CN109819394A - Based on the WiFi indoor orientation method mixed with ultrasonic wave and its system - Google Patents
Based on the WiFi indoor orientation method mixed with ultrasonic wave and its system Download PDFInfo
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- CN109819394A CN109819394A CN201811654253.5A CN201811654253A CN109819394A CN 109819394 A CN109819394 A CN 109819394A CN 201811654253 A CN201811654253 A CN 201811654253A CN 109819394 A CN109819394 A CN 109819394A
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Abstract
The invention discloses a kind of indoor orientation method mixed based on WiFi with ultrasonic wave and its systems.The feature of the indoor orientation method and its system comprehensive WiFi indoor positioning technologies and ultrasonic wave indoor positioning technologies respectively, the WiFi finger print data being collected into is clustered using clustering algorithm, subregion locating for target is calculated using range equation, ultrasonic distance measurement is finally combined to carry out the accurate positioning of regional area.The indoor orientation method and its system had not only reduced the influence of fingerprint location data complexity, but also overcame the defect of ultrasonic transmitter limited angle, reduced the quantity of required ultrasonic transmitter.
Description
Technical field
The present invention relates to a kind of indoor orientation methods mixed based on WiFi with ultrasonic wave, also relate to corresponding interior
Positioning system belongs to wireless location technology field.
Background technique
Positioning under indoor environment is always the field that many problems are not solved.Due to signal deep fades and
Multipath effect, general outdoor positioning technology (such as GPS, Beidou etc.) can not effectively work in building.Currently, big
All there is WiFi under the indoor environment of part.WiFi signal has the characteristics that high coverage rate, flow be big and long transmission distance, this makes
The indoor positioning technologies based on WiFi are obtained to be developed rapidly.
Indoor positioning technologies based on WiFi can be divided into two classes, it may be assumed that indoor positioning technologies based on ranging and based on referring to
The indoor positioning technologies of line.Wherein, the indoor positioning technologies based on ranging are to dispose multiple anchor nodes indoors, are set by calculating
The standby position for carrying out positioning tracing equipment to the relative distance between anchor node.Wherein, distance can be obtained by a variety of methods,
Such as received signal intensity (RSSI), arrival time (ToA), angle of arrival (AoA).Distance measuring method based on RSSI is to utilize road
Diameter attenuation model calculates distance.Distance measuring method based on ToA is reached for the first time by obtaining the multipath component of channel impulse response
Time measures distance.Distance measuring method based on AoA is the arrival direction that transmitting node signal is perceived by certain hardware devices,
The relative bearing or angle between receiving node and anchor node are calculated, then triangulation etc. is recycled to calculate unknown node
Position.Indoor positioning technologies based on fingerprint are to connect the position in actual environment with certain " fingerprint ", a position
Set a corresponding unique fingerprint.This fingerprint can be one-dimensional or multidimensional, for example equipment to be positioned is being received or sent
Signal, then fingerprint can be a feature or multiple features for this signal or signal.Equipment to be positioned receives some fixations
Sending device signal or signal characteristic, the position of itself is then estimated according to the signal characteristic that these are detected.
On the other hand, ultrasonic wave indoor positioning technologies are built upon on the basis of ultrasonic distance measurement.Due to ultrasonic distance measurement
Precision can reach grade, therefore it is also relatively high using the precision that ultrasonic wave carries out indoor positioning.But ultrasonic transmitter
There are certain field angles, often can cross over some shelters like that without image of Buddha WiFi signal in face of complicated shelter.
Therefore, WiFi indoor positioning technologies and ultrasonic wave indoor positioning technologies cut both ways.If can learn from other's strong points to offset one's weaknesses, interior will be become
The contenders of location technology.
Summary of the invention
Aiming at the shortcomings in the prior art, primary technical problem to be solved by this invention is to provide a kind of based on WiFi
The indoor orientation method mixed with ultrasonic wave.
It is fixed that another technical problem to be solved by this invention is to provide a kind of interior mixed based on WiFi with ultrasonic wave
Position system.
For achieving the above object, the present invention uses following technical solutions:
According to a first aspect of the embodiments of the present invention, a kind of indoor positioning side mixed based on WiFi with ultrasonic wave is provided
Method includes the following steps:
Step 1: obtaining WiFi fingerprint, construct WiFi fingerprint base；
Step 2: clustering is carried out to the WiFi finger print data being collected into using clustering algorithm；
Step 3: target position being locked in single subregion, the subdivision for carrying out regional area in conjunction with ultrasonic distance measurement is fixed
Position.
