CN104968046A - Skip distance correction WSN three-dimensional space target positioning method based on coplanarity - Google Patents

Abstract

The invention discloses a skip distance correction WSN three-dimensional space target positioning method based on coplanarity. The method comprises the following steps: first, the RSSI distance measurement technology is employed to measure a distance between adjacent nodes; second, beacon node information is received and transmitted through a distance vector exchange protocol, and minimum skip values and cumulative distance of all the nodes and a beacon node are obtained; third, a correction parameter is calculated, and the cumulative distance is corrected according the correction parameter; fourth, the coplanarity value of each positioning unit is calculated, and the best positioning unit is selected based on the coplanarity values; fifth, a four-face measuring method is employed to calculate a coordinate of an unknown node according to the selected best positioning unit; sixth, a quasi-Newton method is employed to optimize the coordinate of the unknown node; seven, the node positioned successfully is raised to a beacon node to participate in secondary positioning. The best positioning unit suitable for positioning is selected based on coplanarity values, the quasi-Newton method is employed to raise the positioning result precision, and positioning precision and the positioning coverage rate of three-dimensional space positioning can be raised.

Description

A kind of jumping based on coplane degree is apart from the WSN Three dimensional Targets localization method revised

Technical field

The invention belongs to computer radio sensor network field, particularly a kind of jumping based on coplane degree is apart from the WSN Three dimensional Targets localization method revised.

Background technology

Wireless sensor network (Wireless Sensor Network, WSN) be by having collection in a large number, calculate and network that the sensor node of wireless communication ability is consisted of multi-hop, Ad hoc mode, be arranged in monitored area, can information independently in acquisition and processing monitored area, and send to observer.Positional information all has important effect at the application such as monitoring of wireless sensor network and Route Selection, reliability and security in ensureing, does not have the supervisory messages of positional information often meaningless.Therefore location technology has become wireless sensor network and has applied one of requisite support technology.At present, in the world mainly two dimensional surface is concentrated on to the research of WSN node locating, also fewer to the achievement in research of the three-dimensional fix problem based on WSN.And the deployment of transducer often may in the 3D region such as underground, high-wall be even aerial in practical application.Because three-dimensional environment is more complicated, the computation complexity of refinement problem increases considerably, be difficult to directly by two-dimensional localization algorithm application in three dimensions.

What the orientation problem in three dimensions compared two-dimensional space is positioned with following difficult point: the reference point required for (1) location will increase to some extent.In two-dimensional space, locating a unknown node at least needs three reference nodes.And in three dimensions, at least needing four reference nodes could determine the position of unknown node, this not only requires the density increasing reference node, and adds algorithm complex.(2) if there is terrain obstruction, impact is existed on the signal transmission between node.The non line of sight transmission that three dimensions mesorelief brings is very important on the impact of signal, therefore uses the distance between RSSI computing node can there is certain error, thus has an impact to positioning precision.

Along with the development of WSN technology, the application of wireless sensor network is more and more extensive, and also more and more higher to the required precision of location.At present, the research of the two-dimensional localization technology of wireless sensor network is tending towards ripe, but also rare for the research work of three-dimensional localization techniques, also there is no ripe standard.Current existing three-dimensional localization techniques, still adopt on the whole and two dimensional surface location algorithm is generalized to three-dimensional method, it is do not consider three-dimensional complex situations that the WSN location algorithm of two dimensional surface is directly generalized to three dimensions Problems existing, amount of calculation can be caused to increase considerably, cause the problems such as cumulative errors.

Summary of the invention

Technical problem solved by the invention is to provide the WSN Three dimensional Targets localization method of a kind of jumping based on coplane degree apart from revising.

Realizing technical solution of the present invention is: a kind of jumping based on coplane degree, apart from the WSN Three dimensional Targets localization method revised, specifically comprises the following steps:

Step 1, adopts the distance between RSSI ranging technology measurement adjacent node;

Step 2, according to minimum hop count value in step 2 and accumulative jumping distance, receives and forwards beaconing nodes information by distance vector exchange agreement, obtain minimum hop count value and the cumulative distance of all nodes and beaconing nodes;

Step 3, calculates corrected parameter, according to corrected parameter correction cumulative distance;

Step 4, calculates the coplanar angle value of each positioning unit, selects best located unit based on coplanar angle value;

Step 5, adopts four sides mensuration to calculate unknown node coordinate according to the best located unit selected;

Step 6, adopts quasi-Newton method to be optimized unknown node coordinate;

Step 7, is promoted to beaconing nodes participation second and takes turns location by the node that success is located.

