CN105848109B - A kind of localization method of interior Internet of Things active label - Google Patents
A kind of localization method of interior Internet of Things active label Download PDFInfo
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- 238000000034 method Methods 0.000 title claims abstract description 23
- 230000004807 localization Effects 0.000 title claims abstract description 16
- 238000012216 screening Methods 0.000 claims abstract description 4
- 238000012937 correction Methods 0.000 claims description 17
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- 230000002159 abnormal effect Effects 0.000 claims description 4
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- 230000004888 barrier function Effects 0.000 description 15
- 238000012545 processing Methods 0.000 description 7
- 230000005540 biological transmission Effects 0.000 description 3
- 230000000903 blocking effect Effects 0.000 description 2
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- H04W4/04—
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06K—GRAPHICAL DATA READING; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K7/00—Methods or arrangements for sensing record carriers, e.g. for reading patterns
- G06K7/10—Methods or arrangements for sensing record carriers, e.g. for reading patterns by electromagnetic radiation, e.g. optical sensing; by corpuscular radiation
- G06K7/10009—Methods or arrangements for sensing record carriers, e.g. for reading patterns by electromagnetic radiation, e.g. optical sensing; by corpuscular radiation sensing by radiation using wavelengths larger than 0.1 mm, e.g. radio-waves or microwaves
- G06K7/10297—Methods or arrangements for sensing record carriers, e.g. for reading patterns by electromagnetic radiation, e.g. optical sensing; by corpuscular radiation sensing by radiation using wavelengths larger than 0.1 mm, e.g. radio-waves or microwaves arrangements for handling protocols designed for non-contact record carriers such as RFIDs NFCs, e.g. ISO/IEC 14443 and 18092
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04B—TRANSMISSION
- H04B17/00—Monitoring; Testing
- H04B17/30—Monitoring; Testing of propagation channels
- H04B17/309—Measuring or estimating channel quality parameters
- H04B17/318—Received signal strength
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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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- 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
- H04W64/006—Locating users or terminals or network equipment for network management purposes, e.g. mobility management with additional information processing, e.g. for direction or speed determination
Abstract
The present invention provides a kind of localization method of indoor Internet of Things active label, carries out preliminary screening and grouping including the signal strength data to the received Internet of Things active label of each reader；The initial coordinate of Internet of Things active label is calculated using packet data；Amendment is iterated to the initial coordinate of Internet of Things active label, obtains the final coordinate of Internet of Things active label.The present invention realizes the three-dimensional localization to Internet of Things active label indoor location, is not necessarily to human intervention, positioning accuracy is high, speed is fast by calculating the signal strength for being mounted on the collected Internet of Things active label of indoor multiple readers and iteration.
Description
Technical field
The present invention relates to Internet of Things radio frequency field of locating technology, the positioning side of specifically a kind of interior Internet of Things active label
Method.
Background technique
Internet of Things active label position error under the conditions of computer room is larger at present, and it is accurately and effectively three-dimensional fixed to cannot achieve
Position.Indoor Internet of Things radio frequency location technology has extremely important value in equipment management field, realize it is a kind of reliable, efficiently,
Accurate localization method is very necessary to the requirement for reaching practical application.
Summary of the invention
It is indoor according to being mounted on the purpose of the present invention is to provide a kind of localization method of indoor Internet of Things active label
The signal strength of multiple collected Internet of Things active labels of reader is realized by calculating and iteration to the active mark of Internet of Things
The three-dimensional localization of label.
The technical solution of the present invention is as follows:
A kind of localization method of interior Internet of Things active label, method includes the following steps:
(1) preliminary screening and grouping are carried out to the signal strength data of the received Internet of Things active label of each reader；
(2) initial coordinate of Internet of Things active label is calculated using packet data；
(3) amendment is iterated to the initial coordinate of Internet of Things active label, obtains the final seat of Internet of Things active label
Mark.
