A method, system and related devices for fingerprint-enhanced visible light positioning

Abstract

The application discloses a fingerprint-enhanced visible light positioning method, system and related equipment. The method comprises the following steps: acquiring a first visible light signal intensity group of a to-be-positioned point in a visible light receiving surface of a plurality of visible light sources with power differences, the first visible light signal intensity group comprising a plurality of visible light signal intensities with power differences; determining at least one neighboring point of the to-be-positioned point based on the first visible light signal intensity group; acquiring fingerprint information of each neighboring point from a preset fingerprint library, wherein each neighboring point fingerprint information comprises position information of the neighboring point and a second visible light signal intensity group of the neighboring point, and the second visible light signal intensity group comprises a plurality of visible light signal intensities with power differences; and determining the position of the to-be-positioned point in the visible light receiving surface according to the first visible light signal intensity group and the fingerprint information of the at least one neighboring point. The plurality of visible light sources with power differences make the visible light signal intensity of the to-be-positioned point more unique, thereby effectively improving the positioning accuracy.

Description

Technical Field

[0001] This application relates to the field of Internet technology, and more specifically, to a fingerprint-enhanced visible light positioning method, system, and related equipment. Background Technology

[0002] With the development of internet technology, location services are no longer limited to outdoor environments, and indoor positioning technology has gradually emerged. Indoor positioning services can be applied in many places, such as shopping malls, where they can promptly obtain the location information of counters to facilitate finding goods. Because outdoor positioning technology struggles to provide reliable location data indoors, indoor visible light positioning technology has gradually become the mainstream technology for indoor positioning. In indoor visible light positioning technology, each location point can possess its own "fingerprint," which is the intensity of the visible light signal received from the visible light source.

[0003] Current visible light positioning technology has low positioning accuracy. Summary of the Invention

[0004] In view of this, this application provides a fingerprint-enhanced visible light positioning method, system, and related equipment to solve the problem of low positioning accuracy.

[0005] To achieve the above objectives, the following solution is proposed:

[0006] A fingerprint-enhanced visible light localization method, the fingerprint-enhanced visible light localization method comprising:

[0007] The first visible light signal intensity group of the point to be located is obtained in the visible light receiving surface of multiple visible light sources with different power. The first visible light signal intensity group includes multiple visible light signal intensities with different power.

[0008] Determine at least one neighboring point of the point to be located based on the first visible light signal intensity group;

[0009] The fingerprint information of each neighboring point is obtained from the preset fingerprint database. The fingerprint information of each neighboring point includes: the location information of the neighboring point and the second visible light signal intensity group received by the neighboring point. The second visible light signal intensity group includes multiple visible light signal intensities with different powers.

[0010] The position of the point to be located in the visible light receiving surface is determined based on the first visible light signal intensity group and the fingerprint information of the at least one nearby point.

[0011] Optionally, determining at least one neighboring point of the point to be located based on the first visible light signal intensity group includes:

[0012] At least one neighboring point of the point to be located is determined based on the nearest neighbor algorithm and the first visible light signal intensity group.

[0013] Optionally, determining at least one neighboring point of the point to be located based on the nearest neighbor algorithm and the first visible light signal intensity group includes:

[0014] Obtain the visible light signal intensity group of all positioning points in the visible light receiving surface from the preset fingerprint database;

[0015] Calculate the Euclidean distance between the point to be located and all the positioning points based on the first visible light signal intensity group and the visible light signal intensity group of all the positioning points;

[0016] Based on the Euclidean distance, a preset number of positioning points are selected from all the positioning points as the neighboring points of the point to be positioned, and the Euclidean distance of any of the neighboring points is less than the Euclidean distance of each of the unselected positioning points.

[0017] Optionally, determining the position of the point to be located in the visible light receiving surface based on the first visible light signal intensity group and the fingerprint information of the at least one nearby point includes:

[0018] Calculate the position weights of the target's neighboring points based on the first visible light signal intensity group and the target's second visible light signal intensity group;

[0019] The position of the point to be located in the visible light receiving surface is calculated based on the position weights of the at least one neighboring point and the position information of the at least one neighboring point.

