CN109831737B - Bluetooth positioning method, device, equipment and system based on confidence degree - Google Patents
Bluetooth positioning method, device, equipment and system based on confidence degree Download PDFInfo
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Abstract
The invention discloses a Bluetooth positioning method based on confidence coefficient, which comprises the following steps: acquiring the detected Bluetooth signals of a plurality of Bluetooth nodes within preset time; searching a corresponding adjacent node group which is divided in advance according to the detected Bluetooth signal of each Bluetooth node; taking the ratio of the number of the adjacent nodes which can be detected with Bluetooth signals in the adjacent node group to the number of the adjacent nodes in the adjacent node group as the confidence of the current Bluetooth node; and calculating the weight of the Bluetooth node according to the detected Bluetooth signal intensity and the confidence coefficient of the Bluetooth node, and calculating a positioning coordinate according to the weight of the Bluetooth node. The embodiment of the invention also discloses a Bluetooth positioning device, equipment and a system based on the confidence coefficient. By adopting the embodiment of the invention, the accuracy and the usability can be improved, the requirement of training a database by acquiring data in the early stage is eliminated, and the cost is reduced.
Description
Technical Field
The present invention relates to bluetooth positioning technologies, and in particular, to a bluetooth positioning method, apparatus, device, and system based on confidence.
Background
With the rapid development of cities, large buildings such as large underground parking lots and shopping centers are emerging continuously. In the indoor environment, it is desirable to quickly determine the location of the user and find a desired destination. The Bluetooth positioning technology based on confidence coefficient adopted in the prior art comprises the following two technologies, one is that the relation between the signal intensity and the actual distance is established directly by some mapping modes such as fitting and the like after the intelligent terminal acquires the signal intensity value of the Bluetooth node on line; and the other two methods are that fingerprint vector data of the intelligent terminal offline Bluetooth module are stored to obtain fingerprint-position mapping database resources during training, when the intelligent terminal offline Bluetooth module is used, the acquired fingerprint vectors are compared with each fingerprint vector in the fingerprint data resources by the intelligent terminal online module, and a reference position with higher proximity is selected as a sample position for fusion output.
However, with the first scheme, since the signal intensity is greatly influenced by environmental factors (such as temperature, humidity and physical shielding), the actual distance value calculated by the first scheme is also extremely unstable and inaccurate; for the second scheme, the sample acquisition cost is very high when the database is trained, and any indoor scene change/reparation can cause the fingerprint database in the area to be invalid, and acquisition training needs to be performed again, so that the cost is increased.
Disclosure of Invention
The embodiment of the invention aims to provide a Bluetooth positioning method, device, equipment and system based on confidence coefficient, which do not need to directly fit the relationship between signal intensity and actual distance, improve the accuracy and the usability, avoid the requirement of training a database by acquiring data at the early stage and reduce the cost.
In order to achieve the above object, an embodiment of the present invention provides a bluetooth positioning method based on confidence, including:
acquiring the detected Bluetooth signals of a plurality of Bluetooth nodes within preset time; the Bluetooth signal is greater than the preset signal intensity;
searching a corresponding adjacent node group which is divided in advance according to the detected Bluetooth signal of each Bluetooth node; the adjacent node group takes any Bluetooth node as a central node and comprises the central node and a plurality of adjacent nodes in a preset range of the central node;
taking the ratio of the number of the adjacent nodes which can be detected with Bluetooth signals in the adjacent node group to the number of the adjacent nodes in the adjacent node group as the confidence of the current Bluetooth node;
and calculating the weight of the Bluetooth node according to the detected Bluetooth signal intensity and the confidence coefficient of the Bluetooth node, and calculating a positioning coordinate according to the weight of the Bluetooth node.