The localization method of the indoor Internet of Things active label, the step (2), specifically includes the following steps:
(21) use following formula, be calculated each reader to Internet of Things active label theoretical distance:
PLA=P0-PL(d0)
Wherein, djIndicate theoretical distance of j-th of reader to Internet of Things active label, prjIndicate that j-th of reader connects
The signal strength of the Internet of Things active label of receipts, η indicate that signal attenuation coefficient, PLA are indicated apart from Internet of Things active label d0Place
Signal strength, P0Indicate the rated power intensity of Internet of Things active label, PL (d0) indicate apart from Internet of Things active label d0Place
Signal attenuation, d0Indicate reference distance；
(22) signal strength data of the received Internet of Things active label of each reader is compared, therefrom chooses letter
Internet of Things active label is calculated using following formula as reference mode in number maximum three readers of strength reception value
X-axis, y-axis initial coordinate:
Wherein, x0、y0Respectively indicate x-axis, the y-axis initial coordinate of Internet of Things active label, xA、xB、xCRespectively indicate three
The x-axis coordinate of reference mode, yA、yB、yCRespectively indicate the y-axis coordinate of three reference modes, dA、dB、dCRespectively indicate three ginsengs
Examine node to Internet of Things active label theoretical distance；
(23) use following formula, be calculated each reader and projection of the Internet of Things active label on x/y plane away from
From:
Wherein, vdjIndicate j-th of reader and projector distance of the Internet of Things active label on x/y plane, xj、yjRespectively
Indicate the x-axis, y-axis coordinate of j-th of reader；
(24) following formula is used, height of each reader relative to Internet of Things active label is calculated:
Wherein, zdjIndicate height of j-th of reader relative to Internet of Things active label, HjIndicate j-th of reader
Highly；
(25) following formula is used, the z-axis initial coordinate of Internet of Things active label is calculated:
Wherein, z0Indicate the z-axis initial coordinate of Internet of Things active label, n indicates the total number of reader.
The localization method of the indoor Internet of Things active label, in the step (3), to Internet of Things active label just
Beginning coordinate is iterated amendment, specifically includes the following steps:
(31) initial coordinate for assuming Internet of Things active label is (x0,y0,z0), each reader to the active mark of Internet of Things
The inceptive direction vector of label are as follows:
Vj=(x0-xj,y0-yj,z0-zj)
Wherein, VjIndicate inceptive direction vector of j-th of reader to Internet of Things active label, (xj,yj,zj) indicate jth
The coordinate of a reader；
(32) using air as special obstacle object, it is assumed that the signal propagation path between Internet of Things active label and reader
It is divided into N sections by barrier, final stage road is passed through based on the signal that reader received signal intensity is Internet of Things active label
Signal strength when diameter, using following anti-recurrence formula, the signal that iteration extrapolates Internet of Things active label passes through the preceding paragraph road
The signal strength of diameter, until Pm≥P0When terminate:
Wherein, PmIndicate the signal strength obtained at anti-recursion m times, P0Indicate that the rated power of Internet of Things active label is strong
Degree, PiIndicate that the signal of Internet of Things active label passes through i-th, i=N, the signal strength in section path N-1 ..., N-m+1, Pi-1Table
Show that the signal of Internet of Things active label passes through the signal strength in (i-1)-th section of path, ηiIndicate the signal decaying system in i-th section of path
Number, diIndicate the length in i-th section of path, l indicates the rated power strength retrogression of Internet of Things active label to PiWhen signal propagate
Theoretical distance, l-diIndicate the rated power strength retrogression of Internet of Things active label to Pi-1When signal propagate theoretical distance, X
Indicate standard variance；
As i=N, PN=prj, PNIt indicates when the signal of Internet of Things active label passes through final stage i.e. N sections of paths
Signal strength, prjIndicate j-th of reader received signal intensity；
(33) use following formula, be calculated each reader to Internet of Things active label correction distance:
Wherein, DjIndicate correction distance of j-th of reader to Internet of Things active label, diIndicate i-th, i=N, N-
1 ..., the length in N-m+1 sections of paths；
(34) the inceptive direction vector of each reader to Internet of Things active label is modified, obtains amendment direction arrow
Amount, and use following formula, be calculated each reader along its it is corresponding amendment direction vector direction and be located at correction away from
Coordinate from place:
Wherein, VRjJ-th of reader is indicated along the direction of its corresponding amendment direction vector and is located at correction distance DjPlace
Coordinate, i.e. new coordinate of the Internet of Things active label based on j-th of reader, RjIndicate the phasor coordinate of j-th of reader, V 'j
Indicate j-th of reader to Internet of Things active label amendment direction vector；
(35) following formula is used, inceptive direction vector and amendment direction to each reader to Internet of Things active label
Angle between vector carries out linear transformation:
Wherein, θjIndicate j-th of reader to Internet of Things active label inceptive direction vector and amendment direction vector it
Between angle, β is constant,Angle after indicating conversion；
(36) VR is chosenj, any four point forms several tetrahedrons in j=1,2 ..., n, wherein n indicates reader
Total number center coordination is weighted to each tetrahedron using following formula, obtain newly-generated point:
Wherein, (x, y, z) indicates the coordinate of newly-generated point, (x1,y1,z1)、(x2,y2,z2)、(x3,y3,z3)、(x4,y4,
z4) coordinate for forming some tetrahedral four point is respectively indicated, It respectively indicates and forms the tetrahedron
The corresponding reader of four points to Internet of Things active label inceptive direction vector and amendment direction vector between angle line
Property conversion after value, pr1、pr2、pr3、pr4It respectively indicates the corresponding reader of composition tetrahedral four points and receives Internet of Things
The signal strength of active label；
Several new tetrahedrons are formed with newly-generated point again, repeat above-mentioned operation, until of last remaining point
Number calculates the average value of the coordinate of remaining point, the amendment coordinate as Internet of Things active label less than 4；
(37) it using the amendment coordinate of the calculated Internet of Things active label of step (36) as initial coordinate, repeats step (31)
~(36), iteration terminate afterwards three times.