[0020] Optionally, the step of calculating the position weights of the target's neighboring points based on the first visible light signal intensity group and the target's second visible light signal intensity group includes:

[0021] The first visible light intensity of the point to be located is obtained based on the first visible light signal intensity group.

[0022] The target second visible light intensity of the nearby point is obtained based on the target second visible light signal intensity group;

[0023] Calculate the Euclidean distance between the point to be located and the nearby point of the target based on the first visible light intensity and the second visible light intensity of the target.

[0024] The position weights of the target's nearest points are calculated based on the Euclidean distance.

[0025] Optional, also includes:

[0026] The preset fingerprint database is established based on the positioning point information in the visible light receiving surface of the multiple visible light sources with power differences.

[0027] Optionally, establishing the preset fingerprint database based on the positioning point information in the visible light receiving surfaces of the multiple visible light sources with power differences includes:

[0028] The visible light receiving surface is divided into a grid, and each grid node is a positioning point, with each positioning point having its own position information;

[0029] The visible light signal intensity group of the target positioning point is detected multiple times and averaged. The averaged visible light signal intensity group is used as the target visible light signal intensity group of the target positioning point.

[0030] The location information corresponding to each target positioning point and the target visible light signal intensity group corresponding to each target positioning point are stored to obtain the preset fingerprint database.

[0031] A fingerprint-enhanced visible light positioning system, the fingerprint-enhanced visible light positioning system comprising:

[0032] The signal strength acquisition unit is used to acquire a first visible light signal strength group of the point to be located in the visible light receiving surface of multiple visible light sources with different power, wherein the first visible light signal strength group includes multiple visible light signal strengths with different power.

[0033] A proximity point determination unit is used to determine at least one proximity point of the point to be located based on the first visible light signal intensity group.

[0034] The fingerprint acquisition unit is used to acquire fingerprint information of each neighboring point from a preset fingerprint database. The fingerprint information of each neighboring point includes: the location information of the neighboring point and a second visible light signal intensity group received by the neighboring point. The second visible light signal intensity group includes multiple visible light signal intensities with different powers.

[0035] The positioning unit is used to determine the position of the point to be positioned in the visible light receiving surface based on the first visible light signal intensity group and the fingerprint information of the at least one nearby point.

[0036] An electronic device, comprising a memory and a processor;

[0037] The memory is used to store programs;

[0038] The processor is configured to execute the program to implement each step of the fingerprint-enhanced visible light localization method described above.

[0039] A readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of any of the above-described fingerprint-enhanced visible light localization methods.

[0040] This application provides a fingerprint-enhanced visible light positioning method, system, and related equipment. In this method, when obtaining the location of a point to be located, a first group of visible light signal intensities of the point under multiple visible light sources with varying power is used, along with a second group of visible light signal intensities of neighboring points in a preset fingerprint database under multiple visible light sources with varying power. The multiple visible light sources with varying power make the visible light signal intensity of the positioning point more unique, resulting in more obvious fingerprint differences between positioning points, effectively improving the signal-to-noise ratio in indoor environments, and effectively enhancing the positioning accuracy of visible light. Attached Figure Description

[0041] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of this application. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0042] Figure 1 A schematic flowchart illustrating a visible light-based fingerprint-enhanced localization method provided in an embodiment of this application;

[0043] Figure 2 This is a structural schematic diagram of the location of a visible light source provided in an embodiment of this application;

[0044] Figure 3 A schematic diagram of a fingerprint-enhanced visible light positioning system provided in an embodiment of this application;

[0045] Figure 4 This is a hardware structure block diagram of an electronic device provided in an embodiment of this application. Detailed Implementation

[0046] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0047] like Figure 1 As shown in the figure, this application provides a visible light positioning method for fingerprint enhancement, which may include:

[0048] S10. Obtain a first visible light signal intensity group of the point to be located in the visible light receiving surface of multiple visible light sources with different power. The first visible light signal intensity group includes multiple visible light signal intensities with different power.