Compared with the prior art, the Bluetooth positioning method based on confidence coefficient disclosed by the invention comprises the following steps of firstly, acquiring the detected Bluetooth signals of a plurality of Bluetooth nodes in preset time, and searching the corresponding pre-divided adjacent node groups according to the detected Bluetooth signal of each Bluetooth node; then, obtaining the confidence of the Bluetooth node; and finally, calculating the weight of the Bluetooth node according to the detected Bluetooth signal intensity and confidence of the Bluetooth node, and calculating a positioning coordinate according to the weight of the Bluetooth node. The method solves the problem that the actual distance value calculated due to the influence of environmental factors is inaccurate in the prior art, and also solves the problem that the cost is increased due to the fact that data needs to be acquired in the early stage.
As an improvement of the above scheme, each of the bluetooth nodes transmits bluetooth signals with the same signal strength according to the same period.
As an improvement of the above scheme, the bluetooth node is arranged in the passable area; the passable area is divided into a plurality of square areas with the same size, and the Bluetooth nodes are arranged on four nodes of each square area.
As an improvement of the above scheme, the calculating a location coordinate according to the weight of the bluetooth node specifically includes:
and calculating the positioning coordinate according to the weight of the Bluetooth node and the coordinate vector of the Bluetooth node.
In order to achieve the above object, an embodiment of the present invention further provides a bluetooth positioning apparatus based on confidence, including:
the signal detection unit is used for acquiring the detected Bluetooth signals of the plurality of Bluetooth nodes within preset time; the Bluetooth signal is greater than the preset signal intensity;
the adjacent node group searching unit is used for searching a corresponding adjacent node group which is divided in advance according to the detected Bluetooth signal of each Bluetooth node; the adjacent node group takes any Bluetooth node as a central node and comprises the central node and a plurality of adjacent nodes in a preset range of the central node;
a confidence coefficient obtaining unit, configured to obtain a ratio of the number of neighboring nodes in the neighboring node group, where a bluetooth signal can be detected, to the number of neighboring nodes in the neighboring node group, as a confidence coefficient of the current bluetooth node;
and the positioning coordinate calculation unit is used for calculating the weight of the Bluetooth node according to the detected Bluetooth signal intensity and the confidence coefficient of the Bluetooth node and calculating the positioning coordinate according to the weight of the Bluetooth node.
Compared with the prior art, the Bluetooth positioning device based on confidence coefficient disclosed by the invention comprises the following steps that firstly, a signal detection unit acquires the detected Bluetooth signals of a plurality of Bluetooth nodes in preset time, and an adjacent node group searching unit searches corresponding adjacent node groups which are divided in advance according to the detected Bluetooth signal of each Bluetooth node; then, the confidence coefficient obtaining unit obtains the confidence coefficient of the Bluetooth node; and finally, the positioning coordinate calculation unit calculates the weight of the Bluetooth node according to the detected Bluetooth signal strength and confidence of the Bluetooth node, and calculates the positioning coordinate according to the weight of the Bluetooth node. The problem that the actual distance value calculated due to the influence of environmental factors is inaccurate in the prior art is solved, and the problem that the cost is increased due to the fact that data needs to be collected in the early stage is also solved.
As an improvement of the above scheme, the location coordinate calculation unit is configured to calculate the location coordinate according to the weight of the bluetooth node and the coordinate vector of the bluetooth node.
In order to achieve the above object, an embodiment of the present invention further provides a confidence-based bluetooth positioning apparatus, which is characterized by comprising a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor, when executing the computer program, implements the confidence-based bluetooth positioning method according to any of the above embodiments.
In order to achieve the above object, an embodiment of the present invention further provides a bluetooth positioning system based on confidence, including a plurality of bluetooth nodes and the bluetooth positioning apparatus based on confidence as described in any of the above embodiments; the Bluetooth node is arranged in the passable area; the passable area is divided into a plurality of square areas with the same size, and the Bluetooth nodes are arranged on four nodes of each square area; and each Bluetooth node sends Bluetooth signals with the same signal strength according to the same period.