The localization method of the indoor Internet of Things active label, this method further include the coordinate data abnormal to positioning into
Row KNN correction, specifically includes the following steps:
(41) the signal strength vector Pr formed from the signal strength of the received Internet of Things active label of each reader
(pr1,pr2,…,prn) in, according to descending sequence, the meter of q signal strength composition Internet of Things active label before choosing
Calculate vector Pr (pra,prb,…,prc), wherein the total number of a, b, c ∈ (1, n), n expression reader；
(42) from the signal strength vector VPr (vpr of each virtual label1,vpr2,…,vprn) in choose corresponding calculate
Vector VPr (vpra,vprb,…,vprc)；
(43) following formula is used, the calculating of the calculating vector and each virtual label of Internet of Things active label is calculated
Euclidean distance between vector:
εj=(prj-vprj)
Wherein, δtIndicate the calculating vector and t, t=1,2 of Internet of Things active label ..., the calculating of M virtual label
Euclidean distance between vector, M indicate the total number of virtual label, λjIndicate weighted factor, εjIndicate that individual signals intensity is corresponding
Deviation, d1jIt indicates from Pr (pr1,pr2,…,prn) in choose the corresponding reader of j-th of signal strength have to Internet of Things
The theoretical distance of source label, prjIt indicates from Pr (pr1,pr2,…,prn) in choose j-th of signal strength, d2jIt indicates from VPr
(vpr1,vpr2,…,vprn) in theoretical distance of the corresponding reader of j-th of signal strength to virtual label chosen, vprj
It indicates from VPr (vpr1,vpr2,…,vprn) in choose j-th of signal strength, η indicate signal attenuation coefficient, PLA1 indicate away from
From Internet of Things active label d0The signal strength at place, PLA2 are indicated apart from virtual label d0The signal strength at place, d0Indicate with reference to away from
From；
(44) to δt, t=1,2 ..., M be ranked up according to ascending, and G Euclidean distance is corresponding virtually before choosing
The calibration coordinate of Internet of Things active label is calculated using following formula as reference mode in label:
Wherein, correct_pos indicates the calibration coordinate of Internet of Things active label, posuIndicate u-th of the Euclidean chosen
Coordinate apart from corresponding virtual label, wuIndicate posuWeight, δuIndicate u-th of the Euclidean distance chosen.
The invention has the benefit that
As shown from the above technical solution, the present invention is by having to being mounted on the indoor collected Internet of Things of multiple readers
The signal strength of source label calculate and iteration, realization are not necessarily to people to the three-dimensional localization of Internet of Things active label indoor location
To intervene, positioning accuracy is high, speed is fast.
Detailed description of the invention
Fig. 1 is flow chart of the method for the present invention；
Fig. 2 is to realize structural block diagram of the invention；
Fig. 3 is Internet of Things active label signal propagation path segmentation decay pattern of the invention；
Fig. 4 is Internet of Things active label signal correction angle schematic diagram of the invention；
Fig. 5 is Internet of Things active label amendment positioning figure of the invention；
Fig. 6 is Internet of Things active label signal correction goniometer nomogram of the invention.
Specific embodiment
The present invention is further illustrated in the following with reference to the drawings and specific embodiments.