[0049] The point to be located can be any point on the visible light receiving surface of multiple visible light sources with different power levels. The visible light sources with different power levels can be LEDs (light-emitting diodes) with different power levels, and in this embodiment, there are four. Of course, the specific number can be determined in real-time according to actual positioning needs, and this embodiment does not limit it. The visible light signal intensity group can be composed of multiple visible light signal intensities of different power received by the point to be located; essentially, it can be a vector group composed of multiple visible light signal intensity vectors. Visible light sources of different power emit different visible light signal intensities, resulting in different visible light signal intensities received by the receiving end. Therefore, in this embodiment, four LEDs of different power levels can be used as visible light sources. The point to be located can simultaneously receive different visible light signal intensities from the four LEDs, forming a first light signal intensity group. This first light signal intensity group can serve as a unique fingerprint for the point to be located, distinguishing it from other points on the visible light receiving surface. Figure 2 As shown, four visible light sources A, B, C, and D with different powers are represented. E can be the visible light receiving surface of the four visible light sources, and F can be a point on the visible light receiving surface. Clearly, the visible light signal intensities emitted by the four visible light sources with different powers can be received at point F, forming the first light signal intensity group at point F. This embodiment transforms the visible light positioning problem into a problem of identifying differences in visible light signal intensity, achieving positioning simultaneously with optical signal communication without the need for additional equipment. The optical signal communication can be communication between the visible light source and the receiving end. Specifically, the light signal emitted by the visible light source can carry power information and visible light identification information (used to distinguish the visible light source), and the receiving end can acquire the power information and visible light identification information when receiving the light signal.

[0050] Furthermore, regarding how to determine the power of multiple visible light sources, this embodiment can obtain multiple sets of power values ​​in the MATLAB simulation environment and perform simulations under different sets of power values ​​to obtain a set of power values ​​suitable for positioning. Specifically, this embodiment can first select four visible light sources with identical power, then set the power of the four visible light sources to different preset power differences in sequence, and perform simulations. Finally, select the preset power difference that results in higher positioning accuracy during the simulation, and set the power of the visible light sources according to this preset power difference. Selecting a suitable preset power difference can ensure both the fingerprint enhancement effect at the receiver and increase the signal-to-noise ratio to improve positioning accuracy. For example, four 25W LEDs can be set as the first set of power values, with a preset power difference of 0W; the preset power difference in the second set of power values ​​can be 5W, so the second set of power values ​​can be 18W, 23W, 28W, and 33W; the preset power difference in the third set of power values ​​is 10W, so the third set of power values ​​can be 10W, 20W, 30W, and 40W. Simulations were performed on the three sets of power values, and it was found that the positioning accuracy was higher when the preset power difference was 5W. Therefore, the power of the visible light source can be set according to the preset power difference of 5W.

[0051] During actual simulation, it was found that when the preset power difference value was set too large, low-power visible light could not meet the requirements of optical signal communication, resulting in a large positioning accuracy error. Therefore, in the actual simulation, the positioning errors of multiple power values ​​were compared with the positioning errors of groups with the same power. It was found that using 5W as the power difference value could effectively improve the positioning accuracy.

[0052] S11. Determine at least one neighboring point of the point to be located based on the first visible light signal intensity group.

[0053] In this context, a neighboring point can be a point close to the location of the point to be located, and the location and visible light signal intensity of the neighboring point can be known quantities. There are various ways to determine neighboring points, and this embodiment does not limit the methods. Specifically, in this embodiment, neighboring points can be determined using a first visible light signal intensity group of the point to be located and a group of visible light signal intensities of neighboring points. Optionally, this embodiment can calculate and determine at least one neighboring point of the point to be located based on a nearest neighbor algorithm and the first visible light signal intensity group. Nearest neighbor algorithms can include KNN (K-nearest Neighbor) and WKNN (Weighted K-nearest Neighbor). The general idea of ​​the KNN algorithm is: in the feature space, if most of the K nearest (nearest in feature space) samples around a sample belong to a certain category, then the sample can also belong to that category. The WKNN algorithm can be an algorithm further optimized based on the KNN algorithm. Generally, the greater the distance between the target sample and other samples, the smaller the contribution of other samples to the classification of the target sample. Therefore, the WKNN algorithm can introduce weights in the final result calculation process, which can represent the contribution of other samples to the target sample category determination. This embodiment can obtain at least one neighboring point of the point to be located using either the KNN or WKNN algorithm. Specifically, this embodiment can obtain the visible light signal intensity groups of all positioning points in the visible light receiving surface from a preset fingerprint database. Based on the first visible light signal intensity group and the visible light signal intensity groups of all positioning points, the Euclidean distance between the point to be located and all positioning points is calculated. Based on the Euclidean distance, a preset number of positioning points are selected from all positioning points as neighboring points of the point to be located. The Euclidean distance of any neighboring point is less than the Euclidean distance of any unselected positioning point. The formula for calculating the Euclidean distance can be expressed as:

