CN104635206B - A kind of method and device of wireless location - Google Patents
A kind of method and device of wireless location Download PDFInfo
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- CN104635206B CN104635206B CN201310571669.1A CN201310571669A CN104635206B CN 104635206 B CN104635206 B CN 104635206B CN 201310571669 A CN201310571669 A CN 201310571669A CN 104635206 B CN104635206 B CN 104635206B
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S5/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
- G01S5/02—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations using radio waves
- G01S5/0278—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations using radio waves involving statistical or probabilistic considerations
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S5/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
- G01S5/02—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations using radio waves
- G01S5/14—Determining absolute distances from a plurality of spaced points of known location
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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
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- General Physics & Mathematics (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Probability & Statistics with Applications (AREA)
- Position Fixing By Use Of Radio Waves (AREA)
- Complex Calculations (AREA)
- Mobile Radio Communication Systems (AREA)
Abstract
The present invention provides a kind of method and device of wireless location, and this method includes：Acquire the received signal strength of multiple known reference points respectively on tested point；The valued space of tested point position is estimated according to the received signal strength；The tested point position valued space that estimation obtains is divided into multiple equal-sized grids；Corresponding Pearson product-moment correlation coefficient is solved, and determines minimum Pearson product-moment correlation coefficient ρL, by the ρLLocational space of the grid as tested point where corresponding position.The wireless location of degree of precision can be realized with lower computation complexity through the invention.
Description
Technical field
The present invention relates to the communications fields, more particularly to a kind of method and device of wireless location.
Background technology
Due to received signal strength（RSS）Information is easy to get, is at low cost, therefore the wireless location based on RSS has obtained generally
Concern and extensive use.Usually the positioning based on RSS can be divided into two major classes：Location fingerprint identification positioning is positioned with triangle.
The former needs to pre-establish database, and as environmental change updates the data library, the cost for building library and maintenance is higher, thus at present
Mostly used in laboratory, building etc., it is not yet a wide range of universal.The latter's passage path loss model calculates tested point and known ginseng
Then distance between examination point does triangle positioning according to known reference point position and estimated distance.It is this to be positioned based on triangle
Scheme it is simple and practicable, the fields such as business, scientific research obtain extensive use.However since wireless signal is easily by environmental change
Influence, the estimation of unknown path loss model is very difficult, thus affects the use of triangle locating scheme.
It is existing to research and propose to solve the triangle orientation problem based on RSS in the case of unknown path loss model
Several solutions below：[1]The Combined estimator problem of path loss index and position is modeled as nonlinear optimal problem, and
Based on Levenberg-Marquardt（Literary Burger-the Ma Kuaertefa of row）Algorithm solves the problem；[2]Based on root axis definition away from
From compatibility, and by maximizing the compatible dynamic estimation path loss index of distance, and then triangle algorithm is carried out using it
Positioning；[3]The Combined estimator of path loss index and position is modeled and uses Gaussian- after forming nonlinear optimal problem
Seidel（Gauss-Sai get Er）Algorithm is solved；[4]By reducing the dimension of Jacobian matrix come Jian Hua [1]In
The complexity that Lavenberg-Marquardt is realized；[5]Original is contained into 3 variables by linearizing path loss model processing
Path loss index and the Combined estimator problem of position be changed into univariate optimization problem and solved, and in the hope of value
[ is substituted into as initial value;4]To further increase positioning accuracy in scheme.
Although above-mentioned five kinds of schemes can solve the orientation problem under unknown path loss model, there is also respective
It is insufficient.[1]Calculate the selection that complicated and result is limited to initial value；[2]In distance compatibility under noisy communication channel be easy hair
Raw mistake, and then lead to the path loss index and location estimation of mistake；[3]In non-linear Gaussian-Seidel algorithms
It does not guarantee that and exports globally optimal solution in non-convex optimization problem, as a result also depend on the selection of suitable initial value；[4]Although
Jian Hualiao [1]Application, but complexity remains unchanged not low, and Ji Chengliao [1]As a result the problem of being limited to initial value；[5]To non-thread
The path loss model of property has carried out linearization process, has lost details and introduces error, complexity is not also low.
