CN108712718A - Location processing method, device, server and storage medium - Google Patents
Location processing method, device, server and storage medium Download PDFInfo
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- CN108712718A CN108712718A CN201810457686.5A CN201810457686A CN108712718A CN 108712718 A CN108712718 A CN 108712718A CN 201810457686 A CN201810457686 A CN 201810457686A CN 108712718 A CN108712718 A CN 108712718A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/02—Services making use of location information
- H04W4/025—Services making use of location information using location based information parameters
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/30—Services specially adapted for particular environments, situations or purposes
- H04W4/33—Services specially adapted for particular environments, situations or purposes for indoor environments, e.g. buildings
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W64/00—Locating users or terminals or network equipment for network management purposes, e.g. mobility management
Abstract
A kind of location processing method of the application offer, device, server and storage medium, this method include：Location Request is received, Location Request includes the first fingerprint of target to be positioned；It according to the location fingerprint library of pre-configuration, determines that the fingerprint class belonging to the first fingerprint is target fingerprint class, includes at least two fingerprint classes in location fingerprint library, each fingerprint class includes the fingerprint and location information of one or more reference points；If the first fingerprint is in the edge of target fingerprint class, determine that at least one other fingerprint class is reference fingerprint class according to the Euclidean distance of the center reference point of other each fingerprint classes in the first fingerprint and location fingerprint library；According to the Euclidean distance of each reference point in the first fingerprint and target fingerprint class and reference fingerprint class, the position of target to be positioned is determined.If the fingerprint for solving target to be positioned in the prior art is located at the edge of target fingerprint class, the larger problem of the site error of the target to be positioned determined effectively increases the accuracy of positioning.
Description
Technical field
This application involves indoor positioning technologies field more particularly to a kind of location processing method, device, server and storages
Medium.
Background technology
Under the historical background of Modern Information, location based service is more and more common, this development to location technology
Propose new requirement.Traditional location technology based on GPS can reach civilian 3 meters of precision, but apply in general to outdoor
Environment is difficult to reach degree of precision indoors under complex environment.
Currently, technology type relatively common in indoor positioning technologies has Zigbee, RFID, bluetooth, ultrasonic wave, infrared
Line, WiFi etc., various positioning methods popularize range, cost of equipment maintenance etc. mutual in positioning accuracy, deployment cost, market
Pros and cons.And being widely used with the development of WiFi technology and wireless terminal, WiFi are more and more universal in environment indoors, it is personal
WiFi signal is all provided in the houses such as family, coffee-house, library, airport departure lounge, market, and WiFi technology have it is logical
The features such as believing fast rate, signal stabilization, strong antijamming capability, high equipment popularity rate is all established for it as general indoor positioning technologies
Basis is determined.
WiFi indoor positioning technologies are more widely to be based on received signal strength at present also there are many subdivision technology is planted
The positioning of RSSI (Received Signal Strength Indication), and exist here there are many specific algorithm
It enriches constantly and perfect.Wherein, fixed in order to simplify since location fingerprint technology needs to process huge location fingerprint data
Bit stream journey improves location efficiency, and the thought of cluster is applied in the division of location fingerprint by people, and achieves good effect
Fruit.
Existing clustering algorithm applies the calculation amount that the tuning on-line stage can be reduced in the fingerprint location of position, and it is fixed to accelerate
Bit rate still when tuning on-line determines which class anchor point to be measured belong to, is susceptible to point to be determined and is in certain class A
Edge, positioning accuracy can be reduced by being classified to class A merely.Therefore, indoor position accuracy how is effectively improved as there is an urgent need for solutions
Certainly the technical issues of.
Invention content
A kind of location processing method of the application offer, device, server and storage medium, it is fixed in prior art room to solve
The defects of position accuracy is relatively low.
The application the first aspect provides a kind of location processing method, including：
Location Request is received, the Location Request includes the first fingerprint of target to be positioned；
According to the location fingerprint library of pre-configuration, determine that the fingerprint class belonging to first fingerprint is target fingerprint class, it is described
Include at least two fingerprint classes in location fingerprint library, each fingerprint class includes fingerprint and the position of one or more reference points
Information；
If first fingerprint is in the edge of the target fingerprint class, referred to the position according to first fingerprint
The Euclidean distance of the center reference point of other each fingerprint classes determines that at least one other fingerprint class is reference fingerprint class in line library；
According to each reference point in first fingerprint and the target fingerprint class and the reference fingerprint class it is European away from
From determining the position of the target to be positioned.
The second aspect of the application provides a kind of positioning treatment apparatus, including：
Receiving module, for receiving Location Request, the Location Request includes the first fingerprint of target to be positioned；
First determining module determines the fingerprint class belonging to first fingerprint for the location fingerprint library according to pre-configuration
Include at least two fingerprint classes for target fingerprint class, in the location fingerprint library, each fingerprint class includes one or more
The fingerprint and location information of reference point；
Second determining module, if being in the edge of the target fingerprint class for first fingerprint, according to described the
The Euclidean distance of one fingerprint and the center reference point of other each fingerprint classes in the location fingerprint library determines at least one other finger
Line class is reference fingerprint class；
Processing module, for according to each ginseng in first fingerprint and the target fingerprint class and the reference fingerprint class
The Euclidean distance of examination point determines the position of the target to be positioned.
A kind of server is provided in terms of the third of the application, including：At least one processor and memory；
The memory stores computer program；At least one processor executes the computer of the memory storage
Program, to realize above-mentioned method.
The 4th aspect of the application provides a kind of computer readable storage medium, is deposited in the computer readable storage medium
Computer program is contained, the computer program, which is performed, realizes above-mentioned method.
