based on beacon deployment information as described in any one of claims 1 to 5, and / or the positioning method as described in claim 6.

9. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the positioning area identification method based on beacon deployment information as described in any one of claims 1 to 5 and / or the positioning method as described in claim 6 is implemented.

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