[0054]

[0055] Where, d i It can be represented as the Euclidean distance of the i-th fingerprint point (nearest point); j can be represented as the j-th visible light source; R j This can be expressed as the visible light signal intensity of the point to be located under the j-th visible light source; R ji It can be expressed as the visible light signal intensity of the i-th fingerprint point under the j-th visible light source.

[0056] After obtaining the Euclidean distances between the point to be located and all other located points in this embodiment, the located points can be sorted in ascending order of Euclidean distance. At least one located point can be selected from the sorted points in ascending order of Euclidean distance, and this at least one located point can be designated as at least one neighbor of the point to be located. Alternatively, the points can be sorted in descending order of Euclidean distance, and a preset number of located points can be selected starting from the end of the sorted points. The preset number can be determined by the K value in the nearest neighbor algorithm. For example, if K is 2, and there are ten located points on the visible light receiving surface, after sorting by Euclidean distance, two points with the smallest Euclidean distance can be selected from the ten sorted points as neighbors of the point to be located.

[0057] S12. Obtain fingerprint information of each neighboring point from the preset fingerprint database. The fingerprint information of each neighboring point includes: the location information of the neighboring point and the second visible light signal intensity group received by the neighboring point. The second visible light signal intensity group includes multiple visible light signal intensities with different powers.

[0058] The preset fingerprint database can be a pre-set fingerprint database that contains fingerprint information of locations on the light-receiving surface. In this embodiment, the preset fingerprint database can be established based on the location information of locations on the visible light receiving surfaces of multiple visible light sources with power differences.

[0059] Specifically, in this embodiment, the visible light receiving surface can be divided into a grid, with each grid node serving as a positioning point, and each positioning point possessing its own location information. This embodiment can repeatedly detect and average the visible light signal intensity groups of the target positioning points, using the averaged visible light signal intensity groups as the target visible light signal intensity groups for the target positioning points. The location information corresponding to each target positioning point and the target visible light signal intensity groups corresponding to each target positioning point are stored to obtain a preset fingerprint database. Of course, the shape of the grid is not limited in this embodiment; it can be rectangular or triangular. In addition to dividing the visible light receiving surface into a grid to obtain positioning points, multiple positioning points can also be directly selected from a representative area of ​​the visible light receiving surface (such as the area directly below the visible light source), with the spacing between the positioning points being exactly the same. This embodiment, by repeatedly measuring the visible light signal intensity of the positioning points and taking the average value, helps to reduce interference from environmental or other factors and improve the accuracy of the positioning point information.

[0060] Therefore, a neighboring point can be a partial location point in the visible light receiving surface grid that is close to the point to be located. The position of the neighboring point can be the position of the neighboring point in the grid. The second visible light signal intensity group of the neighboring point can be composed of multiple visible light signal intensities of different powers received by the neighboring point. In essence, it can be a vector group composed of multiple visible light signal intensity vectors.

[0061] S13. Determine the position of the point to be located in the visible light receiving surface based on the first visible light signal intensity group and the fingerprint information of at least one nearby point.