Location processing method, device, server and storage medium provided by the present application, pass through the fingerprint in target to be positioned
When in the edge of target fingerprint class, the reference point in combining target fingerprint class and the reference fingerprint class closed on determines undetermined jointly
The position of position target refers to if the fingerprint for solving target to be positioned in the prior art is located at the edge of target fingerprint class in target
Reference point that may be not enough in line class assists positioning or the target to be positioned away from other reference points in target fingerprint class
Farther out, the problem for causing the site error of determining target to be positioned larger, effectively increases the accuracy of positioning.
Description of the drawings
In order to illustrate the technical solutions in the embodiments of the present application or in the prior art more clearly, to embodiment or will show below
There is attached drawing needed in technology description to be briefly described, it should be apparent that, the accompanying drawings in the following description is this Shen
Some embodiments please for those of ordinary skill in the art without having to pay creative labor, can be with
Obtain other attached drawings according to these attached drawings.
Fig. 1 is the flow diagram for the location processing method that one embodiment of the application provides；
Fig. 2 is the flow diagram for the location processing method that another embodiment of the application provides；
Fig. 3 is the edge decision criteria schematic diagram that one embodiment of the application provides；
Fig. 4 is that the room area that one embodiment of the application provides divides schematic diagram；
Fig. 5 is the absolute error contrast schematic diagram that one embodiment of the application provides；
Fig. 6 is the structural schematic diagram for the positioning treatment apparatus that one embodiment of the application provides；
Fig. 7 is the structural schematic diagram for the server that one embodiment of the application provides；
Fig. 8 is the structural schematic diagram for the localization process system that one embodiment of the application provides.
Through the above attached drawings, it has been shown that the specific embodiment of the application will be hereinafter described in more detail.These attached drawings
It is not intended to limit the scope of this disclosure concept by any means with verbal description, but is by referring to specific embodiments
Those skilled in the art illustrate the concept of the application.
Specific implementation mode
To keep the purpose, technical scheme and advantage of the embodiment of the present application clearer, below in conjunction with the embodiment of the present application
In attached drawing, technical solutions in the embodiments of the present application is clearly and completely described, it is clear that described embodiment is
Some embodiments of the present application, instead of all the embodiments.Based on the embodiment in the application, those of ordinary skill in the art
The every other embodiment obtained without creative efforts, shall fall in the protection scope of this application.
Location processing method provided by the present application is suitable for having been set up the indoor target to be positioned in location fingerprint library
Localization process.Target to be positioned, which can be but not limited to mobile phone, tablet computer etc., has the terminal of wireless WIFI function.Tool
Body, to realize to the positioning in the indoor target to be positioned of certain target, need to be arranged in target chamber a certain number of
Signal source device, such as wireless access points AP, and pre-establish the indoor location fingerprint library of the target, i.e., mesh is obtained in advance
The indoor fingerprint of at least two reference points of mark and the correspondence of location information, and cluster is carried out to each reference point and obtains at least two
A fingerprint class.When needing to position to being in the indoor target to be positioned of target, the first of target to be positioned can be obtained
Fingerprint determines target to be positioned according to the fingerprint of each reference point stored in the first fingerprint and location fingerprint library and location information
Position.
In practical applications, according to the propagation model of indoor signal, the signal strength received at AP different distances is not
With, the distance of terminal counter can be pushed away according to received signal strength, usual three or more signal strengths can determine that two dimension is flat
The position of terminal in face uses in certain room area according to the correlation of WIFI signal and position and avoids symmetrical mode cloth
Set a certain number of AP, then the signal strength that each AP received at different location in the room area is sent out has otherness,
It is reference point that different location in room area, which thus can be selected, and the signal strength sequence for testing each reference point in advance (refers to
Line) and location information, it is used for the subsequently positioning to the terminal in the room area.
The signal strength sequence and location information of each reference point, positioning terminal can specifically be tested in advance by positioning terminal
Can be equipped with wireless network card, can be used for scan receive WIFI signal electronic equipment, such as can be mobile phone, tablet electricity
The mobile electronic devices such as brain, motion bracelet can also be the electronic equipment for being fixed on default each reference point.
In addition, term " first ", " second " etc. are used for description purposes only, it is not understood to indicate or imply relatively important
Property or implicitly indicate the quantity of indicated technical characteristic.In the description of following embodiment, the meaning of " plurality " is two
More than a, unless otherwise specifically defined.
These specific embodiments can be combined with each other below, may be at certain for same or analogous concept or process
It is repeated no more in a little embodiments.Below in conjunction with attached drawing, the embodiment of the present invention is described.
Embodiment one
The present embodiment provides a kind of location processing methods, for being positioned to indoor target to be positioned.The present embodiment
Executive agent be positioning treatment apparatus, which can be arranged in location-server.
As shown in Figure 1, for the flow diagram of location processing method provided in this embodiment, this method includes：
Step 101, Location Request is received, Location Request includes the first fingerprint of target to be positioned.
Specifically, the mobile phone that target to be positioned, which can be user, to be used, tablet computer, laptop or other have
The terminal device or electronic equipment of WIFI function.It oneself is currently at indoor position when user wants to know about, or needs to lead
Navigate to other positions and it needs to be determined that user current location when, can by terminal device to location-server send positioning ask
It asks, Location Request includes the first fingerprint of target to be positioned, and location-server receives Location Request, can get terminal and set
The first standby fingerprint, the first fingerprint can be the wireless access points AP signal strength sequences that terminal device receives.
Step 102, according to the location fingerprint library of pre-configuration, determine that the fingerprint class belonging to the first fingerprint is target fingerprint class,
Include at least two fingerprint classes in location fingerprint library, each fingerprint class includes fingerprint and the position of one or more reference points
Information.