Invention content
The technical problem to be solved in the present invention is to provide a kind of method and devices of wireless location, lower can calculate multiple
Miscellaneous degree realizes the wireless location of degree of precision.
In order to solve the above technical problem, the present invention provides a kind of methods of wireless location, including：
Acquire the received signal strength of multiple known reference points respectively on tested point；
The valued space of tested point position is estimated according to the received signal strength；
The tested point position valued space that estimation obtains is divided into multiple equal-sized grids；
Corresponding Pearson product-moment correlation coefficient is solved, and determines minimum Pearson product-moment correlation coefficient ρL, by the ρLIt is right
Answer locational space of the grid where position as tested point.
Further, the above method also has the characteristics that following：The tested point position valued space that estimation is obtained is drawn
Being divided into multiple equal-sized grids includes：
The tested point position valued space that estimation obtains is divided into m equal-sized, area s2m2Square net
Lattice, with the center of each gridAs all position probable values of tested point, the selection of s by
Expected iterations and positioning accuracy request determine.
Further, the above method also has the characteristics that following：It is described to solve corresponding Pearson product-moment correlation coefficient ρl(l=
1,2 ..., m) it is to be realized by following formula：
Wherein, kiFor the received signal strength measurement number from i-th of reference point
Mesh, ri,jFor j-th of the received signal strength received from i-th of reference point, j=1,2 ..., ki；
(xi,yi) be the known reference point position, i=1,2 ... N, N
≥3。
Further, the above method also has the characteristics that following：The grid corresponding positionIt is obtained by following formula：
To solve the above-mentioned problems, the present invention also provides a kind of devices of wireless location, wherein including：
Acquisition module, the received signal strength for acquiring multiple known reference points respectively on tested point；
Estimation module, the valued space for estimating tested point position according to the received signal strength；
The tested point position valued space that estimation obtains is divided into multiple equal-sized grids by division module；
Processing module solves corresponding Pearson product-moment correlation coefficient, and determines minimum Pearson product-moment correlation coefficient
ρL, by the ρLLocational space of the grid as tested point where corresponding position.
Further, above-mentioned apparatus also has the characteristics that following：
It is a equal in magnitude to be divided into m specifically for the tested point position valued space for obtaining estimation for the division module
, area s2m2Square net, with the center of each gridInstitute as tested point
There are position probable value, the selection of s to be determined by expected iterations and positioning accuracy request.
Further, above-mentioned apparatus also has the characteristics that following：
The solution module is to solve corresponding Pearson product-moment correlation coefficient ρ by following formulal(l=1,2 ..., m),
Wherein,
kiFor the received signal strength measurement number from i-th of reference point, ri,jIt is received from i-th of reference point
J-th of received signal strength, j=1,2 ..., ki；(xi,yi) it is the known ginseng
The position of examination point, i=1,2 ... N, N >=3.
Further, above-mentioned apparatus also has the characteristics that following：The ρLCorresponding positionIt is obtained by following formula：
The present invention provides a kind of method and device of wireless location, can realize degree of precision with lower computation complexity
Wireless location.
Description of the drawings
Fig. 1 is a kind of flow chart of the method for wireless location of the embodiment of the present invention.
Fig. 2 is a kind of schematic diagram of the device of wireless location of the embodiment of the present invention；
Fig. 3 is the result schematic diagram of the embodiment of the present invention.
Specific implementation mode
To make the objectives, technical solutions, and advantages of the present invention clearer, below in conjunction with attached drawing to the present invention
Embodiment be described in detail.It should be noted that in the absence of conflict, in the embodiment and embodiment in the application
Feature mutually can arbitrarily combine.