Wherein more preferably, in the step 1, the different location by positioning terminal in localization region, which obtains corresponding WiFi, to be believed
Number feature, and collect the feature and location information of the position, the WiFi fingerprint base constructed by method for normalizing.
Wherein more preferably, multiple WiFi is continuously recorded to the same wireless router in same position using positioning terminal to believe
Number feature, feature of the averaged as the WiFi signal of the position.
Wherein more preferably, whether the feature of the WiFi signal includes but is not limited to signal strength, multidiameter configuration, can detect
To any one or more in access point or base station, two-way time or delay.
Wherein more preferably, in the step 2, collected WiFi finger print data is polymerized to K using K-means clustering algorithm
Then class calculates the initial position of current point using the locating point of current signal strength with the manhatton distance at K class center, wherein
K is positive integer.
Wherein more preferably, collected WiFi finger print data is polymerized to K class, including following sub-step:
(1) K point is randomly chosen in localization region as cluster centre；
(2) successively calculate in localization region that each point, and will be closely located to the Euclidean distance between K cluster centre
Point is classified as one kind；Euclidean distance calculates as follows:
Wherein, vector RSSIj,kFor the RSSI value of location point j, vector y is some cluster centre value, and p is wireless router
Number, q be each position collecting sample number；
(3) all cluster centres are recalculated, remember TMidtFor the set of all member vectors' values of 1 cluster, idt is indicated should
The label of cluster, then the cluster centre value H of this clusteridtIt is expressed as
(4) circulation step (2) and (3) are less than expected threshold value until cluster centre position restrains.
Wherein more preferably, according to the following formula, the signal strength RSSI of current point is determinediAffiliated subregion SK:
Sk=min { Manhattan_distance (RSSIi,RSSIu,Sk)}
Wherein, SkFor the class center of current sub-region, the nearest subregion of manhatton distance is found out after cycle calculations
Class center determines the subscript S of current sub-regionk；
Using following formula, coordinate mapping is carried out according to the data in WiFi fingerprint base, obtains the initial coordinate of current point:
(x0,y0)=min { Manhattan_distance (RSSIm,RSSIu,Sk,x,y)}
Wherein, Sk,x,yFor SkInterior fingerprint coordinate points.
Wherein more preferably, in the step 3, S is being determinedkWhen the region at place, the direction of rotary ultrasonic wave launcher makes
It is aligned to corresponding overlying regions.
It wherein more preferably, further include step 4: when initial coordinate and the difference of ultrasonic two-dimensional coordinate are greater than scheduled threshold value
When, step 2 is returned to, until initial coordinate and the difference of ultrasonic two-dimensional coordinate are less than scheduled threshold value.
According to a second aspect of the embodiments of the present invention, a kind of indoor positioning system mixed based on WiFi with ultrasonic wave is provided
System, including positioning terminal, server, ultrasonic receiver, multiple wireless routers and multiple ultrasonic transmitters, wherein described
Indoor locating system is for implementing above-mentioned indoor orientation method.
Compared with prior art, indoor orientation method provided by the present invention and its comprehensive WiFi indoor positioning skill of system
The feature of art and ultrasonic wave indoor positioning technologies respectively is clustered the WiFi finger print data being collected into using clustering algorithm,
Subregion locating for target is calculated using range equation, ultrasonic distance measurement is finally combined to carry out the accurate positioning of regional area.It should
Indoor orientation method and its system had not only reduced the influence of fingerprint location data complexity, but also overcame ultrasonic transmitter angle
Limited defect reduces the quantity of required ultrasonic transmitter.
Detailed description of the invention
Fig. 1 is the flow chart of the indoor orientation method provided by the present invention mixed based on WiFi with ultrasonic wave；
Fig. 2 is the schematic diagram that localization region is divided into k sub-regions；
Fig. 3 is the schematic diagram of the indoor locating system provided by the present invention mixed based on WiFi with ultrasonic wave.
Specific embodiment
Detailed specific description is unfolded to technical solution of the present invention in the following with reference to the drawings and specific embodiments.