[0062] In this embodiment, the position of the point to be located can be calculated using the WKNN algorithm. The Euclidean distance between the point and its neighboring points is used as the position weight of each neighboring point. Combining the positions of multiple neighboring points and their corresponding position weights, the position of the point to be located can be calculated. Specifically, this embodiment can calculate the position weights of the target's neighboring points based on a first visible light signal intensity group and a target second visible light signal intensity group. The position of the point to be located within the visible light receiving surface is calculated based on the position weights and position information of at least one neighboring point. Specifically, for the calculation of the position weights, this embodiment obtains the first visible light intensity of the point to be located based on the first visible light signal intensity group, obtains the target second visible light intensity of the target's neighboring points based on the target second visible light signal intensity group, calculates the Euclidean distance between the point to be located and the target's neighboring points based on the first and second visible light intensities, and calculates the position weights of the target's neighboring points based on the Euclidean distances.

[0063] Specifically, the formula for calculating the position of the point to be located can be expressed as:

[0064]

[0065] Where (x,y) can represent the position of the point to be located in the visible light receiving surface; K can represent the specific value of K in the nearest neighbor algorithm; (x i ,y i W can be represented as the position of the i-th fingerprint in the visible light receiving surface; i The weight of the i-th fingerprint can be expressed as:

[0066]

[0067] Where, d i It can be represented as the Euclidean distance of the i-th fingerprint point; K can be represented as the specific value of K in the nearest neighbor algorithm.

[0068] This application provides a fingerprint-enhanced visible light positioning method. In this method, when obtaining the location of a point to be located, a first visible light signal intensity group of the point under multiple visible light sources with power differences and a second visible light signal intensity group of neighboring points in a preset fingerprint database under multiple visible light sources with power differences are used. Multiple visible light sources with power differences make the visible light signal intensity of the positioning point more unique, and the fingerprint differences between positioning points are more obvious, effectively improving the signal-to-noise ratio in indoor environments and effectively improving the positioning accuracy of visible light. Furthermore, the fingerprint-enhanced visible light positioning method in this embodiment can be implemented through a positioning model. By reasonably setting the power differences between visible light sources, the robustness of the positioning model can be effectively improved.

[0069] Corresponding to the fingerprint-enhanced visible light positioning method provided in the embodiments of this application, the embodiments of this application also provide a fingerprint-enhanced visible light positioning system.

[0070] like Figure 3 As shown in the illustration, this application also provides a fingerprint-enhanced visible light positioning system, which may include:

[0071] The signal strength acquisition unit 100 is used to acquire a first visible light signal strength group of the point to be located in the visible light receiving surface of multiple visible light sources with power differences. The first visible light signal strength group includes multiple visible light signal strengths with different powers.

[0072] The nearest point determination unit 110 is used to determine at least one nearest point of the point to be located based on the first visible light signal intensity group;

[0073] The fingerprint acquisition unit 120 is used to acquire fingerprint information of each neighboring point from a preset fingerprint database. The fingerprint information of each neighboring point includes: the location information of the neighboring point and the second visible light signal intensity group received by the neighboring point. The second visible light signal intensity group includes multiple visible light signal intensities with different powers.

[0074] The positioning unit 130 is used to determine the position of the point to be positioned in the visible light receiving surface based on the first visible light signal intensity group and the fingerprint information of at least one nearby point.

[0075] According to another fingerprint-enhanced visible light positioning system provided in the embodiments of this application, Figure 3 The nearest point determination unit 110 shown may include

[0076] The nearest point acquisition sub-unit is used to calculate and determine at least one nearest point of the point to be located based on the nearest neighbor algorithm and the first visible light signal intensity group.

[0077] In another fingerprint-enhanced visible light positioning system provided according to an embodiment of this application, the aforementioned nearest point acquisition subunit may include:

[0078] The positioning point information acquisition subunit is used to acquire the visible light signal intensity group of all positioning points in the visible light receiving surface from the preset fingerprint database;

[0079] The Euclidean distance calculation subunit is used to calculate the Euclidean distance between the point to be located and all other positioning points based on the first visible light signal intensity group and the visible light signal intensity group of all positioning points.

[0080] The nearest point selection subunit is used to select a preset number of positioning points from all positioning points as nearest points of the point to be positioned based on the Euclidean distance. The Euclidean distance of any nearest point is less than the Euclidean distance of any unselected positioning point.