The embodiment of the present invention measures the RSS information from N (N >=3) a known reference point on tested point, utilizes these
RSS information estimates tested point position.Assuming that destination node is located at (x, y)；The known location of reference point is (xi,yi)(i=1,2,…
N)；It is k that RSS from i-th of reference point, which measures number,i, j-th of the RSS received from i-th of reference point is ri,j(j=1,
2,…,ki).According to the path loss model of radio transmission, ri,jIt can be given by：
Wherein, α is the power received at range transmission antenna 1m；N is path loss index, should according to existing research
The value range of value is usually：2≤n≤5；ωjShadow fading is represented, its obedience is often assumed that in wireless transmission model research
Gaussian Profile, such as ωj~N (0, σ2)。
IfAbove-mentioned ri,jExpression formula can be reduced to：ri,j=α-10nβi+ωj。
Accordingly, r can be easily foundi,jAnd βiIt is linearly related.Further by 2≤n≤5 it is found that ri,jWith βiLinear negative correlation.
Degree of correlation between usual two variables can be described with Pearson product-moment correlation coefficient ρ.Pearson product-moment
The value range of related coefficient is -1≤ρ≤1, ρ >0 indicates two variable positive correlations, i.e., a variable is with another variable
Increase and increases；ρ<0 indicates that two variable negative correlation, i.e. a variable reduce with the increase of another variable；ρ=0 is indicated
Two variables are not linearly related；ρ=± 1 means that two variables can be described with good linear equation, i.e. two variables
Value all fall on same straight line.
Since accurate tested point location estimation meets expression formula ri,j=α-10nβi+ωj, i.e., accurate location estimation should make
ri,jWith βiMeet linear negative correlativing relation, therefore the estimation problem of tested point position can be converted to and solve following Pearson product-moments
The minimization problem of related coefficient：
I.e.：Wherein,
On the basis of establishing above-mentioned model, it is above-mentioned to solve that the embodiment of the present invention proposes a kind of simple and practicable algorithm
Minimization problem.The algorithm iteratively solves tested point position using the thought of classification processing：Located space is discretized into first
Several localization regions are calculated by Pearson product-moment correlation coefficient located space being contracted to some region；Then selected
Zonule in repeat previous step until stopping criterion for iteration meet.
The value of s and m can change in above-mentioned each iteration.
Wireless location problem based on RSS under unknown path loss model is modeled as minimizing Pierre by the embodiment of the present invention
The optimization problem of inferior product moment correlation coefficient, and simple and practicable iterative solution algorithm is given, compared to the prior art, Ke Yi
It is directly realized and is accurately positioned with lower complexity in the case of without estimated path loss index.Although institute of the embodiment of the present invention
Carrying algorithm, there is no Combined estimator path loss model parameters, but after obtaining location estimation, and path loss model parameters can be with
Easily directly it is calculated according to linear regression.
The embodiment of the present invention proposes the wireless location scheme based on RSS in the case of a kind of unknown path loss model.It should
Scheme has been modeled as minimum Pearson product-moment phase first with RSS, by the wireless location problem under unknown path loss model
Then the problem of relationship number gives simple and practicable derivation algorithm.Its specific implementation process is as shown in Figure 1, including following step
Suddenly：
101, on tested point, acquisition respectively comes from the RSS of N (N >=3) a known reference point, and each reference point RSS's adopts
Integrate sample number as ki(i=1,2 ... N) are a, it is known that the position of reference point isJ-th from i-th of reference point
RSS is ri,j(j=1,2,…,ki)。
Wherein, the acquisition of reference point locations can be by GPS（GPS）, manually estimation, map, CAD software
（CAD）Etc. different approaches obtain)；RSS samples can be by being equipped with laptop, the PDA of wireless network card（It is a
People's digital assistant）, the collections such as smart mobile phone.
By taking the collection of Wi-Fi RSS signals as an example, installation is wireless on the laptop of operation Window operating systems
After network monitoring software, you can runs software collects the RSS of surrounding Wi-Fi access points.