It is preceding to have addressed, it, will be at if WiFi indoor positioning technologies and ultrasonic wave indoor positioning technologies learnt from other's strong points to offset one's weaknesses
For the contenders of indoor positioning technologies.For this purpose, present invention firstly provides a kind of rooms mixed based on WiFi with ultrasonic wave
Interior localization method, the technical thought taken is: a feature of the WiFi signal of acquisition current reference point or multiple spies first
Sign (preferably signal strength RSSI also may include other feature, for example, the multidiameter configuration of WiFi signal on some position, certain
Whether access point or base station, some position on the two-way time of WiFi signal or delay etc. can be detected on a position), it obtains
WiFi fingerprint constructs WiFi fingerprint base by method for normalizing；Later, target position is locked in single subregion, in conjunction with
High-precision ultrasonic distance measurement carries out the segmented positioning of regional area.In the following, detailed specific description is unfolded to this.
Fig. 1 is the flow chart of the indoor orientation method provided by the present invention mixed based on WiFi with ultrasonic wave.
In one embodiment of the invention, it is assumed that localization region area be S, according to the area S size of localization region with
And localization region is divided into k sub-regions S by indoor arrangement situationi(subregion SiIt is preferably impartial, but also do not repel unequal
The case where), i.e. localization region S=(S1,S2,…,Sk), referring specifically to Fig. 2.
P wireless router AP is disposed in the area S of the localization regionu,idu,1≤u≤p.It is adopted with the amplitude setting of 1m*1m
Sampling point simultaneously records coordinate value, it is assumed that m sampled point is arranged in localization region, the signal strength RSSI of each sampled point and position are believed
Breath indicates are as follows:
mv=(RSSIu,v、Si、idu、(x,y))
Wherein, RSSIu,vIndicate RSSI (signal strength), 1≤u≤p, 1≤v that u-th of AP is collected at sampled point v
≤m,SiIndicate the ith zone where sampled point, idu indicates that the id of u-th of wireless router, (x, y) indicate sampled point
Coordinate, above-mentioned k, p, m, u, i etc. are positive integer.
Step 1: obtaining WiFi fingerprint, construct WiFi fingerprint base
As shown in Figure 1, first by positioning terminal (such as locating base station configured with CC2530 chip or smart phone etc.)
Different location (i.e. different sampled points) in localization region obtains the RSSI of corresponding WiFi signal, and collects the position
RSSI and location information establish initial WiFi fingerprint base.
When establishing WiFi fingerprint base, in order to guarantee the timeliness and reliability of data, it can use positioning terminal and exist
Same position continuously records multiple RSSI to the same wireless router, seeks RSSI of the average value as the position of RSSI.
In order to reduce the influence of missing values, the data that the routing of specific position difference is collected are standardized, it may be assumed that
MAX={ J1,J2,…,Jp} (1)
MIN={ j1,j2,…,jp} (2)
In formula,
In formula, 1≤u≤p, 1≤v≤m, RP={ RSSI1,RSSI2,…,RSSIm, then each standardized feature value indicates
It is as follows:
Using above-mentioned formula (1)~(5), WiFi fingerprint base can be constructed by method for normalizing.
Step 2: clustering is carried out to the WiFi finger print data being collected into using clustering algorithm
In one embodiment of the invention, using K-means clustering algorithm, (or similar cluster based on division is calculated
Method, such as K-medoids algorithm, CLARANS algorithm etc.) by collected WiFi finger print data be polymerized to K class (K is positive integer, under
Together), the first of current point then is calculated using the manhatton distance at point (i.e. current point) locating for current signal strength and K class center
Beginning position.
It is described as follows:
Above-mentioned steps data set collected is all made of standardized feature vector, is clustered and is calculated using K-means
Method is divided into several groups, there is a center, several members in each group.Partiting step is as follows:
(1) K point is randomly chosen in localization region as cluster centre.
(2) successively calculate in localization region that each point, and will be closely located to the Euclidean distance between K cluster centre
Point is classified as one kind.Euclidean distance calculates as follows:
Wherein, vector RSSIj,kFor the RSSI value of location point j, vector y is some cluster centre value, and p is wireless router
Number, q be each position collecting sample number.
(3) all cluster centres are recalculated, remember TMidtFor the set of all member vectors' values of 1 cluster, idt is indicated should
The label of cluster, then the cluster centre value H of this clusteridtIt is expressed as
(4) circulation step (2) and (3) are less than expected threshold value until cluster centre position restrains.
After the completion of K-means clustering algorithm, the point in spatial distribution with similar signal strength can be polymerized to one kind,
Finally K cluster is polymerized in whole region.