Drawings
Fig. 1 is a flowchart of a bluetooth positioning method based on confidence level according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of a bluetooth positioning apparatus 10 based on confidence level according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of a bluetooth positioning apparatus 20 based on confidence level according to an embodiment of the present invention;
fig. 4 is a schematic structural diagram of a bluetooth positioning system 30 based on confidence level according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Example one
Referring to fig. 1, fig. 1 is a flowchart of a bluetooth positioning method based on confidence level according to an embodiment of the present invention; the method comprises the following steps:
s1, acquiring the detected Bluetooth signals of a plurality of Bluetooth nodes within preset time; the Bluetooth signal is greater than the preset signal intensity;
s2, searching a corresponding pre-divided adjacent node group according to the detected Bluetooth signal of each Bluetooth node; the adjacent node group takes any Bluetooth node as a central node and comprises the central node and a plurality of adjacent nodes in a preset range of the central node;
s3, taking the ratio of the number of the adjacent nodes which can be detected with Bluetooth signals in the adjacent node group to the number of the adjacent nodes in the adjacent node group as the confidence of the current Bluetooth node;
s4, calculating the weight of the Bluetooth node according to the detected Bluetooth signal intensity and the confidence coefficient of the Bluetooth node, and calculating the positioning coordinate according to the weight of the Bluetooth node.
It should be noted that the bluetooth positioning method based on confidence level according to the embodiment of the present invention may be implemented by a mobile terminal, and the mobile terminal may be a mobile phone, a tablet computer, or another mobile terminal capable of implementing a positioning function. In the embodiment of the invention, a plurality of Bluetooth nodes are arranged in a certain passable area and used for transmitting Bluetooth signals, each Bluetooth node transmits signals according to the same periodicity, and the transmitted signals have equal strength; the passable area is divided into a plurality of square areas with the same size, and the Bluetooth nodes are arranged on four nodes of each square area. When a user holds the mobile terminal by hand and enters the signal range of the Bluetooth node, the positioning function can be started to be realized.
The effective radius of coverage of the bluetooth module of chooseing for use is 10 meters, and intensity is more stable along with the rule of distance decay in the within range of m (m is 5), and if the distance exceeds the scope, the precision of distinguishing of distance will reduce. For realizing the location of the precision for the meter level, arrange bluetooth module on 4 summits in the big square region of 25 square meters, when expanding the location area, only need expand a plurality of squares according to unilateral coincidence mode. Thus, within the feasible area planned in advance, four bluetooth nodes can cover each square area with the size of 25 square meters. If the area of the communication area is less than 25 square meters, the minimum distance m between the Bluetooth nodes can be properly adjusted, so that the Bluetooth nodes are uniformly distributed on the periphery as much as possible to wrap the core area.
Specifically, in step S1, bluetooth signals of a plurality of detected bluetooth nodes are acquired within a preset time; the Bluetooth signal is greater than the preset signal intensity; preferably, the preset time may be 2 s. When the positioning program is started, the Bluetooth nodes enter an area covered by the Bluetooth nodes, firstly, the signal intensity of a plurality of Bluetooth nodes collected in the latest 2s is counted, and the Bluetooth nodes with the signal intensity larger than the preset signal intensity are screened out.
Specifically, in step S2, according to the detected bluetooth signal of each bluetooth node, a corresponding pre-divided adjacent node group is searched; the adjacent node group takes any Bluetooth node as a central node and comprises the central node and a plurality of adjacent nodes in a preset range of the central node. After the Bluetooth nodes are arranged, each independent node is taken as a central node, and adjacent Bluetooth nodes in a preset range are counted and classified into an adjacent node group. Preferably, the preset range may be 10 m.
Specifically, in step S3, if the mobile phone terminal is located near a certain bluetooth node, then there is a high probability that neighboring nodes around the current bluetooth node are received; if the current bluetooth node is far away from the mobile phone terminal, only because the system error is accidentally detected, the probability that the neighboring nodes around the current bluetooth node are simultaneously received is very low, the confidence coefficient is also small, and even under the extreme condition that the corresponding neighboring node is not detected, the confidence coefficient with the numerical value of 0 is obtained.