The present invention compared with prior art, its remarkable advantage is: 1) the present invention introduces the thought of coplane degree, eliminate positioning unit in three-dimensional localization and be similar to the coplanar position error caused, according to the positioning unit that coplane degree Threshold selection positions, improve location algorithm precision; 2) cumulative distance is revised, reduce the error replacing actual range to cause with jumping segment distance, thus improve the positioning precision of algorithm; 3) by the unknown node that success is located is promoted to the location that beaconing nodes participates in unknown node, improve the ratio of beaconing nodes, thus improve the Signal Coverage Percentage of location algorithm; 4) adopt quasi-Newton method to be optimized positioning result, further increase positioning precision.

Below in conjunction with accompanying drawing, the present invention is described in further detail.

Accompanying drawing explanation

Fig. 1 is three-dimensional fix illustraton of model.

Fig. 2 is the flow chart of a kind of jumping based on coplane degree apart from the WSN Three dimensional Targets localization method revised.

Fig. 3 is simulated effect figure of the present invention.

Fig. 4 is the positioning precision comparison diagram of algorithm of the present invention and other algorithms.

Fig. 5 is the Signal Coverage Percentage comparison diagram of algorithm of the present invention and other algorithms.

Embodiment

A kind of jumping based on coplane degree of the present invention, apart from the WSN Three dimensional Targets localization method revised, comprises the following steps:

Step 1, adopt the distance between RSSI ranging technology measurement adjacent node, RSSI technology (Received SignalStrength Indicator, RSSI), according to the signal strength signal intensity that receiving node receives, the distance between transmitting node to receiving node can be estimated.Signal strength signal intensity is converted to and apart from formula used is:

$d=10\frac{10\mathrm{nlg}{d}_0+\mathrm{PL}\left(d_0\right)-X_{\mathrm{\σ}}-P_{\mathrm{RSSI}}}{10n}$

In formula, d is the distance between transmitting node to receiving node, and n is wireless channel attenuation coefficient, and general value is 2 ~ 4, d ₀be be known distance, generally obtain by experiment, PL (d ₀) be receiving node be known distance d from transmitting node distance ₀time received signal strength, X _σbe average be 0, variance is σ ²gaussian random noise variable, P _rSSIfor the RSSI value that receiving node receives.

Step 2, receive and forward beaconing nodes information by distance vector exchange agreement, obtain minimum hop count value and the cumulative distance of all nodes and beaconing nodes, by distance vector exchange agreement, jumping figure and cumulative distance are initialized as 0, and each node compares the jumping figure value of the same beaconing nodes received, and retains the information that wherein jumping figure is minimum, then the cumulative jumping segment distance from each beaconing nodes jumping figure is added 1, is finally transmitted to other neighbor nodes.

Step 3, according to minimum hop count value in step 2 and accumulative jumping distance, calculates corrected parameter, according to corrected parameter correction cumulative distance, calculates corrected parameter and adopt following formula:

${\mathrm{\λ}}_K=\frac{{\mathrm{\ΣL}}_{\mathrm{ij}}}{{\mathrm{\ΣD}}_{\mathrm{ij}}}$

In formula, K is unknown node, i and j is beaconing nodes i=1 ... n, j=1 ..., n and i ≠ j, i and j are positive integer, L _ijfor the actual distance between beaconing nodes i to beaconing nodes j, D _ijcumulative distance between beaconing nodes i to beaconing nodes j.

Revise cumulative distance and adopt following formula:

L _Ki＝λ _K*D _Ki

In formula, λ _kfor the corrected parameter of unknown node K, D _kifor unknown node K is to the cumulative distance of beaconing nodes i, L _kifor the revised cumulative distance of unknown node K to beaconing nodes i.