Then, the signal strength RSSI of current point is determined according to formula (8)iAffiliated subregion SK, then utilize formula
(9) coordinate mapping is carried out according to the data in WiFi fingerprint base, obtains the initial coordinate of current point.
Sk=min { Manhattan_distance (RSSIi,RSSIu,Sk)} (8)
Wherein, SkFor the class center of current sub-region, the nearest son of manhatton distance can be found out after cycle calculations
Region class center determines the subscript S of current sub-regionk。
(x0,y0)=min { Manhattan_distance (RSSIm,RSSIu,Sk,x,y)} (9)
Wherein, Sk,x,yFor SkInterior fingerprint coordinate points.
According to the data in WiFi fingerprint base, the i.e. true coordinate of the signal strength and current point of various dimensions, in sub-district
Domain SkAfter interior progress new round search, the coordinate of the point of minimum range is assigned to current point as initial alignment value.
Step 3: target position being locked in single subregion, the subdivision for carrying out regional area in conjunction with ultrasonic distance measurement is fixed
Position
Next, in identified subregion SkInterior, the ultrasonic distance measurement of combined high precision carries out the accurate of regional area
Positioning.It is described as follows:
Determining SkWhen the region at place, the direction of rotary ultrasonic wave launcher makes it be aligned to corresponding overlying regions.
The range that ultrasonic wave positioning can adaptively be reduced in this way, the angle limitation that can also overcome ultrasonic wave to emit itself are asked
Topic.
Corresponding rotation angle can be determined in the following way: if current ultrasonic wave launcher is located at the region S
Right above center, then according to locating height HsonicAnd on the region S mapping point to locating subregion SkDistance Dk,xyJust
Value is cut, such as formula (10).
Θ=arctan (Hsonic/Dk,xy) (10)
In subregion SkIt is interior, pass through the distance d of the signal transmission of three ultrasonic transmitters received1, d2, d3To count
Coordinate value is calculated, such as formula (11).
Step 4: location model calibration
When initial coordinate and the difference of ultrasonic two-dimensional coordinate are greater than scheduled threshold value, step 2 is returned to, until initial
Until the difference of coordinate and ultrasonic two-dimensional coordinate is less than scheduled threshold value.It is specific to calculate referring to formula (12).
|(x0,y0)-(x_sonic,y_sonic) |≤1 (12)
The indoor orientation method provided by the present invention mixed based on WiFi with ultrasonic wave has been carried out specifically above
It is bright.Next, being further described the basic composition and work original of the indoor locating system for implementing above-mentioned indoor orientation method
Reason.
As shown in figure 3, in one embodiment of indoor locating system provided by the present invention, including positioning terminal, clothes
Business device, ultrasonic receiver, multiple wireless routers and multiple ultrasonic transmitters.Wherein, positioning terminal and ultrasonic wave receive
Device, which can integrate, to be integrated.Server can be realized by PC or laptop etc., for storing WiFi fingerprint base and executing
Three dimension location calculates.Multiple wireless routers and multiple ultrasonic transmitters are distributed in the different corners of the interior space, point
WiFi signal and ultrasonic signal are not emitted to positioning terminal.
In indoor locating system shown in Fig. 3, it is assumed that have a point to be determined (position i.e. where positioning terminal), utilize
Above-mentioned formula (5) standardizes the point to be determined, calculates point to be determined to the Europe between each cluster centre point using formula (6)
Point to be determined is assigned to that nearest one kind of Euclidean distance, the son where the point to be determined is judged using formula (8) by formula distance
The relevant location information of the point to be determined is substituted into the regression equation of the subregion by region, and using formula (9), that you can get it is undetermined
The coordinate in site.
Compared with prior art, indoor orientation method provided by the present invention and its comprehensive WiFi indoor positioning skill of system
The feature of art and ultrasonic wave indoor positioning technologies respectively is clustered the WiFi finger print data being collected into using clustering algorithm,
Subregion locating for target is calculated using range equation, ultrasonic distance measurement is finally combined to carry out the accurate positioning of regional area.It should
Indoor orientation method and its system had not only reduced the influence of fingerprint location data complexity, but also overcame ultrasonic transmitter angle
Limited defect reduces the quantity of required ultrasonic transmitter.
The indoor orientation method provided by the present invention mixed based on WiFi with ultrasonic wave and its system are carried out above
Detailed description.For those of ordinary skill in the art, it is done under the premise of without departing substantially from true spirit
Any obvious change, will all constitute the infringement weighed to the invention patent, corresponding legal liabilities will be undertaken.