[0081] According to another fingerprint-enhanced visible light positioning system provided in the embodiments of this application, Figure 3 The positioning unit 130 shown may include:

[0082] The weight acquisition subunit is used to calculate the position weights of nearby points of the target based on the first visible light signal intensity group and the second visible light signal intensity group of the target.

[0083] The position calculation subunit is used to calculate the position of the point to be located in the visible light receiving surface based on the position weight of at least one neighboring point and the position information of at least one neighboring point.

[0084] In another fingerprint-enhanced visible light positioning system provided according to an embodiment of this application, the aforementioned weight acquisition subunit may include:

[0085] The first visible light intensity acquisition subunit is used to obtain the first visible light intensity of the point to be located based on the first visible light signal intensity group.

[0086] The second visible light intensity acquisition subunit is used to obtain the target second visible light intensity of the target's neighboring point based on the target's second visible light signal intensity group;

[0087] The Euclidean distance acquisition unit is used to calculate the Euclidean distance between the point to be located and the nearby point of the target based on the first visible light intensity and the second visible light intensity of the target.

[0088] The position weight calculation subunit is used to calculate the position weights of the target's nearest points based on Euclidean distance.

[0089] In another fingerprint-enhanced visible light positioning system provided according to an embodiment of this application, the system may further include:

[0090] The fingerprint database establishment unit is used to establish a preset fingerprint database based on the positioning point information in the visible light receiving surface of multiple visible light sources with power differences.

[0091] In another fingerprint-enhanced visible light positioning system provided according to an embodiment of this application, the fingerprint database establishment unit may include:

[0092] Mesh division sub-units are used to divide the visible light receiving surface into a mesh, where each mesh node is a positioning point and each positioning point has its own position information;

[0093] The averaging sub-unit is used to detect the visible light signal intensity group of the target positioning point multiple times and perform averaging processing, and use the averaged visible light signal intensity group as the target visible light signal intensity group of the target positioning point.

[0094] The data storage subunit is used to store the location information corresponding to each target positioning point and the target visible light signal intensity group corresponding to each target positioning point to obtain a preset fingerprint database.

[0095] like Figure 4 As shown, this application provides an electronic device 70, including at least one processor 701, at least one memory 702 connected to the processor 701, and a bus 703; wherein the processor 701 and the memory 702 communicate with each other through the bus 703; the processor 701 is used to call program instructions in the memory 702 to execute the above-described fingerprint-enhanced visible light positioning method. The electronic device 70 in this document can be a server, PC, PAD, mobile phone, etc.

[0096] This application also provides a readable storage medium storing a computer program thereon. When the computer program is executed by a processor, it implements each step of any of the above-described fingerprint-enhanced visible light positioning methods.

[0097] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0098] In a typical configuration, the device includes one or more processors (CPUs), memory, and a bus. The device may also include input / output interfaces, network interfaces, etc.

[0099] Memory may include non-persistent memory in computer-readable storage media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM, and memory includes at least one memory chip. Memory is an example of a computer-readable medium.

[0100] Computer-readable storage media include both permanent and non-permanent, removable and non-removable media that can store information by any method or technology. Information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0101] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0102] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes the element.

[0103] The various embodiments in this specification are described in a related manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the apparatus embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions of the method embodiments.

[0104] The above are merely embodiments of this application and are not intended to limit the scope of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.

Claims

1. A visible light-based fingerprint localization method, characterized in that, The fingerprint-enhanced visible light localization method includes: The first visible light signal intensity group of the point to be located is obtained in the visible light receiving surface of multiple visible light sources with different power. The first visible light signal intensity group includes multiple visible light signal intensities with different power. Determine at least one neighboring point of the point to be located based on the first visible light signal intensity group; The fingerprint information of each neighboring point is obtained from the preset fingerprint database. The fingerprint information of each neighboring point includes: the location information of the neighboring point and the second visible light signal intensity group received by the neighboring point. The second visible light signal intensity group includes multiple visible light signal intensities with different powers. The position of the point to be located in the visible light receiving surface is determined based on the first visible light signal intensity group and the fingerprint information of the at least one nearby point.