The location estimation problem of tested point is modeled according to the definition of Pearson product-moment correlation coefficient and path loss model
At Pearson product-moment correlation coefficient problem is minimized, i.e.,：
102, the valued space of estimation tested point position.
Utilize the transmission range of the RSS, wireless signal received on known reference point position, tested point and other（Such as
Building, area etc. residing for tested point）The valued space x ∈ [ of information rough estimate tested point position in relation to tested point position;X1,
X2],y∈[Y1,Y2]。
Such as：If known tested point in some floor, can the floor coordinate space taking as tested point position
It is worth space；If first can not estimate that tested point position is according to centroid algorithm with the relevant reference information in tested point positionAnd the length of side is done centered on the point for the square of 2D, using it as the value of tested point position sky
Between.Wherein, D is the corresponding wireless transmission distance of wireless communication technique, outdoor if the indoor transmissions distance of 802.11g is about 38m
Transmission range is about 140m.
The tested point position valued space that estimation obtains is divided into more by 103, the position valued space of discretization tested point
A equal-sized grid.
The tested point position valued space that step 102 estimation obtains is divided into m equal-sized, area s2m2's
Square net, with the center of each gridAll position probable values as tested point.Its
In, the selection of s is determined by expected iterations and positioning accuracy request, it is contemplated that iterations less, positioning accuracy request more
The value of height, s is smaller.
104, corresponding Pearson product-moment correlation coefficient is solved, and determines minimum Pearson product-moment correlation coefficient ρlIt is corresponding
Locational space：By all tested point possible positionsSubstitute into following formula：
Solve corresponding Pearson product-moment correlation coefficient ρl(l=1,2 ..., m), and it is related to find minimum Pearson product-moment
Coefficient ρL, by the ρLIt is correspondingLocational space of the grid at place as tested point.
Step 103-104 is repeated, until stopping criterion for iteration meets.The minimum Pearson product-moment correlation coefficient obtained at this time
ρLCorresponding positionThe position estimation value as to be solved
Stopping criterion for iteration can obtain requirement in practical systems decision according to positioning accuracy, operation time, such as if it is desired to position
Precision is 1m magnitudes, and iteration can be set to terminate as s≤1m.
So far, the orientation problem based on RSS solves in the case of completing unknown path loss model.
Fig. 2 is a kind of schematic diagram of the device of wireless location of the embodiment of the present invention, as shown in Fig. 2, the dress of the present embodiment
Set including：
Acquisition module, the received signal strength for acquiring multiple known reference points respectively on tested point；
Estimation module, the valued space for estimating tested point position according to the received signal strength；
The tested point position valued space that estimation obtains is divided into multiple equal-sized grids by division module；
Processing module solves corresponding Pearson product-moment correlation coefficient, and determines minimum Pearson product-moment correlation coefficient
ρL, by the ρLLocational space of the grid as tested point where corresponding position.
Wherein, the division module specifically can be used for the tested point position valued space that estimation obtains being divided into m
Equal-sized, area s2m2Square net, with the center of each gridAs waiting for
All position probable values of measuring point, the selection of s are determined by expected iterations and positioning accuracy request.
Wherein, the solution module is that corresponding Pearson product-moment correlation coefficient ρ can be solved by following formulal(l=1,
2 ..., m),
Wherein,
kiFor the received signal strength measurement number from i-th of reference point, ri,jIt is received from i-th of reference point
J-th of received signal strength, j=1,2 ..., ki；(xi,yi) it is the known ginseng
The position of examination point, i=1,2 ... N, N >=3.