Preferably, the formula of the confidence coefficient satisfies:
wherein, confidenceiRepresenting the confidence of the current Bluetooth node (each Bluetooth node can be used as the central node, namely each Bluetooth node has its corresponding adjacent node group, i represents the ith Bluetooth node and also represents the ith adjacent node group); n represents the number of the adjacent nodes of which the Bluetooth signals are detected in the adjacent node group corresponding to the current Bluetooth node, wherein the Bluetooth signals are greater than the preset signal intensity; and N represents the number of the adjacent nodes in the adjacent node group corresponding to the current Bluetooth node.
It should be noted that, in the actual operation process, any detected bluetooth node respectively calculates the number of neighboring nodes within the preset range (the number of neighboring nodes detecting bluetooth signals is calculated at this time), and compares the number with the preset number of neighboring nodes in the installation scheme (the number of neighboring nodes inherent to a bluetooth node is calculated and prestored at this time), and the higher the matching degree is, the higher the confidence of the bluetooth node is.
Specifically, in step S4, after the confidence level of the current neighboring node group is established, more detailed positioning coordinates need to be determined in the area, and it is natural to refer to the bluetooth node with the highest signal strength in the neighboring node group, and consider that the bluetooth node to which the mobile terminal should be closest has the highest confidence level. However, for higher robustness, the roles of other bluetooth nodes cannot be ignored, different confidences are given to the remaining other bluetooth nodes according to the difference between the signal strength of the other bluetooth nodes and the highest strength, a gaussian curve is used to simulate the rule, assuming that the signal strength of each bluetooth node is Ri (i ═ 1, 2, 3 …), the maximum value max (Ri) is taken as the expected μ of a normal distribution N (Ri, μ, δ), and the variance is δ, preferably, the variance δ can be 10, so that bluetooth nodes with signal strength differences within 10db can still obtain higher confidences, and the weight calculation method of each bluetooth node is as follows:
after the weight of each Bluetooth node is obtained, calculating the positioning coordinate according to the weight of the Bluetooth node and the coordinate vector of the Bluetooth node, and then estimating the positioning coordinate as follows:
X＝∑i Pi*Xiformula (3);
wherein, XiA coordinate vector representing the ith bluetooth node.
Furthermore, positioning is performed by adopting the adjacent node group matching, so that the positioning accuracy is greatly improved, but if the motion information characteristic of the mobile terminal can be obtained, the motion information characteristic of the mobile terminal and the position estimation based on signal intensity measurement can be linearly fitted through a Kalman filtering algorithm, and the estimation of the motion state of the user at the current moment can be further perfected.
In specific implementation, firstly, the detected Bluetooth signals of a plurality of Bluetooth nodes are acquired within preset time, and corresponding adjacent node groups which are divided in advance are searched according to the detected Bluetooth signals of each Bluetooth node; then, obtaining the confidence of the Bluetooth node; and finally, calculating the weight of the Bluetooth node according to the detected Bluetooth signal strength and confidence of each Bluetooth node, and calculating a positioning coordinate according to the weight of the Bluetooth node.
Compared with the prior art, the Bluetooth positioning method based on the confidence coefficient solves the problem that the actual distance value calculated is inaccurate due to the influence of environmental factors in the prior art, and also solves the problem that the cost is increased due to the need of acquiring data in the early stage.
Example two
Referring to fig. 2, fig. 2 is a schematic structural diagram of a bluetooth positioning apparatus 10 based on confidence level according to an embodiment of the present invention; the method comprises the following steps:
the signal detection unit 11 is configured to acquire the detected bluetooth signals of the plurality of bluetooth nodes within a preset time; the Bluetooth signal is greater than the preset signal intensity;
an adjacent node group searching unit 12, configured to search a corresponding adjacent node group that is pre-divided according to the detected bluetooth signal of each bluetooth node; the adjacent node group takes any Bluetooth node as a central node and comprises the central node and a plurality of adjacent nodes in a preset range of the central node;
a confidence obtaining unit 13, configured to obtain a ratio of the number of neighboring nodes in the neighboring node group, where a bluetooth signal can be detected, to the number of neighboring nodes in the neighboring node group, as a confidence of the current bluetooth node;
and the positioning coordinate calculation unit 14 is configured to calculate a weight of the bluetooth node according to the detected bluetooth signal strength of the bluetooth node and the confidence, and calculate a positioning coordinate according to the weight of the bluetooth node.