Specifically, after location-server gets the first fingerprint of terminal device, then can be referred to according to the position of pre-configuration
Line library determines that the fingerprint class belonging to the first fingerprint is target fingerprint class, includes at least two fingerprint classes in location fingerprint library, often
A fingerprint class includes the fingerprint and location information of one or more reference points.
Wherein, reference point refers to that room area is divided into the central point of all subregion.The fingerprint of reference point is specific bit
The signal strength sequence that the signal strength for the WIFI signal that each AP that terminal receives at the reference point is sent out is constituted.
Illustratively, the first fingerprint is signal strength sequence R={ riss1,riss2,…,rissn, wherein n is preset
AP is ranked sequentially, riss by the quantity of AP according to presetiIndicate the signal for the WIFI signal that i-th of the AP received is sent out
Intensity, i can be 1,2 ..., n.In the present embodiment, preset order can be each AP being ranked sequentially according to any determination, such as
To each AP serial numbers, preset order can be that descending sequence is numbered according to AP.It calculates in R and location fingerprint library successively
The Euclidean distance of the center Mj of each fingerprint class, it is target fingerprint class to choose the wherein minimum corresponding fingerprint class of Euclidean distance,
Namely the first fingerprint of target to be positioned belongs to the target fingerprint class.
Fingerprint class refers to being clustered each reference point of the room area in location fingerprint library using clustering algorithm, is divided into
Each fingerprint class.
Step 103, if the first fingerprint is in the edge of target fingerprint class, according to each in the first fingerprint and location fingerprint library
The Euclidean distance of the center reference point of other fingerprint classes determines that at least one other fingerprint class is reference fingerprint class.
Specifically, when the first fingerprint is in the edge of target fingerprint class, if only relying on the reference point in target fingerprint class
It determines the position of target to be positioned, is likely to result in larger error, therefore, if the first fingerprint is in the side of target fingerprint class
Edge needs to select a certain number of fingerprint classes as fingerprint class is referred to from the adjacent class of target fingerprint class, with target fingerprint class
The positioning of target to be positioned is participated in jointly.
Step 104, according to the Euclidean distance of each reference point in the first fingerprint and target fingerprint class and reference fingerprint class, really
The position of fixed target to be positioned.
Specifically, when determining the position of target to be positioned, if the first fingerprint of target to be positioned is in target fingerprint class
Edge, need each reference point in the reference fingerprint class in conjunction with above-mentioned determination and each reference point in target fingerprint class, altogether
With the position for determining target to be positioned.
Location processing method provided in this embodiment is in the edge of target fingerprint class by the fingerprint in target to be positioned
When, the reference point in combining target fingerprint class and the reference fingerprint class closed on determines the position of target to be positioned jointly, solves
It, may be not enough in target fingerprint class if the fingerprint of target to be positioned is located at the edge of target fingerprint class in the prior art
Reference point assists positioning or the target to be positioned farther out, to cause determining to be positioned away from other reference points in target fingerprint class
The larger problem of the site error of target, effectively increases the accuracy of positioning.
Embodiment two
The location processing method that the present embodiment provides embodiment one does further supplementary explanation.
As shown in Fig. 2, for the flow diagram of location processing method provided in this embodiment.
As a kind of enforceable mode, on the basis of the above embodiment 1, optionally, step 102 specifically includes：
Step 1021, the Euclidean distance of the first fingerprint and the center reference point of each fingerprint class in location fingerprint library is calculated.
Illustratively, the first fingerprint is R={ riss1,riss2,…,rissn, i-th fingerprint class in location fingerprint library
The fingerprint of center reference point is Ri={ riss1 i,riss2 i,…,rissn i, then the first fingerprint and the center reference point is European
Distance is Di：
Wherein, rissj iThe letter for the WIFI signal that j-th of AP is sent out is received at center reference point for i-th of fingerprint class
Number intensity.
Step 1022, determine that fingerprint class corresponding with the center reference point of Euclidean distance minimum of the first fingerprint refers to for target
Line class.
As another enforceable mode, on the basis of the above embodiment 1, optionally, step 103 includes：
If the first fingerprint is in the edge of target fingerprint class, according to other each fingerprints in the first fingerprint and location fingerprint library
The Euclidean distance of the center reference point of class determines that at least one other fingerprint class is reference fingerprint class, including：
If the first value P to be determined meets P>1, alternatively, L≤P≤1, wherein P=d/D1*100%, d be the first fingerprint with
The Euclidean distance of the center reference point of target fingerprint class, D1 are the maximum Europe of each reference point and center reference point in target fingerprint class
Formula distance, L are the first predetermined threshold value, 0 < L < 1；Also, for other fingerprint classes of each of location fingerprint library, if second waits for
Decision content S meets 1≤S of decision condition≤T, wherein S=D2/d*100%, D2 are the center of the first fingerprint and other fingerprint classes
The Euclidean distance of reference point, d are the Euclidean distance of the first fingerprint and the center reference point of target fingerprint class, and T is the second default threshold
Value, T > 1, it is determined that the first fingerprint is in the edge of target fingerprint class and other fingerprint classes are reference fingerprint class.
Specifically, judging whether the first fingerprint is in the edge of target fingerprint class, need to meet two conditions：
Condition one：As P > 1, illustrate the Euclidean distance ratio of the center reference point of target range target fingerprint class to be positioned
Any reference point of other in target fingerprint class will be remote, and determination at this time meets condition one；When L≤P≤1, determination meets condition one；
In practical operation, L with value 0.8, can illustrate that the first fingerprint of target to be positioned is in the center reference point away from target fingerprint class
Maximum Euclidean distance 80% other than, it can be determined that it meets condition one.It should be noted that the value of L can be according to reality
Demand is configured, for example can also be 0.7,0.9 etc., and the present embodiment is merely illustrative, and is not limited it.