2. The visible light positioning method for fingerprint enhancement according to claim 1, characterized in that, Determining at least one neighboring point of the point to be located based on the first visible light signal intensity group includes: At least one neighboring point of the point to be located is determined based on the nearest neighbor algorithm and the first visible light signal intensity group.

3. The visible light positioning method for fingerprint enhancement according to claim 2, characterized in that, The step of determining at least one neighboring point of the point to be located based on the nearest neighbor algorithm and the first visible light signal intensity group includes: Obtain the visible light signal intensity group of all positioning points in the visible light receiving surface from the preset fingerprint database; Calculate the Euclidean distance between the point to be located and all the positioning points based on the first visible light signal intensity group and the visible light signal intensity group of all the positioning points; Based on the Euclidean distance, a preset number of positioning points are selected from all the positioning points as the neighboring points of the point to be positioned, and the Euclidean distance of any of the neighboring points is less than the Euclidean distance of each of the unselected positioning points.

4. The visible light positioning method for fingerprint enhancement according to claim 1, characterized in that, Determining the position of the point to be located in the visible light receiving surface based on the first visible light signal intensity group and the fingerprint information of the at least one nearby point includes: Calculate the position weights of the target's neighboring points based on the first visible light signal intensity group and the target's second visible light signal intensity group; The position of the point to be located in the visible light receiving surface is calculated based on the position weights of the at least one neighboring point and the position information of the at least one neighboring point.

5. The visible light positioning method for fingerprint enhancement according to claim 4, characterized in that, The step of calculating the position weights of nearby points of the target based on the first visible light signal intensity group and the second visible light signal intensity group of the target includes: The first visible light intensity of the point to be located is obtained based on the first visible light signal intensity group. The target second visible light intensity of the nearby point is obtained based on the target second visible light signal intensity group; Calculate the Euclidean distance between the point to be located and the nearby point of the target based on the first visible light intensity and the second visible light intensity of the target. The position weights of the target's nearest points are calculated based on the Euclidean distance.

6. The visible light positioning method for fingerprint enhancement according to claim 1, characterized in that, Also includes: The preset fingerprint database is established based on the positioning point information in the visible light receiving surface of the multiple visible light sources with power differences.

7. The visible light positioning method for fingerprint enhancement according to claim 6, characterized in that, The step of establishing the preset fingerprint database based on the positioning point information in the visible light receiving surfaces of the multiple visible light sources with power differences includes: The visible light receiving surface is divided into a grid, and each grid node is a positioning point, with each positioning point having its own position information; The visible light signal intensity group of the target positioning point is detected multiple times and averaged. The averaged visible light signal intensity group is used as the target visible light signal intensity group of the target positioning point. The location information corresponding to each target positioning point and the target visible light signal intensity group corresponding to each target positioning point are stored to obtain the preset fingerprint database.

8. A fingerprint-enhanced visible light positioning system, characterized in that, The fingerprint-enhanced visible light positioning system includes: The signal strength acquisition unit is used to acquire a first visible light signal strength group of the point to be located in the visible light receiving surface of multiple visible light sources with different power, wherein the first visible light signal strength group includes multiple visible light signal strengths with different power. A proximity point determination unit is used to determine at least one proximity point of the point to be located based on the first visible light signal intensity group. The fingerprint acquisition unit is used to acquire fingerprint information of each neighboring point from a preset fingerprint database. The fingerprint information of each neighboring point includes: the location information of the neighboring point and a second visible light signal intensity group received by the neighboring point. The second visible light signal intensity group includes multiple visible light signal intensities with different powers. The positioning unit is used to determine the position of the point to be positioned in the visible light receiving surface based on the first visible light signal intensity group and the fingerprint information of the at least one nearby point.

9. An electronic device, characterized in that, Including memory and processor; The memory is used to store programs; The processor is configured to execute the program to implement the steps of the visible light positioning method for fingerprint enhancement as described in any one of claims 1-7.

10. A readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the visible light localization method for fingerprint enhancement as described in any one of claims 1-7.

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