It should be noted that the bluetooth positioning apparatus 10 based on confidence level according to the embodiment of the present invention may be a mobile terminal, and the mobile terminal may be a mobile phone, a tablet computer, or another mobile terminal capable of implementing a positioning function. In the embodiment of the invention, a plurality of Bluetooth nodes are arranged in a certain passable area and used for transmitting Bluetooth signals, each Bluetooth node transmits signals according to the same periodicity, and the transmitted signals have equal strength; the passable area is divided into a plurality of square areas with the same size, and the Bluetooth nodes are arranged on four nodes of each square area. When a user holds the mobile terminal by hand and enters the signal range of the Bluetooth node, the positioning function can be started to be realized.
The effective radius of coverage of the bluetooth module of chooseing for use is 10 meters, and intensity is more stable along with the rule of distance decay in the within range of m (m is 5), and if the distance exceeds the scope, the precision of distinguishing of distance will reduce. For realizing the location of the precision for the meter level, arrange bluetooth module on 4 summits in the big square region of 25 square meters, when expanding the location area, only need expand a plurality of squares according to unilateral coincidence mode. Thus, within the feasible area planned in advance, four bluetooth nodes can cover each square area with the size of 25 square meters. If the area of the communication area is less than 25 square meters, the minimum distance m between the Bluetooth nodes can be properly adjusted, so that the Bluetooth nodes are uniformly distributed on the periphery as much as possible to wrap the core area.
Specifically, the signal detection unit 11 acquires bluetooth signals of a plurality of detected bluetooth nodes within a preset time; the Bluetooth signal is greater than the preset signal intensity; preferably, the preset time may be 2 s. When the positioning program is opened, the bluetooth nodes enter an area covered by the bluetooth nodes, the signal detection unit 11 first counts the signal intensity of a plurality of bluetooth nodes collected in the latest 2s, and selects the bluetooth nodes with the signal intensity greater than the preset signal intensity.
Specifically, the adjacent node group searching unit 12 searches for a corresponding adjacent node group divided in advance according to the detected bluetooth signal of each bluetooth node; the adjacent node group takes any Bluetooth node as a central node and comprises the central node and a plurality of adjacent nodes in a preset range of the central node. After the Bluetooth nodes are arranged, each independent node is taken as a central node, and adjacent Bluetooth nodes in a preset range are counted and classified into an adjacent node group. Preferably, the preset range may be 10 m.
Specifically, if the mobile phone terminal is located near a certain bluetooth node, then neighboring nodes around the current bluetooth node are also received with a high probability; if the current bluetooth node is far away from the mobile phone terminal, only because the system error is accidentally detected, the probability that the neighboring nodes around the current bluetooth node are simultaneously received is very low, the confidence coefficient is also small, and even under the extreme condition that the corresponding neighboring node is not detected, the confidence coefficient with the numerical value of 0 is obtained.
The confidence coefficient obtaining unit 13 takes the ratio of the number of the neighboring nodes in the neighboring node group, where the bluetooth signal can be detected, to the number of the neighboring nodes in the neighboring node group as the confidence coefficient of the current bluetooth node, where the above process satisfies the following formula:
wherein, confidenceiRepresenting the confidence of the current Bluetooth node (each Bluetooth node can be used as the central node, namely each Bluetooth node has its corresponding adjacent node group, i represents the ith Bluetooth node and also represents the ith adjacent node group); n represents the number of the adjacent nodes of which the Bluetooth signals are detected in the adjacent node group corresponding to the current Bluetooth node, wherein the Bluetooth signals are greater than the preset signal intensity; and N represents the number of the adjacent nodes in the adjacent node group corresponding to the current Bluetooth node.
It should be noted that, in the actual operation process, any detected bluetooth node respectively calculates the number of neighboring nodes within the preset range (the number of neighboring nodes detecting bluetooth signals is calculated at this time), and compares the number with the preset number of neighboring nodes in the installation scheme (the number of neighboring nodes inherent to a bluetooth node is calculated and prestored at this time), and the higher the matching degree is, the higher the confidence of the bluetooth node is.