As shown in Figure 1, a kind of localization method of interior Internet of Things active label, comprising the following steps:
S1, the signal strength for reading Internet of Things active label respectively using multiple readers.
S2, the signal strength data that multiple readers are read is summarized to central processing unit:
As shown in Fig. 2, central processing unit is led to by Transmission Control Protocol Socket socket mode with each reader
News, collect each reader data, and data are packaged by bit, and the ID comprising reader, reader reception Internet of Things are active
The signal strength of label and the timestamp for receiving information.
S3, central processing unit carry out preliminary screening and grouping to signal strength data:
Central processing unit will examine the integrality of received data, abandon deficiency of data, only retains partial data and waits for
With.Next interior (by taking 100ms as an example) at certain time intervals to read a data from each reader, it arranges and is grouped for one
And unified time stabs.
S4, central processing unit calculate the initial coordinate of Internet of Things active label using packet data:
The theoretical distance of S41, each reader of calculating to Internet of Things active label:
Semaphore attenuation model:
Wherein, PL (dj) indicate apart from Internet of Things active label djLocate the attenuation of signal, PL (d0) it is reference distance d0
The signal attenuation at place, unit db calculate for convenience, generally take d0It is 1 meter, lg is denary logarithm, and X is standard
Variance, η are signal attenuation coefficients, and the coefficient is different because of environment.
It can be obtained by above-mentioned semaphore attenuation model:
Wherein, P0For the rated power intensity of Internet of Things active label, prjFor apart from Internet of Things active label djIt reads at place
The signal strength reception value of device, unit dbm enable d0It is 1 meter, X 0, then passing through received prj, each reader can be acquired and arrived
The theoretical distance d of Internet of Things active labelj:
Enable PLA=P0-PL(d0), then:
Prj=PLA-10nlg (dj)
PLA is indicated apart from Internet of Things active label d0The signal strength at place.
S42, due to the coordinate of indoor each reader be all it is known, therefrom choose signal strength reception value maximum three
A reader is based on weighted mass center method, finds out Internet of Things active label in x-axis and y-axis using following formula as reference mode
On initial coordinate x0And y0:
Wherein, xA、xB、xCRespectively coordinate of maximum three readers of signal strength reception value in x-axis, yA、yB、yC
The respectively coordinate of maximum three readers of signal strength reception value on the y axis, dA、dB、dCRespectively signal strength reception value
Theoretical distance of maximum three readers to Internet of Things active label.
S43, initial coordinate z of the Internet of Things active label in z-axis is calculated0:
By step S41 acquire each reader to Internet of Things active label theoretical distance dj,
dj∈(d1,d2,d3,…,dn)
Each reader and projector distance vd of the Internet of Things active label on x/y plane are acquired by step S42j:
vdj∈(vd1,vd2,vd3,…,vdn)
Height zd of each reader relative to Internet of Things active label can be acquired according to Pythagorean theoremj, zdj∈(zd1,
zd2,zd3,…,zdn), due to reader height H on cabinetjIt is all 2.18 meters, then can acquire:
The signal strength or weakness read again using each reader is weight, the more strong then d of signaljIt is smaller, zdjWeight is bigger, acquires object
Network initial coordinate z of the active label in z-axis0Are as follows:
To sum up, the initial coordinate (x of Internet of Things active label is obtained0,y0,z0)。
S5, pass through iterated revision positioning result, further increase the coordinate accuracy of Internet of Things active label:
S51, the initial coordinate for assuming Internet of Things active label are (x0,y0,z0), then reader RjTo the active mark of Internet of Things
The direction vector V of labelj=(x0-xj,y0-yj,z0-zj).If using air as special obstacle object, Internet of Things active label is arrived
Reader RjPhysical pathway can carry out segment processing, the segmentation of signal decay path is as shown in Figure 3.
Wherein, Pi-1For the signal strength (unit dbm) before barrier, diThe biography for being signal inside barrier
Broadcast path, PiThen have for the signal strength for being pierced by barrier interface since signal strength is logarithmic decrement:
Wherein, ηiThe attenuation coefficient for being signal in barrier, l are the rated power of Internet of Things active label in barrier
Middle propagation attenuation is to PiWhen corresponding theoretical distance, l-diIt propagates and declines in barrier for the rated power of Internet of Things active label
Reduce to Pi-1When corresponding theoretical distance.