Condition two：When T can illustrate target to be positioned and target fingerprint class with value 1.5 in 1≤S≤T, practical application
Center reference point within the scope of 1.5 times of the Euclidean distance d of center reference point still with the presence of other fingerprint classes, therefore this other
Fingerprint class needs take in.In practical operation, the value of T can be configured according to actual demand, for example can also be
1.4,1.6 etc., the present embodiment is merely illustrative, and is not limited it.
When the first fingerprint of target to be positioned meets above-mentioned condition one and condition two, it may be determined that the target to be positioned
First fingerprint is in the edge of target fingerprint class.
As shown in figure 3, being decision criteria schematic diagram in edge provided in this embodiment.Wherein, A indicates target fingerprint class, X tables
Show that target to be positioned, M indicate that other fingerprint classes, d are the Euclidean distance of the first fingerprint and the center reference point O1 of target fingerprint class,
D1 is the maximum Euclidean distance of each reference point and center reference point in target fingerprint class, and D2 is the first fingerprint and other fingerprint classes M
Center reference point O2 Euclidean distance.
As another enforceable mode, on the basis of the above embodiment 1, optionally, step 104 specifically includes：
Step 1041, according to the Euclidean distance of each reference point in the first fingerprint and target fingerprint class and reference fingerprint class,
By sequence from small to large, select K reference point as intended reference point, K is preset positive integer.
Specifically, after reference fingerprint class is determined, need to calculate the first fingerprint and each reference point in target fingerprint class
The Euclidean distance of Euclidean distance and the first fingerprint and each reference point in each reference fingerprint class, specific calculating process and above-mentioned meter
Calculation process is consistent, and details are not described herein.
After the Euclidean distance for calculating each reference point in obtaining the first fingerprint and target fingerprint class and each reference fingerprint class,
It therefrom selects with K reference point of the first fingerprint Euclidean distance minimum as intended reference point, for determining target to be positioned
Position.
Illustratively, there are 6 reference points in target fingerprint class, there are two reference fingerprint class, have 4 in each reference fingerprint class
A reference point, i.e., a total of 14 intended reference points, calculates separately the Euclidean distance of the first fingerprint and this 14 intended reference points,
14 Euclidean distance values are obtained, K=4 minimum Euclidean distance value are selected from this 14 Euclidean distance values, this 4 European
The corresponding reference point of distance value is intended reference point.
Step 1042, mesh to be positioned is determined using weighting K adjacent to WKNN algorithms according to the location information of intended reference point
Target position.
Specifically, by the location information of K intended reference point, such as coordinate, it averages, target to be positioned is calculated
Position.
Optionally, this method further includes：
Step 201, if the first fingerprint is not at the edge of target fingerprint class, according in the first fingerprint and target fingerprint class
Each reference point Euclidean distance, by K reference point of sequential selection from small to large as intended reference point.
Specifically, the concrete operations of the step are similar to the above process, details are not described herein.
As another enforceable mode, on the basis of the above embodiment 1, optionally, before step 101, the party
Method further includes：
Step 202, the fingerprint and location information of preset each reference point are obtained.
Step 203, the fingerprint of each reference point and location information are corresponded into storage, establishes location fingerprint library.
Step 204, using K mean value K-means clustering algorithms, each reference point in the fingerprint base of position is clustered, is obtained
Obtain at least two fingerprint classes.
Specifically, before realizing and being positioned to the target to be positioned of certain room area, needs to pre-establish position and refer to
Line library, and preset each reference point is clustered, obtain at least two fingerprint classes.
Illustratively, certain careat is 9.9m*16m, and surrounding is solid wall, indoor several compartments, hall Office Area
Several tables and chairs and electrical equipment constitute the complex environment of indoor positioning.Room area is divided 160 with the interval of 1m
Zonule, in real map and cell phone map from the upper left corner start setting up coordinate be (0,0), until the lower right corner be (990,
1600) reference point, is set up at the center of each zonule, according to from left to right, sequence from top to bottom is labeled as 1-160.It adopts
It is 1-6 by sequence number consecutively from left to right with random and symmetrical mode is avoided to arrange 6 AP indoors.Such as Fig. 4 institutes
Show, schematic diagram is divided for room area provided in this embodiment.Each dot is a reference point, and each small rectangle is one small
Region.
The client that test is installed in positioning terminal acquires 50 fingers using positioning terminal at each reference point
The signal strength information of line, i.e. AP transmitting, client calculate mean value automatically and MAC Address together with reference point serial number and AP and
Signal strength is sent to server end.After the data of full 160 reference points of acquisition, server executes clustering algorithm, according to letter
Reference point cluster is obtained each fingerprint class by number intensity relationship corresponding with reference point locations information, and is calculated in each fingerprint class
The heart refers to point coordinates and fingerprint, i.e. signal strength, in storage to database, to establish location fingerprint library.
When user is in the interior, when needing positioning, portable terminal device (target to be positioned) can be passed through
Location Request is sent to location-server, Location Request includes the first fingerprint of terminal device, and location-server receives fixed
After the request of position, according to the first fingerprint, the position of subscriber terminal equipment is determined using above-mentioned location processing method, and to terminal device
Determining position is returned to, terminal device shows the position that location-server returns on default map.
In practical applications, the map individual difference of indoor positioning is big, and the map needs of different indoor environments are specifically painted
System.Quick updating ability is needed when environment changes.Therefore it can use the softwares such as MicrosoftOffice Visio will
Localization region is depicted as the picture of jpg formats, imported into target to be positioned, and mark is corresponded on map in conjunction with the position that positioning obtains
Note.In addition, have the scaling button to map in map interface, and can be with long press dragging map.One option can also be set
Button is integrated with snapshot and position and reports an error function, to count correct localization.
In the present embodiment, for the clustering algorithm used for K mean value K-means clustering algorithms, specific implementation procedure can be existing
There is technology, details are not described herein.