Specifically, after the confidence level of the current neighboring node group is established, more detailed positioning coordinates need to be determined in the area, and it is natural to refer to the bluetooth node with the highest signal strength in the neighboring node group, and consider that the bluetooth node to which the mobile terminal should be closest has the highest confidence level. However, for higher robustness, the roles of other bluetooth nodes cannot be ignored, different confidences are given to the remaining other bluetooth nodes according to the difference between the signal strength of the other bluetooth nodes and the highest strength, a gaussian curve is used to simulate the rule, assuming that the signal strength of each bluetooth node is Ri (i ═ 1, 2, 3 …), the maximum value max (Ri) is taken as the expected μ of a normal distribution N (Ri, μ, δ), and the variance is δ, preferably, the variance δ can be 10, so that bluetooth nodes with signal strength differences within 10db can still obtain higher confidences, and the weight calculation method of each bluetooth node is as follows:
after obtaining the weight of each bluetooth node, the coordinate calculation unit 14 calculates the positioning coordinate according to the weight of the bluetooth node and the coordinate vector of the bluetooth node, and then the estimated positioning coordinate is:
X＝∑i Pi*Xiformula (3);
wherein, XiA coordinate vector representing the ith bluetooth node.
Furthermore, positioning is performed by adopting the adjacent node group matching, so that the positioning accuracy is greatly improved, but if the motion information characteristic of the mobile terminal can be obtained, the motion information characteristic of the mobile terminal and the position estimation based on signal intensity measurement can be linearly fitted through a Kalman filtering algorithm, and the estimation of the motion state of the user at the current moment can be further perfected.
In specific implementation, firstly, the signal detection unit 11 acquires the detected bluetooth signals of a plurality of bluetooth nodes within a preset time, and the adjacent node group search unit 12 searches a corresponding adjacent node group which is divided in advance according to the detected bluetooth signal of each bluetooth node; then, the confidence coefficient obtaining unit 13 obtains the confidence coefficient of the bluetooth node; finally, the positioning coordinate calculation unit 14 calculates the weight of the bluetooth node according to the detected bluetooth signal strength and confidence of each bluetooth node, and calculates the positioning coordinate according to the weight of the bluetooth node.
Compared with the prior art, the Bluetooth positioning device 10 based on the confidence coefficient solves the problem that the actual distance value calculated is inaccurate due to the influence of environmental factors in the prior art, and also solves the problem that the cost is increased due to the need of acquiring data in the early stage.
EXAMPLE III
Referring to fig. 3, fig. 3 is a schematic structural diagram of a bluetooth positioning apparatus 20 based on confidence level according to an embodiment of the present invention; the confidence-based bluetooth positioning apparatus 20 of this embodiment includes: a processor 21, a memory 22 and a computer program stored in said memory 22 and executable on said processor 21. The processor 21, when executing the computer program, implements the steps of the above-mentioned embodiments of the bluetooth location method based on confidence level, such as steps S1 to S4 shown in fig. 1. Alternatively, the processor 21, when executing the computer program, implements the functions of the modules/units in the above-mentioned device embodiments, such as the signal detection unit 11.
Illustratively, the computer program may be divided into one or more modules/units, which are stored in the memory 22 and executed by the processor 21 to accomplish the present invention. The one or more modules/units may be a series of computer program instruction segments capable of performing specific functions, which are used to describe the execution of the computer program in the confidence-based bluetooth positioning apparatus 20. For example, the computer program may be divided into a signal detection unit 11, an adjacent node group search unit 12, a confidence level obtaining unit 13, and a positioning coordinate calculation unit 14, and for specific functions of each module, reference is made to specific functions of each unit of the bluetooth positioning apparatus 10 based on confidence level in the second embodiment, which are not described herein again.