Above-mentioned formula is the relationship of anti-recursion, because signal also has decaying in air, also regards air as barrier
If, it comes then can be regarded as different barrier partitions between Internet of Things active label and reader.Since signal is at this
Attenuation coefficient in a little barriers can be calculated to obtain in advance, if the path that signal is propagated is divided into N sections by barrier, often
The length d in section pathi, i ∈ (1, N) can be calculated, then signal can be regarded as managing when passing through each section of path
By decaying, only attenuation coefficient is different.Using above-mentioned formula the last period can be extrapolated by the signal strength in latter section of path
The signal strength in path.And reader received signal intensity prjIt is signal strength when signal passes through final stage barrier.
The P extrapolated every timei-1All it is greater than Pi, such iteration calculates the signal strength in the preceding paragraph path, if P after m timesm≥P0When
Terminate.
How P is judgedm≥P0, it is to be judged by l, for example, final stage path reader received signal intensity is
prj, the attenuation coefficient of final stage path signal is ηi, it is substituted into theoretical distance computation model if by the two parameters,
A distance value can be obtained, this value is exactly l, it shows that Internet of Things active label will decay the distance of l under the attenuation coefficient,
Signal strength can just decay to prj.But during actual propagation, corresponding this section of path length of the attenuation coefficient only has di, that
:
Work as l > diWhen, illustrate Internet of Things active label not on this section of path, with decay distance diSubject to, using above-mentioned anti-
Recurrence formula acquires signal strength when signal penetrates the preceding paragraph path, and so on the basis of required result, using same
Kind method, until acquiring l≤di；
As l≤diWhen, illustrate Internet of Things active label just on this section of path, corresponding decay distance should be l, will be anti-
The length in each section of path of recursive process experience adds up, just obtain each reader to Internet of Things active label correction distance
Dj:
S52, as shown in figure 4, P1 point is the point that intersects with blocking surfaces when signal passes through barrier, it is known that barrier
The length, width and height of (cabinet) and corresponding starting point coordinate can find out P1 point coordinate by simple geometric operation.
Collection point is some coordinate points of blocking surfaces, coordinates of these points be it is fixed, reader be also it is fixed,
Point-to-point transmission determines straight line, then attenuation coefficient of the signal on this straight line can be obtained through actual measurement.
P2 point is unknown position, when acquiring P1 point, to obtain Internet of Things active label by P1 point to reader Rj
More accurate attenuation coefficient on coordinate straight line just can be carried out distance correction.And signal is in P1 point to reader RjOn coordinate straight line
Attenuation coefficient can be acquired by the collection point (empirical data) near P1 point, these collection points to RjThe rectilinear direction of coordinate
Almost with P1 point to RjThe rectilinear direction of coordinate is the same.
Assuming that having k collection point, TK in P1 point rangei, i ∈ (1, k), each TKiIn containing Internet of Things active label pass through
The point is to reader RjAttenuation coefficient, here withIndicate that signal passes through TKiTo reader RjDecaying system on coordinate straight line
Number.
If in TKiPoint uses attenuation coefficientIt is asked using path segments attenuation model mentioned in the present invention away from being calculated
Distance is greater than TKiTo reader RjWhen coordinate distance, it is believed that pickup electrode may be by the direction and travel to reader Rj's.
If there is a such collection points meet this condition, then P2 point just indicates the central point of a collection point coordinate:
Internet of Things active label is in P2 and reader RjOn the straight line of coordinate, and corresponding attenuation coefficient η at P2
It can be according to the attenuation coefficient of a collection pointIt acquires:
When a is 0, P2 point will not be generated, then the calculation formula of corresponding attenuation coefficient η is as follows at P1 point；
Wherein, wiIndicate the weight of the attenuation coefficient of i-th of collection point, TdiIndicate i-th of collection point to P1 point distance.
When a is 0, since P2 point will not be generated, then do not need to reader R in step S51jTo Internet of Things active label
Direction vector VjIt is modified.
When a is not 0, reader RjDirection vector to P2 point is just revised direction vector Vj.Using following formula
Reader R is calculatedjIn revised VjOn direction, distance DjThe coordinate at place, i.e. Internet of Things active label are based on each reading
The new coordinate VR of devicej, as shown in Figure 5:
As shown in fig. 6, P1, P2, RjCoordinate both know about, by geometry calculate acquire point-to-point transmission linear distance (d1,
D2, d3), θjIt just is P1, Rj, P2 angle, can be in the hope of according to the cosine law:
New positioning correcting result is to VRjThe solution of (j=1,2 ..., n) mass center.