In cluster process, the effect of cluster is examined using cluster test rating BWP indexs.Specific checked operation can
Think the prior art, details are not described herein.
Illustratively, the present embodiment chooses 20 targets to be positioned at edge to having carried out assignment test in above-mentioned interior
It is tested, each 3 fingerprints of target detection to be positioned, i.e. signal strength calculate average signal strength, corresponding information sent out
Server is given, positioning result is sent to client after executing above-mentioned location processing method and stored to database by server.
As shown in figure 5, being absolute error contrast schematic diagram provided in this embodiment.It refer to the localization process side of the prior art before improvement
Method refers to location processing method provided by the present application after improvement.As seen from the figure, the measurement error value of the application it is whole compared with
It is small, and discreteness be less than improve before, especially the 1st time and the 10 to 15th time, the application position error is obviously reduced, this is because
Above-mentioned test point is larger to the compatible degree of edge anchor point, has large error when positioning using a class merely.Existing skill
Art worst error is 4.02m, is 3.29 meters after improvement, average error drops to 2.11 meters by 2.64m, and error reduces
20%.
It should be noted that each enforceable mode can individually be implemented in the present embodiment, it can also be in the feelings not conflicted
It is not limited in conjunction with implementation the application in any combination under condition.
Location processing method provided in this embodiment is in the edge of target fingerprint class by the fingerprint in target to be positioned
When, the reference point in combining target fingerprint class and the reference fingerprint class closed on determines the position of target to be positioned jointly, solves
It, may be not enough in target fingerprint class if the fingerprint of target to be positioned is located at the edge of target fingerprint class in the prior art
Reference point assists positioning or the target to be positioned farther out, to cause determining to be positioned away from other reference points in target fingerprint class
The larger problem of the site error of target, effectively increases the accuracy of positioning.
Embodiment three
The present embodiment provides a kind of positioning treatment apparatus, the method for executing above-described embodiment one.
As shown in fig. 6, for the structural schematic diagram of positioning treatment apparatus provided in this embodiment.The positioning treatment apparatus 30 wraps
Include receiving module 31, the first determining module 32, the second determining module 33 and processing module 34.
Wherein, for receiving module 31 for receiving Location Request, Location Request includes the first fingerprint of target to be positioned；First
Determining module 32 is used for the location fingerprint library according to pre-configuration, determines that the fingerprint class belonging to the first fingerprint is target fingerprint class, position
It includes at least two fingerprint classes to set in fingerprint base, and each fingerprint class includes the fingerprint and position letter of one or more reference points
Breath；If the second determining module 33 is in the edge of target fingerprint class for the first fingerprint, according to the first fingerprint and location fingerprint
The Euclidean distance of the center reference point of other each fingerprint classes determines that at least one other fingerprint class is reference fingerprint class in library；Processing
Module 34 is used to, according to the Euclidean distance of each reference point in the first fingerprint and target fingerprint class and reference fingerprint class, determine undetermined
The position of position target.
Device in this present embodiment is closed, wherein modules execute the concrete mode of operation in related this method
It is described in detail in embodiment, explanation will be not set forth in detail herein.
According to positioning treatment apparatus provided in this embodiment, target fingerprint class is in by the fingerprint in target to be positioned
When edge, the reference point in combining target fingerprint class and the reference fingerprint class closed on determines the position of target to be positioned jointly, solution
It, may be without foot in target fingerprint class if the fingerprint for the target to be positioned in the prior art of having determined is located at the edge of target fingerprint class
Enough reference points assist positioning or the target to be positioned farther out, to lead to determining wait for away from other reference points in target fingerprint class
The larger problem of the site error of target is positioned, the accuracy of positioning is effectively increased.
Example IV
The positioning treatment apparatus that the present embodiment provides above-described embodiment three does further supplementary explanation, to execute above-mentioned reality
The method that the offer of example two is provided.
As a kind of enforceable mode, on the basis of above-described embodiment three, optionally, the first determining module, specifically
For：
Calculate the Euclidean distance of the first fingerprint and the center reference point of each fingerprint class in location fingerprint library；It determines and refers to first
The corresponding fingerprint class of center reference point of the Euclidean distance minimum of line is target fingerprint class.
As another enforceable mode, on the basis of above-described embodiment three, optionally, and the second determining module, tool
Body is used for：
If the first value P> to be determined;1, alternatively, L≤P≤1, wherein P=d/D1*100%, d are that the first fingerprint refers to target
The Euclidean distance of the center reference point of line class, D1 be the maximum of each reference point and center reference point in target fingerprint class it is European away from
From L is the first predetermined threshold value, 0 < L < 1；Also, for other fingerprint classes of each of location fingerprint library, if second is to be determined
Value S meets 1≤S of decision condition≤T, wherein S=D2/d*100%, D2 are the center reference of the first fingerprint and other fingerprint classes
The Euclidean distance of point, d are the Euclidean distance of the first fingerprint and the center reference point of target fingerprint class, and T is the second predetermined threshold value, T
> 1, it is determined that the first fingerprint is in the edge of target fingerprint class and other fingerprint classes are reference fingerprint class.
As another enforceable mode, on the basis of above-described embodiment three, optionally, processing module is specific to use
In：
According to the Euclidean distance of each reference point in the first fingerprint and target fingerprint class and reference fingerprint class, by from small to large
Sequence, select K reference point as intended reference point, K is preset positive integer；According to the location information of intended reference point,
Using weighting K adjacent to WKNN algorithms, the position of target to be positioned is determined.
Optionally, the second determining module is additionally operable to：
If the first fingerprint is not at the edge of target fingerprint class, according to each reference in the first fingerprint and target fingerprint class
The Euclidean distance of point, by K reference point of sequential selection from small to large as intended reference point.