The confidence-based bluetooth positioning device 20 may be a desktop computer, a notebook, a palm top computer, a cloud server, or other computing devices. The confidence-based bluetooth positioning apparatus 20 may include, but is not limited to, a processor 21, a memory 22. Those skilled in the art will appreciate that the schematic diagram is merely an example of the confidence based bluetooth locating device 20 and does not constitute a limitation of the confidence based bluetooth locating device 20 and may include more or less components than shown, or some components in combination, or different components, for example, the confidence based bluetooth locating device 20 may also include an input output device, a network access device, a bus, etc.
The Processor 21 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components, etc. The general purpose processor may be a microprocessor or the processor may be any conventional processor or the like that is the control center for the confidence-based bluetooth positioning apparatus 20, with various interfaces and lines connecting the various parts of the overall confidence-based bluetooth positioning apparatus 20.
The memory 22 may be used to store the computer programs and/or modules, and the processor 21 may implement the various functions of the confidence-based bluetooth positioning apparatus 20 by running or executing the computer programs and/or modules stored in the memory 22 and invoking the data stored in the memory 22. The memory 22 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application program required by at least one function (such as a sound playing function, an image playing function, etc.), and the like; the storage data area may store data (such as audio data, a phonebook, etc.) created according to the use of the cellular phone, and the like. In addition, the memory 22 may include high speed random access memory, and may also include non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), at least one magnetic disk storage device, a Flash memory device, or other volatile solid state storage device.
Wherein the modules/units integrated with the bluetooth positioning apparatus 20 based on confidence level may be stored in a computer readable storage medium if implemented in the form of software functional units and sold or used as independent products. Based on such understanding, all or part of the flow of the method according to the above embodiments may be implemented by a computer program, which may be stored in a computer readable storage medium and used by the processor 21 to implement the steps of the above embodiments of the method. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution medium, and the like. It should be noted that the computer readable medium may contain content that is subject to appropriate increase or decrease as required by legislation and patent practice in jurisdictions, for example, in some jurisdictions, computer readable media does not include electrical carrier signals and telecommunications signals as is required by legislation and patent practice.
Example four
Referring to fig. 4, fig. 4 is a schematic structural diagram of a bluetooth positioning system 30 based on confidence level according to an embodiment of the present invention; comprising a plurality of bluetooth nodes 31 and a confidence based bluetooth positioning apparatus 10 as described in any of the above embodiments; wherein,
the Bluetooth node 31 is arranged in the passable area; the passable area is divided into a plurality of square areas with equal size, and the Bluetooth nodes 31 are arranged on four nodes of each square area; each of the bluetooth nodes 31 transmits bluetooth signals of the same signal strength at the same period.
It should be noted that please refer to the working process of the bluetooth positioning apparatus 10 based on confidence level in the second embodiment, which is not repeated herein.
In specific implementation, firstly, the bluetooth positioning apparatus 10 based on confidence coefficient obtains the detected bluetooth signals of a plurality of bluetooth nodes 31 within a preset time, and searches for a corresponding pre-divided adjacent node group according to the detected bluetooth signal of each bluetooth node 31; then, the bluetooth positioning apparatus 10 based on the confidence level obtains the confidence level of the bluetooth node 31; finally, the bluetooth positioning apparatus 10 based on the confidence calculates the weight of the bluetooth node 31 according to the detected bluetooth signal strength and confidence of each bluetooth node 31, and calculates the positioning coordinate according to the weight of the bluetooth node 31.
Compared with the prior art, the Bluetooth positioning system 30 based on the confidence coefficient solves the problem that the actual distance value calculated is inaccurate due to the influence of environmental factors in the prior art, and also solves the problem that the cost is increased due to the need of acquiring data in the early stage.
It should be noted that the above-described device embodiments are merely illustrative, where the units described as separate parts may or may not be physically separate, and the parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. In addition, in the drawings of the embodiment of the apparatus provided by the present invention, the connection relationship between the modules indicates that there is a communication connection between them, and may be specifically implemented as one or more communication buses or signal lines. One of ordinary skill in the art can understand and implement it without inventive effort.
While the foregoing is directed to the preferred embodiment of the present invention, it will be understood by those skilled in the art that various changes and modifications may be made without departing from the spirit and scope of the invention.