The ρLCorresponding positionIt is obtained by following formula：
A specific wireless location embodiment is given below.The embodiment is entitled using Mannheim, Germany university
For the experimental data used in the Wi-Fi positioning systems of COMPASS.Experiment scene is about 15m one wide, length is about 36m,
Office floor.The Wi-Fi access points of 14 known locations are shared in the Administrative Area.Laboratory data base is included in 612
The collected RSS from this 14 access points in known location test point, wherein the RSS sample numbers acquired in each test point
It is 110.It is different with reference to points in order to investigate（I.e. different N）In the case of the invention positioning performance, be with actual position below
（7.125 6.269）Access point A as tested point, randomly selected from 612 known location test points it is N number of as reference
Point carries out detailed position fixing process explanation.
Illustrated according to above-mentioned implementing procedure, if total iterations are twice, the s of first time iteration is 3, second of iteration
S be 1, then the positioning of test point can be specifically described as：
201, it is selected from 612 known location test points at random N number of as a reference point, while choosing its corresponding RSS.
The position valued space of test point, x ∈ [ are determined by known office building space;0,36],y∈[0,15], i.e. position
Long L=36 in space, wide W=15.
202, the space of points to be measured is changed and is divided into 60 3 × 3m2Grid, i.e. m=60, s=3.With the central point of each grid
As the possibility value of tested point position, then have：
203, according to Pearson product-moment correlation coefficient equations ρlAnd determine minimum Pearson product-moment correlation coefficient ρLIt is corresponding
Locational space.
204,202-203 steps, s=1 at this time, m=9, with minimum ρ are repeatedLCorresponding positionAs test point
Position estimation value.
If with root-mean-square error（RMSE）For performance indicator, then the present invention that 10000 Monte-Carlo Simulations obtain is implemented
The positioning result of example can be provided by Fig. 2, and the positioning performance of the program is improved with the increase of reference point quantity as seen from the figure.With
For points N=10, the positioning RMSE of the embodiment of the present invention is 3.066m at this time, compared to traditional centroid localization algorithm
Background 7.852m and Ji Shufangan [1]41.027m, there is about 61% and 92.6% to significantly improve respectively（Background technology Fang An [1]
The big reason of error is have successive ignition not converge in global optimum in 10000 Monte-Carlo Simulations）.If with
Error intermediate value is as performance indicator, then when being N=10 with reference to points, the position error of the embodiment of the present invention is 2.0125m, phase
Compared with the 7.0028m and background technology Fang An [ of centroid algorithm;1]3.1413m, also have respectively nearly 71.3% and 35.6% it is notable
It improves.Although in addition, the more simplest centroid algorithm of the algorithm of the embodiment of the present invention is complicated, complexity is still relatively low, when N=
When 10, doing 10000 positioning with Intel Core i5 only needs 144s, compared to background technology Fang An [1]988s, saved nearly 85.4%
Time.In addition, the embodiment of the present invention can also be by increasing reference point, increasing grid in iterations, reduction iteration
Size etc. further increases positioning accuracy.
One of ordinary skill in the art will appreciate that all or part of step in the above method can be instructed by program
Related hardware is completed, and described program can be stored in computer readable storage medium, such as read-only memory, disk or CD
Deng.Optionally, all or part of step of above-described embodiment can also be realized using one or more integrated circuits.Accordingly
Ground, the form that hardware may be used in each module/unit in above-described embodiment are realized, the shape of software function module can also be used
Formula is realized.The present invention is not limited to the combinations of the hardware and software of any particular form.
It these are only the preferred embodiment of the present invention, certainly, the invention may also have other embodiments, without departing substantially from this
In the case of spirit and its essence, those skilled in the art make various corresponding changes in accordance with the present invention
And deformation, but these corresponding change and deformations should all belong to the protection domain of appended claims of the invention.
Claims (8)
1. a kind of method of wireless location, including：
Acquire the received signal strength of multiple known reference points respectively on tested point；
The valued space of tested point position is estimated according to the received signal strength, and executes subsequent step；
Step (a)：Obtained tested point position valued space is divided into multiple equal-sized grids；
Step (b)：The Pearson product-moment correlation coefficient of the grid is solved, and determines minimum Pearson product-moment correlation coefficient ρL,
By the ρLCorresponding positionLocational space of the grid at place as tested point；
Repeating said steps (a)-(b), until stopping criterion for iteration meets, the minimum Pearson product-moment correlation coefficient obtained at this time
ρLCorresponding positionThe position estimation value as to be solved.