As another enforceable mode, on the basis of above-described embodiment three, optionally, which further includes obtaining
Module establishes module and cluster module.
Wherein, acquisition module is used to obtain the fingerprint and location information of preset each reference point；Module is established for will be each
The fingerprint and location information of reference point correspond to storage, establish location fingerprint library；Cluster module is used for poly- using K mean values K-means
Class algorithm clusters each reference point in the fingerprint base of position, obtains at least two fingerprint classes.
Device in this present embodiment is closed, wherein modules execute the concrete mode of operation in related this method
It is described in detail in embodiment, explanation will be not set forth in detail herein.
It should be noted that each enforceable mode can individually be implemented in the present embodiment, it can also be in the feelings not conflicted
It is not limited in conjunction with implementation the application in any combination under condition.
According to the positioning treatment apparatus of the present embodiment, the edge of target fingerprint class is in by the fingerprint in target to be positioned
When, the reference point in combining target fingerprint class and the reference fingerprint class closed on determines the position of target to be positioned jointly, solves
It, may be not enough in target fingerprint class if the fingerprint of target to be positioned is located at the edge of target fingerprint class in the prior art
Reference point assists positioning or the target to be positioned farther out, to cause determining to be positioned away from other reference points in target fingerprint class
The larger problem of the site error of target, effectively increases the accuracy of positioning.
Embodiment five
The present embodiment provides a kind of servers, the location processing method provided for executing any of the above-described embodiment.
As shown in fig. 7, for the structural schematic diagram of server provided in this embodiment.The server 50 includes：It is at least one
Processor 51 and memory 52；
Memory stores computer program；At least one processor executes the computer program of memory storage, to realize
The location processing method that above-described embodiment provides.
According to the server of the present embodiment, when being in the edge of target fingerprint class by the fingerprint in target to be positioned, knot
The position that the reference point in target fingerprint class and the reference fingerprint class closed on determines target to be positioned jointly is closed, solves existing skill
If the fingerprint of target to be positioned is located at the edge of target fingerprint class in art, reference point that may be not enough in target fingerprint class
To assist positioning or target to be positioned farther out, to lead to determining target to be positioned away from other reference points in target fingerprint class
The larger problem of site error, effectively increases the accuracy of positioning.
Embodiment six
The present embodiment provides a kind of computer readable storage medium, computer is stored in the computer readable storage medium
Program, computer program are performed the method for realizing that any of the above-described embodiment provides.
According to the computer readable storage medium of the present embodiment, target fingerprint class is in by the fingerprint in target to be positioned
Edge when, the reference point in combining target fingerprint class and the reference fingerprint class closed on determines the position of target to be positioned jointly,
If the fingerprint for solving target to be positioned in the prior art is located at the edge of target fingerprint class, may not have in target fingerprint class
Enough reference points assist positioning or the target to be positioned farther out, to cause determining away from other reference points in target fingerprint class
The larger problem of the site error of target to be positioned, effectively increases the accuracy of positioning.
In some embodiments, a kind of localization process system, including location-server, terminal device and AP can also be provided
Device, as shown in figure 8, for the structural schematic diagram of localization process system provided in this embodiment.Wherein, location-server is for building
Vertical location fingerprint library, reception and the Location Request for responding terminal device.Terminal device is for acquiring AP signal strength informations, Xiang Ding
Position server sends Location Request, and the positioning result for receiving location-server return is presented to the user.AP devices are for emitting
Wireless signal.
Optionally, which can also include one or more positioning terminals, be used for advance collection room inner region
The fingerprint of each preset reference point, is sent to location-server in domain, and data are provided to establish location fingerprint library for server.
It should be noted that the concrete operations of localization process system components are in above-described embodiment in the present embodiment
In be described in detail, details are not described herein.
Localization process system provided in this embodiment is in the edge of target fingerprint class by the fingerprint in target to be positioned
When, the reference point in combining target fingerprint class and the reference fingerprint class closed on determines the position of target to be positioned jointly, solves
It, may be not enough in target fingerprint class if the fingerprint of target to be positioned is located at the edge of target fingerprint class in the prior art
Reference point assists positioning or the target to be positioned farther out, to cause determining to be positioned away from other reference points in target fingerprint class
The larger problem of the site error of target, effectively increases the accuracy of positioning.
In several embodiments provided herein, it should be understood that disclosed device and method can pass through it
Its mode is realized.For example, the apparatus embodiments described above are merely exemplary, for example, the division of the unit, only
Only a kind of division of logic function, formula that in actual implementation, there may be another division manner, such as multiple units or component can be tied
Another system is closed or is desirably integrated into, or some features can be ignored or not executed.Another point, it is shown or discussed
Mutual coupling, direct-coupling or communication connection can be the INDIRECT COUPLING or logical by some interfaces, device or unit
Letter connection can be electrical, machinery or other forms.
The unit illustrated as separating component may or may not be physically separated, aobvious as unit
The component shown may or may not be physical unit, you can be located at a place, or may be distributed over multiple
In network element.Some or all of unit therein can be selected according to the actual needs to realize the mesh of this embodiment scheme
's.
In addition, each functional unit in each embodiment of the application can be integrated in a processing unit, it can also
It is that each unit physically exists alone, it can also be during two or more units be integrated in one unit.Above-mentioned integrated list
The form that hardware had both may be used in member is realized, can also be realized in the form of hardware adds SFU software functional unit.
The above-mentioned integrated unit being realized in the form of SFU software functional unit can be stored in one and computer-readable deposit
In storage media.Above-mentioned SFU software functional unit is stored in a storage medium, including some instructions are used so that a computer
It is each that equipment (can be personal computer, server or the network equipment etc.) or processor (processor) execute the application
The part steps of embodiment the method.And storage medium above-mentioned includes：USB flash disk, mobile hard disk, read-only memory (Read-
Only Memory, ROM), random access memory (Random Access Memory, RAM), magnetic disc or CD etc. it is various
The medium of program code can be stored.