Introduce reader RjReceived signal intensity, which is used as, refers to weight, i.e. reader RjReceived signal intensity is bigger,
VRjCoordinate reference weight is bigger.θjAs reference weight, θjVariation it is bigger, illustrate that its influence to positioning correcting result is got over
Greatly.In view of θjIt is converted by the case where being possible for 0 in the form of linear equationWherein β is constant term, according to experiment
It obtains, θjIt is calculated with Circular measure, and β is set as 1.
Assuming that the signal strength vector that each reader receives Internet of Things active label is Pr (pr1,pr2,…,prn), choosing
Take VRjAny four point forms several tetrahedrons, (pr in (j=1,2 ..., n)1,pr2,pr3,pr4) it is selected four
The mapping of point signal strength, is all positive number, is weighted center coordination to each tetrahedron using following formula, generate new
Point:
Several new tetrahedrons are formed with newly-generated point again, repeat above-mentioned operation, until last only remaining less than four
Remaining point is weighted and averaged evaluation, as the amendment coordinate of Internet of Things active label by a point.
S53, using the calculated amendment coordinate of step S52 as initial coordinate, repeat substitute into step S51 and S52 be iterated
Calculate, empirically iteration three times after calculated result just level off to very much desired quantity.
S6, central processing unit carry out KNN correction to coordinate data:
Since its calculated result is likely to spread across the shadow region of barrier, required coordinate result needs further correction.
When there is abnormal positioning result, according to the information of the virtual label on positioning result periphery and the practical received letter of reader at this time
Number vector calculates the similitude between them, and the lesser virtual label of Euclidean distance is selected to make reference.
Virtual label is empirical data information in fact, for example Internet of Things active label is placed on to the table of wall or cabinet in advance
Some position of face records each reader received signal intensity at this time, forms signal strength vector VPr (vpr1,vpr2,…,
vprn).So position property for just imparting its label, the information that only it is mapped be it is static, contain Internet of Things
Active label is in this, the characteristic information of each reader received signal strength.
When virtual label information contains Internet of Things active label in the position, each reader received signal intensity arrow
VPr is measured, and each reader has its corresponding signal strength vector Pr (pr in actual location1,pr2,…,prn), compare
It is Pr (pr1,pr2,…,prn) and VPr (vpr1,vpr2,…,vprn) Euclidean distance.
Assuming that some time carves existing abnormal positioning result, each reader receives the signal strength vector of Internet of Things active label
For Pr (pr1,pr2,…,prn), a maximum signal strength indications of wherein q, which are chosen, as the higher target of confidence level calculates vector,
Pr(pra,prb,…,prc), wherein a, b, c ∈ (1, n).N indicates the number of reader, how many reader is corresponding
Signal strength reception value just should how many.In order to accurately calculate, the present invention chooses larger from n signal strength reception value
Q composition it is new for calculating the vector of Euclidean distance.Subscript a, b, c therein correspond to selected larger signal strength and receive
The subscript of value, therefore range is (1, n).
From the VPr (vpr of each virtual label1,vpr2,…,vprn) in choose corresponding vector VPr (vpra,vprb,…,
vprc)。
It is so to seek Pr (pr for the Euclidean distance of each virtual labela,prb,…,prc) and VPr (vpra,
vprb,…,vprc) Euclidean distance.
The corresponding deviation of individual signals intensity is εj=(prj-vprj)。
Because signal strength is in logarithmic decrement, then signal strength variance is smaller to influence just whole Euclidean distance
It is bigger, so introducing weighted factor λjEuclidean distance is modified:
Euclidean distance δtCalculation formula:
By to δt(t=1,2 ..., M) is compared (M be virtual label number), and wherein G Euclidean distance be most for selection
For small virtual label as reference mode, these reference mode Euclidean distances are smaller, bigger with reference to weight, finally obtain correction
Coordinate correct_pos:
Wherein, posuIndicate the selected corresponding coordinate of virtual label, wuFor corresponding weight.
S7, the final coordinate for obtaining Internet of Things active label.
Embodiment described above is only that preferred embodiments of the present invention will be described, not to model of the invention
It encloses and is defined, without departing from the spirit of the design of the present invention, those of ordinary skill in the art are to technical side of the invention
The various changes and improvements that case is made, should fall within the scope of protection determined by the claims of the present invention.