Claims (10)
1. a kind of indoor orientation method mixed based on WiFi with ultrasonic wave, it is characterised in that include the following steps:
Step 1: obtaining WiFi fingerprint, construct WiFi fingerprint base；
Step 2: clustering is carried out to the WiFi finger print data being collected into using clustering algorithm；
Step 3: target position being locked in single subregion, the segmented positioning of regional area is carried out in conjunction with ultrasonic distance measurement.
2. the indoor orientation method mixed as described in claim 1 based on WiFi with ultrasonic wave, it is characterised in that:
In the step 1, the different location by positioning terminal in localization region obtains the feature of corresponding WiFi signal, and collects
The feature and location information of the position construct the WiFi fingerprint base by method for normalizing.
3. the indoor orientation method mixed as claimed in claim 2 based on WiFi with ultrasonic wave, it is characterised in that:
The feature for continuously recording multiple WiFi signal to the same wireless router in same position using positioning terminal, seeks putting down
Feature of the mean value as the WiFi signal of the position.
4. the indoor orientation method mixed as claimed in claim 2 or claim 3 based on WiFi with ultrasonic wave, it is characterised in that:
The feature of the WiFi signal include but is not limited to signal strength, multidiameter configuration, whether can detect access point or base station,
Two-way time or delay in any one or more.
5. the indoor orientation method mixed as described in claim 1 based on WiFi with ultrasonic wave, it is characterised in that:
In the step 2, collected WiFi finger print data is polymerized to K class using K-means clustering algorithm, then using current
The locating point of signal strength calculates the initial position of current point with the manhatton distance at K class center, and wherein K is positive integer.
6. the indoor orientation method mixed as claimed in claim 5 based on WiFi with ultrasonic wave, it is characterised in that will be collected
WiFi finger print data be polymerized to K class, including following sub-step:
(1) K point is randomly chosen in localization region as cluster centre；
(2) each point in localization region is successively calculated to return to the Euclidean distance between K cluster centre, and by closely located point
For one kind；Euclidean distance calculates as follows:
Wherein, vector RSSIj,kFor the RSSI value of location point j, vector y is some cluster centre value, and p is of wireless router
Number, q are the collecting sample number of each position；
(3) all cluster centres are recalculated, remember TMidtFor the set of all member vectors' values of 1 cluster, idt indicates the cluster
Label, then the cluster centre value H of this clusteridtIt is expressed as
(4) circulation step (2) and (3) are less than expected threshold value until cluster centre position restrains.
7. the indoor orientation method mixed as claimed in claim 6 based on WiFi with ultrasonic wave, it is characterised in that:
According to the following formula, the signal strength RSSI of current point is determinediAffiliated subregion SK:
Sk=min { Manhattan_distance (RSSIi,RSSIu,Sk)}
Wherein, SkFor the class center of current sub-region, found out after cycle calculations in the nearest subregion class of manhatton distance
The heart determines the subscript S of current sub-regionk；
Using following formula, coordinate mapping is carried out according to the data in WiFi fingerprint base, obtains the initial coordinate of current point:
(x0,y0)=min { Manhattan_distance (RSSIm,RSSIu,Sk,x,y)}
Wherein, Sk,x,yFor SkInterior fingerprint coordinate points.
8. the indoor orientation method mixed as described in claim 1 based on WiFi with ultrasonic wave, it is characterised in that:
In the step 3, S is being determinedkWhen the region at place, the direction of rotary ultrasonic wave launcher makes it be aligned to corresponding area
Above domain.
9. the indoor orientation method mixed as described in claim 1 based on WiFi with ultrasonic wave, it is characterised in that further include step
Rapid 4:
When initial coordinate and the difference of ultrasonic two-dimensional coordinate are greater than scheduled threshold value, step 2 is returned to, until initial coordinate
And until the difference of ultrasonic two-dimensional coordinate is less than scheduled threshold value.
10. a kind of indoor locating system mixed based on WiFi with ultrasonic wave, including positioning terminal, server, ultrasonic wave are received
Device, multiple wireless routers and multiple ultrasonic transmitters, it is characterised in that the indoor locating system is wanted for implementing right
Indoor orientation method described in asking any one of 1~9.
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| CN114339600A (en) * | 2022-01-10 | 2022-04-12 | 浙江德清知路导航科技有限公司 | Electronic equipment indoor positioning system and method based on 5G signal and sound wave signal |
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