Those skilled in the art can be understood that, for convenience and simplicity of description, only with above-mentioned each function module
Division progress for example, in practical application, can be complete by different function modules by above-mentioned function distribution as needed
At the internal structure of device being divided into different function modules, to complete all or part of the functions described above.On
The specific work process for stating the device of description, can refer to corresponding processes in the foregoing method embodiment, and details are not described herein.
Finally it should be noted that：The above various embodiments is only to illustrate the technical solution of the application, rather than its limitations；To the greatest extent
Pipe is described in detail the application with reference to foregoing embodiments, it will be understood by those of ordinary skill in the art that：Its according to
So can with technical scheme described in the above embodiments is modified, either to which part or all technical features into
Row equivalent replacement；And these modifications or replacements, each embodiment technology of the application that it does not separate the essence of the corresponding technical solution
The range of scheme.
Claims (14)
1. a kind of location processing method, which is characterized in that including：
Location Request is received, the Location Request includes the first fingerprint of target to be positioned；
According to the location fingerprint library of pre-configuration, determine that the fingerprint class belonging to first fingerprint is target fingerprint class, the position
Include at least two fingerprint classes in fingerprint base, each fingerprint class includes the fingerprint and position letter of one or more reference points
Breath；
If first fingerprint is in the edge of the target fingerprint class, according to first fingerprint and the location fingerprint library
In the Euclidean distances of center reference point of other each fingerprint classes determine that at least one other fingerprint class is reference fingerprint class；
According to the Euclidean distance of each reference point in first fingerprint and the target fingerprint class and the reference fingerprint class, really
The position of the fixed target to be positioned.
2. according to the method described in claim 1, it is characterized in that, the location fingerprint library according to pre-configuration, determine described in
Fingerprint class belonging to first fingerprint is target fingerprint class, including：
Calculate the Euclidean distance of first fingerprint and the center reference point of each fingerprint class in the location fingerprint library；
Determine that fingerprint class corresponding with the center reference point of Euclidean distance minimum of first fingerprint is the target fingerprint class.
3. if according to the method described in claim 1, it is characterized in that, first fingerprint is in the target fingerprint class
Edge, then according to the Euclidean distance of the center reference point of other each fingerprint classes in first fingerprint and the location fingerprint library
Determine that at least one other fingerprint class is reference fingerprint class, including：
If the first value P> to be determined;1, alternatively, L≤P≤1, wherein P=d/D1*100%, d are first fingerprint and the mesh
The Euclidean distance of the center reference point of fingerprint class is marked, D1 is the maximum of each reference point and center reference point in the target fingerprint class
Euclidean distance, L are the first predetermined threshold value, 0 < L < 1；Also,
For other fingerprint classes of each of described location fingerprint library, if the second value S to be determined meets 1≤S of decision condition≤T,
Wherein, S=D2/d*100%, D2 are the Euclidean distance of first fingerprint and the center reference point of other fingerprint classes, and d is
The Euclidean distance of the center reference point of first fingerprint and the target fingerprint class, T are the second predetermined threshold value, T > 1, then really
Fixed first fingerprint is in the edge of the target fingerprint class and other described fingerprint classes are reference fingerprint class.
4. according to the method described in claim 1, it is characterized in that, described according to first fingerprint and the target fingerprint class
And the Euclidean distance of each reference point in the reference fingerprint class, determine the position of the target to be positioned, including：
According to the Euclidean distance of each reference point in first fingerprint and the target fingerprint class and the reference fingerprint class, press
Sequence from small to large selects K reference point as intended reference point, and K is preset positive integer；
According to the location information of the intended reference point position of the target to be positioned is determined using weighting K adjacent to WKNN algorithms
It sets.
5. if according to the method described in claim 4, it is characterized in that, first fingerprint is not at the target fingerprint class
Edge, then it is suitable by from small to large according to the Euclidean distance of each reference point in first fingerprint and the target fingerprint class
Sequence selects K reference point as the intended reference point.
6. according to claim 1-5 any one of them methods, which is characterized in that before receiving Location Request, the method
Further include：
Obtain the fingerprint and location information of preset each reference point；
The fingerprint of each reference point and location information are corresponded into storage, establish the location fingerprint library；
Using K mean value K-means clustering algorithms, each reference point in the location fingerprint library is clustered, obtains at least two
A fingerprint class.
7. a kind of positioning treatment apparatus, which is characterized in that including：
Receiving module, for receiving Location Request, the Location Request includes the first fingerprint of target to be positioned；
First determining module determines that the fingerprint class belonging to first fingerprint is mesh for the location fingerprint library according to pre-configuration
Fingerprint class is marked, includes at least two fingerprint classes in the location fingerprint library, each fingerprint class includes one or more references
The fingerprint and location information of point；
Second determining module refers to if being in the edge of the target fingerprint class for first fingerprint according to described first
The Euclidean distance of line and the center reference point of other each fingerprint classes in the location fingerprint library determines at least one other fingerprint class
For reference fingerprint class；
Processing module, for according to each reference point in first fingerprint and the target fingerprint class and the reference fingerprint class
Euclidean distance, determine the position of the target to be positioned.
8. device according to claim 7, which is characterized in that first determining module is specifically used for：
Calculate the Euclidean distance of first fingerprint and the center reference point of each fingerprint class in the location fingerprint library；
Determine that fingerprint class corresponding with the center reference point of Euclidean distance minimum of first fingerprint is the target fingerprint class.