Claims (3)
1. a kind of localization method of interior Internet of Things active label, which is characterized in that method includes the following steps:
(1) preliminary screening and grouping are carried out to the signal strength data of the received Internet of Things active label of each reader；
(2) initial coordinate of Internet of Things active label is calculated using packet data；
(3) amendment is iterated to the initial coordinate of Internet of Things active label, obtains the final coordinate of Internet of Things active label；
The step (2), specifically includes the following steps:
(21) use following formula, be calculated each reader to Internet of Things active label theoretical distance:
PLA=P0-PL(d0)
Wherein, djIndicate theoretical distance of j-th of reader to Internet of Things active label, prjIndicate that j-th of reader is received
The signal strength of Internet of Things active label, η indicate that signal attenuation coefficient, PLA are indicated apart from Internet of Things active label d0The letter at place
Number intensity, P0Indicate the rated power intensity of Internet of Things active label, PL (d0) indicate apart from Internet of Things active label d0The letter at place
Number attenuation, d0Indicate reference distance；
(22) signal strength data of the received Internet of Things active label of each reader is compared, it is strong therefrom chooses signal
Maximum three readers of reception value are spent as reference mode, and the x of Internet of Things active label is calculated using following formula
Axis, y-axis initial coordinate:
Wherein, x0、y0Respectively indicate x-axis, the y-axis initial coordinate of Internet of Things active label, xA、xB、xCRespectively indicate three references
The x-axis coordinate of node, yA、yB、yCRespectively indicate the y-axis coordinate of three reference modes, dA、dB、dCRespectively indicate three reference nodes
Point arrives the theoretical distance of Internet of Things active label；
(23) following formula is used, each reader and projector distance of the Internet of Things active label on x/y plane is calculated:
Wherein, vdjIndicate j-th of reader and projector distance of the Internet of Things active label on x/y plane, xj、yjIt respectively indicates
X-axis, the y-axis coordinate of j-th of reader；
(24) following formula is used, height of each reader relative to Internet of Things active label is calculated:
Wherein, zdjIndicate height of j-th of reader relative to Internet of Things active label, HjIndicate the height of j-th of reader；
(25) following formula is used, the z-axis initial coordinate of Internet of Things active label is calculated:
Wherein, z0Indicate the z-axis initial coordinate of Internet of Things active label, n indicates the total number of reader.
2. the localization method of interior Internet of Things active label according to claim 1, which is characterized in that the step (3)
In, amendment is iterated to the initial coordinate of Internet of Things active label, specifically includes the following steps:
(31) initial coordinate for assuming Internet of Things active label is (x0,y0,z0), each reader to Internet of Things active label
Inceptive direction vector are as follows:
Vj=(x0-xj,y0-yj,z0-zj)
Wherein, VjIndicate inceptive direction vector of j-th of reader to Internet of Things active label, (xj,yj,zj) indicate to read for j-th
Read the coordinate of device；
(32) using air as special obstacle object, it is assumed that the signal propagation path between Internet of Things active label and reader is hindered
Object is hindered to be divided into N sections, when passing through final stage path based on the signal that reader received signal intensity is Internet of Things active label
Signal strength, using following anti-recurrence formula, the signal that iteration extrapolates Internet of Things active label passes through the preceding paragraph path
Signal strength, until Pm≥P0When terminate:
Wherein, PmIndicate the signal strength obtained at anti-recursion m times, P0Indicate the rated power intensity of Internet of Things active label, Pi
Indicate that the signal of Internet of Things active label passes through i-th, i=N, the signal strength in section path N-1 ..., N-m+1, Pi-1Indicate Internet of Things
The signal of net active label passes through the signal strength in (i-1)-th section of path, ηiIndicate the signal attenuation coefficient in i-th section of path, diIt indicates
The length in i-th section of path, l indicate the rated power strength retrogression of Internet of Things active label to PiWhen signal propagate it is theoretical away from
From l-diIndicate the rated power strength retrogression of Internet of Things active label to Pi-1When signal propagate theoretical distance, X indicate mark
Quasi- variance；
As i=N, PN=prj, PNIndicate the signal when signal of Internet of Things active label passes through final stage i.e. N sections of paths
Intensity, prjIndicate j-th of reader received signal intensity；
(33) use following formula, be calculated each reader to Internet of Things active label correction distance:
Wherein, DjIndicate correction distance of j-th of reader to Internet of Things active label, diIndicate i-th, i=N, N-1 ..., N-m
The length in+1 section of path；
(34) the inceptive direction vector of each reader to Internet of Things active label is modified, obtains amendment direction vector,
And following formula is used, each reader is calculated along the direction of its corresponding amendment direction vector and is located at correction distance
Coordinate:
Wherein, VRjJ-th of reader is indicated along the direction of its corresponding amendment direction vector and is located at correction distance DjThe seat at place
Mark, i.e. new coordinate of the Internet of Things active label based on j-th of reader, RjIndicate the phasor coordinate of j-th of reader, Vj' indicate
Amendment direction vector of j-th of reader to Internet of Things active label；
(35) following formula is used, inceptive direction vector and amendment direction vector to each reader to Internet of Things active label
Between angle carry out linear transformation:
Wherein, θjIndicate j-th of reader to the folder between the inceptive direction vector of Internet of Things active label and amendment direction vector
Angle, β are constant,Angle after indicating conversion；
(36) VR is chosenj, any four point forms several tetrahedrons in j=1,2 ..., n, wherein n indicates total of reader
Number, using following formula, is weighted center coordination to each tetrahedron, obtains newly-generated point:
Wherein, (x, y, z) indicates the coordinate of newly-generated point, (x1,y1,z1)、(x2,y2,z2)、(x3,y3,z3)、(x4,y4,z4)
The coordinate for forming some tetrahedral four point is respectively indicated, Respectively indicating composition, this is tetrahedral
The corresponding reader of four points is linear to the angle between the inceptive direction vector and amendment direction vector of Internet of Things active label
Value after conversion, pr1、pr2、pr3、pr4Respectively indicating the corresponding reader of composition tetrahedral four points and receiving Internet of Things has
The signal strength of source label；
Several new tetrahedrons are formed with newly-generated point again, repeat above-mentioned operation, until the number of last remaining point is small
In 4, the average value of the coordinate of remaining point is calculated, the amendment coordinate as Internet of Things active label；
(37) using the amendment coordinate of the calculated Internet of Things active label of step (36) as initial coordinate, repetition step (31)~
(36), iteration terminates afterwards three times.
3. the localization method of interior Internet of Things active label according to claim 1, which is characterized in that this method further includes
KNN correction is carried out to the abnormal coordinate data of positioning, specifically includes the following steps:
(41) the signal strength vector Pr (pr formed from the signal strength of the received Internet of Things active label of each reader1,
pr2,…,prn) in, according to descending sequence, the calculating vector of q signal strength composition Internet of Things active label before choosing
Pr(pra,prb,…,prc), wherein the total number of a, b, c ∈ (1, n), n expression reader；
(42) from the signal strength vector VPr (vpr of each virtual label1,vpr2,…,vprn) in choose and corresponding calculate vector
VPr(vpra,vprb,…,vprc)；
(43) following formula is used, the calculating vector of the calculating vector and each virtual label of Internet of Things active label is calculated
Between Euclidean distance:
εj=(prj-vprj)
Wherein, δtIndicate the calculating vector and t, t=1,2 of Internet of Things active label ..., the calculating vector of M virtual label it
Between Euclidean distance, M indicate virtual label total number, λjIndicate weighted factor, εjIndicate that individual signals intensity is corresponding partially
Difference, d1jIt indicates from Pr (pr1,pr2,…,prn) in the corresponding reader of j-th of signal strength chosen to the active mark of Internet of Things
The theoretical distance of label, prjIt indicates from Pr (pr1,pr2,…,prn) in choose j-th of signal strength, d2jIt indicates from VPr
(vpr1,vpr2,…,vprn) in theoretical distance of the corresponding reader of j-th of signal strength to virtual label chosen, vprj
It indicates from VPr (vpr1,vpr2,…,vprn) in choose j-th of signal strength, η indicate signal attenuation coefficient, PLA1 indicate away from
From Internet of Things active label d0The signal strength at place, PLA2 are indicated apart from virtual label d0The signal strength at place, d0Indicate with reference to away from
From；
(44) to δt, t=1,2 ..., M are ranked up according to ascending, choose the corresponding virtual label of preceding G Euclidean distance and make
The calibration coordinate of Internet of Things active label is calculated using following formula for reference mode:
Wherein, correct_pos indicates the calibration coordinate of Internet of Things active label, posuIndicate u-th of the Euclidean distance pair chosen
The coordinate for the virtual label answered, wuIndicate posuWeight, δuIndicate u-th of the Euclidean distance chosen.
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