2. the method as described in claim 1, it is characterised in that：It is described obtained tested point position valued space is divided into it is more
A equal-sized grid includes：
Obtained tested point position valued space is divided into m equal-sized, area s2m2Square net, with every
The position of the central point of a gridAll position probable values as tested point；Wherein, the selection of l=1,2 ..., m, s
It is determined by expected iterations and positioning accuracy request.
3. method as claimed in claim 2, it is characterised in that：The Pearson product-moment correlation coefficient ρ for solving the gridl
It is to be realized by following formula：
Wherein,kiFor the received signal strength measurement number from i-th of reference point, ri,j
For j-th of the received signal strength received from i-th of reference point, j=1,2 ..., ki；
(xi,yi) be the known reference point position, (x, y) be tested point position
It sets, ρlFor the Pearson product-moment correlation coefficient of the grid, i=1,2 ... N, N >=3.
4. method as claimed in claim 3, it is characterised in that：The ρLCorresponding positionIt is obtained by following formula：
5. a kind of device of wireless location, which is characterized in that including：
Acquisition module, the received signal strength for acquiring multiple known reference points respectively on tested point；
Estimation module, the valued space for estimating tested point position according to the received signal strength；
The tested point position valued space that estimation obtains is divided into multiple equal-sized grids by division module, or will processing
The locational space for the tested point that module obtains is divided into multiple equal-sized grids；
Processing module solves the Pearson product-moment correlation coefficient of the grid, and determines minimum Pearson product-moment correlation coefficient
ρL, by the ρLCorresponding positionLocational space of the grid at place as tested point；It, will when stopping criterion for iteration meets
The minimum Pearson product-moment correlation coefficient ρ obtained at this timeLCorresponding positionAs the position estimation value to be solved.
6. device as claimed in claim 5, it is characterised in that：
The division module obtains to be measured specifically for the tested point position valued space for obtaining estimation or by processing module
The locational space of point is divided into m equal-sized, area s2m2Square net, with the position of the central point of each grid
It setsAll position probable values as tested point；Wherein, the selection of l=1,2 ..., m, s by expected iterations and
Positioning accuracy request determines.
7. device as claimed in claim 6, it is characterised in that：
The processing module is to solve corresponding Pearson product-moment correlation coefficient ρ by following formulal,
Wherein,
kiFor the received signal strength measurement number from i-th of reference point, ri,jFor j-th received from i-th of reference point
Received signal strength, j=1,2 ..., ki；(xi,yi) it is the known reference point
Position, (x, y) are the position of tested point, ρlFor the Pearson product-moment correlation coefficient of the grid, i=1,2 ... N, N >=3.
8. device as claimed in claim 7, it is characterised in that：The ρLCorresponding positionIt is obtained by following formula：
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| PCT/CN2014/080718 WO2015070613A1 (en) | 2013-11-14 | 2014-06-25 | Wireless positioning method and device |
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| CN107454669A (en) * | 2016-05-31 | 2017-12-08 | 中国人民解放军理工大学 | A kind of gunz localization method based on signal intensity correlation analysis |
| CN108716918B (en) * | 2018-04-24 | 2021-08-24 | 合肥工业大学 | RSSI indoor positioning algorithm based on grid clustering |
| CN110673181B (en) * | 2019-08-19 | 2022-03-22 | 中国电波传播研究所（中国电子科技集团公司第二十二研究所） | GNSS interference source positioning method based on grid energy traversal search |
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| JP6300922B2 (en) | 2018-03-28 |
| WO2015070613A1 (en) | 2015-05-21 |
| CN104635206A (en) | 2015-05-20 |
| JP2017501389A (en) | 2017-01-12 |
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