9. device according to claim 7, which is characterized in that second determining module is specifically used for：
If the first value P> to be determined;1, alternatively, L≤P≤1, wherein P=d/D1*100%, d are first fingerprint and the mesh
The Euclidean distance of the center reference point of fingerprint class is marked, D1 is the maximum of each reference point and center reference point in the target fingerprint class
Euclidean distance, L are the first predetermined threshold value, 0 < L < 1；Also,
For other fingerprint classes of each of described location fingerprint library, if the second value S to be determined meets 1≤S of decision condition≤T,
Wherein, S=D2/d*100%, D2 are the Euclidean distance of first fingerprint and the center reference point of other fingerprint classes, and d is
The Euclidean distance of the center reference point of first fingerprint and the target fingerprint class, T are the second predetermined threshold value, T > 1, then really
Fixed first fingerprint is in the edge of the target fingerprint class and other described fingerprint classes are reference fingerprint class.
10. device according to claim 7, which is characterized in that the processing module is specifically used for：
According to the Euclidean distance of each reference point in first fingerprint and the target fingerprint class and the reference fingerprint class, press
Sequence from small to large selects K reference point as intended reference point, and K is preset positive integer；
According to the location information of the intended reference point position of the target to be positioned is determined using weighting K adjacent to WKNN algorithms
It sets.
11. device according to claim 10, which is characterized in that second determining module is additionally operable to：
If first fingerprint is not at the edge of the target fingerprint class, according to first fingerprint and the target fingerprint
The Euclidean distance of each reference point in class, by K reference point of sequential selection from small to large as the intended reference point.
12. according to claim 7-11 any one of them devices, which is characterized in that further include：
Acquisition module, fingerprint and location information for obtaining preset each reference point；
Module is established, for the fingerprint of each reference point and location information to be corresponded to storage, establishes the location fingerprint library；
Cluster module gathers each reference point in the location fingerprint library for using K mean value K-means clustering algorithms
Class obtains at least two fingerprint classes.
13. a kind of server, which is characterized in that including：At least one processor and memory；
The memory stores computer program；At least one processor executes the computer journey of the memory storage
Sequence, to realize the method described in any one of claim 1-6.
14. a kind of computer readable storage medium, which is characterized in that be stored with computer journey in the computer readable storage medium
Sequence, the computer program are performed the method realized described in any one of claim 1-6.
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| CN201810457686.5A CN108712718A (en) | 2018-05-14 | 2018-05-14 | Location processing method, device, server and storage medium |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110688431A (en) * | 2019-09-09 | 2020-01-14 | 平安普惠企业管理有限公司 | Method for configuring correspondence, server, and computer storage medium |
| CN112595338A (en) * | 2020-12-24 | 2021-04-02 | 中国联合网络通信集团有限公司 | Navigation method and navigation system |
| CN114630274A (en) * | 2022-03-31 | 2022-06-14 | 大连理工大学 | Precision estimation method for fingerprint positioning |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7216333B2 (en) * | 2003-04-08 | 2007-05-08 | Sun Microsystems, Inc. | Fingerprint subtype checking |
| CN106054128A (en) * | 2016-05-26 | 2016-10-26 | 天津城建大学 | Indoor navigation method and indoor navigation method device |
| US20170257768A1 (en) * | 2011-10-28 | 2017-09-07 | At&T Mobility Ii Llc | Sharing timed fingerprint location information |
| CN107367277A (en) * | 2017-06-05 | 2017-11-21 | 南京邮电大学 | Indoor location fingerprint positioning method based on secondary K Means clusters |
| CN107526058A (en) * | 2017-09-22 | 2017-12-29 | 中国联合网络通信集团有限公司 | Indoor orientation method, apparatus and system |
| WO2018071782A2 (en) * | 2016-10-14 | 2018-04-19 | Westfield Retail Solutions, Inc. | Systems and methods to determine a location of a mobile device |
| CN107979809A (en) * | 2017-10-27 | 2018-05-01 | 广州丰石科技有限公司 | It is a kind of according to distributed mobile base station and the fingerprint positioning method of edge calculations |
-
2018
- 2018-05-14 CN CN201810457686.5A patent/CN108712718A/en active Pending
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7216333B2 (en) * | 2003-04-08 | 2007-05-08 | Sun Microsystems, Inc. | Fingerprint subtype checking |
| US20170257768A1 (en) * | 2011-10-28 | 2017-09-07 | At&T Mobility Ii Llc | Sharing timed fingerprint location information |
| CN106054128A (en) * | 2016-05-26 | 2016-10-26 | 天津城建大学 | Indoor navigation method and indoor navigation method device |
| WO2018071782A2 (en) * | 2016-10-14 | 2018-04-19 | Westfield Retail Solutions, Inc. | Systems and methods to determine a location of a mobile device |
| CN107367277A (en) * | 2017-06-05 | 2017-11-21 | 南京邮电大学 | Indoor location fingerprint positioning method based on secondary K Means clusters |
| CN107526058A (en) * | 2017-09-22 | 2017-12-29 | 中国联合网络通信集团有限公司 | Indoor orientation method, apparatus and system |
| CN107979809A (en) * | 2017-10-27 | 2018-05-01 | 广州丰石科技有限公司 | It is a kind of according to distributed mobile base station and the fingerprint positioning method of edge calculations |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110688431A (en) * | 2019-09-09 | 2020-01-14 | 平安普惠企业管理有限公司 | Method for configuring correspondence, server, and computer storage medium |
| CN112595338A (en) * | 2020-12-24 | 2021-04-02 | 中国联合网络通信集团有限公司 | Navigation method and navigation system |
| CN114630274A (en) * | 2022-03-31 | 2022-06-14 | 大连理工大学 | Precision estimation method for fingerprint positioning |
| CN114630274B (en) * | 2022-03-31 | 2023-03-14 | 大连理工大学 | Precision estimation method for fingerprint positioning |
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