Claims (8)
1. A Bluetooth positioning method based on confidence coefficient is characterized in that the method is suitable for a mobile terminal and comprises the following steps:
when a positioning program is started and a region covered by the Bluetooth nodes is entered, acquiring the detected Bluetooth signals of the plurality of Bluetooth nodes within preset time; the Bluetooth signal is greater than the preset signal intensity;
searching a corresponding adjacent node group which is divided in advance according to the detected Bluetooth signal of each Bluetooth node; the adjacent node group takes any Bluetooth node as a central node and comprises the central node and a plurality of adjacent nodes in a preset range of the central node;
taking the ratio of the number of the adjacent nodes which can be detected with Bluetooth signals in the adjacent node group to the number of the adjacent nodes in the adjacent node group as the confidence of the current Bluetooth node;
calculating the weight of the Bluetooth node according to the detected Bluetooth signal intensity and the confidence coefficient of the Bluetooth node, and calculating a positioning coordinate according to the weight of the Bluetooth node;
the weight calculation method of the Bluetooth node comprises the following steps:
ri is the signal strength of the ith Bluetooth node, mu is the expectation of normal distribution, delta is the variance, confidenceiRepresenting the confidence level of the ith bluetooth node.
2. The confidence-based bluetooth positioning method of claim 1, wherein each of the bluetooth nodes transmits bluetooth signals of the same signal strength according to the same period.
3. The confidence-based bluetooth positioning method according to claim 1, wherein the bluetooth node is located in a passable area; the passable area is divided into a plurality of square areas with the same size, and the Bluetooth nodes are arranged on four nodes of each square area.
4. The bluetooth positioning method based on confidence level according to claim 1, wherein the calculating the positioning coordinates according to the weight of the bluetooth node specifically comprises:
and calculating the positioning coordinate according to the weight of the Bluetooth node and the coordinate vector of the Bluetooth node.
5. A bluetooth positioning apparatus based on confidence level, which is suitable for a mobile terminal, comprising:
the signal detection unit is used for acquiring the detected Bluetooth signals of the plurality of Bluetooth nodes within preset time when a positioning program is started and the Bluetooth nodes enter an area covered by the Bluetooth nodes; the Bluetooth signal is greater than the preset signal intensity;
the adjacent node group searching unit is used for searching a corresponding adjacent node group which is divided in advance according to the detected Bluetooth signal of each Bluetooth node; the adjacent node group takes any Bluetooth node as a central node and comprises the central node and a plurality of adjacent nodes in a preset range of the central node;
a confidence coefficient obtaining unit, configured to obtain a ratio of the number of neighboring nodes in the neighboring node group, where a bluetooth signal can be detected, to the number of neighboring nodes in the neighboring node group, as a confidence coefficient of the current bluetooth node;
the positioning coordinate calculation unit is used for calculating the weight of the Bluetooth node according to the detected Bluetooth signal intensity and the confidence coefficient of the Bluetooth node and calculating the positioning coordinate according to the weight of the Bluetooth node;
the weight calculation method of the Bluetooth node comprises the following steps:
ri is the signal strength of the ith Bluetooth node, mu is the expectation of normal distribution, delta is the variance, confidenceiRepresenting the confidence level of the ith bluetooth node.
6. The confidence-based bluetooth positioning apparatus according to claim 5, wherein the positioning coordinate calculation unit is configured to calculate the positioning coordinates according to the weight of the bluetooth node and the coordinate vector of the bluetooth node.
7. A confidence-based Bluetooth positioning apparatus comprising a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, the processor when executing the computer program implementing the confidence-based Bluetooth positioning method of any of claims 1-4.
8. A confidence-based Bluetooth positioning system, comprising a plurality of Bluetooth nodes and the confidence-based Bluetooth positioning apparatus of any one of claims 5-6; wherein,
the Bluetooth node is arranged in the passable area; the passable area is divided into a plurality of square areas with the same size, and the Bluetooth nodes are arranged on four nodes of each square area; and each Bluetooth node sends Bluetooth signals with the same signal strength according to the same period.
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