Step 4, calculates the coplanar angle value of each positioning unit, and select best located unit based on coplanar angle value, a positioning unit comprises 4 beaconing nodes, and the computational methods of its coplanar angle value adopt following computing formula:

$\mathrm{\ρ}=\frac{{216v}^2}{\underset{i=0}{\overset{3}{\mathrm{\Σ}}}{s}_i\sqrt{(a+b+c)(a+b-c)(a+c-b)(b+c-a)}}$

In formula, v is the tetrahedral volume of four node compositions, and a, b, c are respectively tetrahedron three groups of products to rib length, S _ibeing respectively is the area in tetrahedron four faces.

Step 5, adopts four sides mensuration to calculate unknown node coordinate according to the best located unit selected, calculates unknown node coordinate and adopt following formula:

$\left[\begin{array}{c}x\\ y\\ z\end{array}\right]=\frac{1}{2}{\left[\begin{array}{ccc}{x}_2-x_1& y_2-y_1& z_2-z_1\\ x_3-x_1& y_3-y_1& z_3-z_1\\ x_4-x_1& y_4-y_1& z_4-z_1\end{array}\right]}^{-1}\left[\begin{array}{c}{x}_2^2-x_1^2+y_2^2-y_1^2+z_2^2-z_1^2+d_{\mathrm{KA}}^2-d_{\mathrm{KB}}^2\\ x_3^2-x_1^2+y_3^2-y_1^2+z_3^2-z_1^2+d_{\mathrm{KA}}^2-d_{\mathrm{KC}}^2\\ x_4^2-x_1^2+y_4^2-y_1^2+z_4^2-z_1^2+d_{\mathrm{KA}}^2-d_{\mathrm{KD}}^2\end{array}\right]$

In formula, the coordinate that (x, y, z) is unknown node K, (x ₁, y ₁, z ₁) (x ₂, y ₂, z ₂) (x ₃, y ₃, z ₃) (x ₄, y ₄, z ₄) be the coordinate of four beaconing nodes in positioning unit, d _kA, d _kB, d _kC, d _kDbe respectively the correction cumulative distance between unknown node K and beaconing nodes.

Step 6, adopts quasi-Newton method to be optimized unknown node coordinate, adopts quasi-Newton method to be optimized positioning result, positioning and optimizing problem is converted into Unconstrained Optimization Problem, determines that target function is:

$\min F(x,y,z)=\underset{i=1}{\overset{n}{\mathrm{\Σ}}}[{(x_i-x)}^2+{(y_i-y)}^2+{(z_i-z)}^2-d_i^2]$

In formula, the coordinate that (x, y, z) is unknown node K, (x _i, y _i, z _i) be the coordinate of beaconing nodes i, i=1,2 ..., n, i are positive integer, d _ifor the cumulative distance of beaconing nodes i to unknown node K.

Step 7, is promoted to beaconing nodes participation second and takes turns location by the node that success is located.

Below in conjunction with accompanying drawing, the present invention is described in more detail:

By reference to the accompanying drawings 2, a kind of jumping based on coplane degree of the present invention is divided into four-stage apart from the WSN Three dimensional Targets localization method revised: the first stage, adopt the distance between rssi measurement adjacent node, employing DV-Distance algorithm obtains the distance between unknown node and each beaconing nodes; Second stage, the principle based on coplane degree selects best located unit, adopts four limit mensurations to estimate the rough location of node; Phase III, quasi-Newton method is adopted to be optimized positioning result; Fourth stage, is promoted to beaconing nodes by the unknown node that success is located, then carries out second to the unknown node of unsuccessful location and take turns location, to improve the coverage rate of location.

(1) first stage

In wireless sensor network, radio transmission signal behavior normality logarithmic model, shown in (1):

$\mathrm{PL}\left(d\right)=\mathrm{PL}\left(d_0\right)-10\mathrm{nlg}\left(\frac{d}{d_0}\right)-x_{\mathrm{\σ}}---\left(1\right)$

In formula, if PL (d) represents the signal strength signal intensity of two wireless sensor nodes in time being d, PL (d ₀) be receiving node be known distance d from transmitting node distance ₀time received signal strength, PL (d ₀) generally experience or hardware specification definition obtain by experiment; N is wireless channel attenuation coefficient, and general value is 2 ~ 4; X _σbe average be 0, variance is σ ²gaussian random noise variable.

Due to formula (1) d ₀in be known quantity, therefore PL (d ₀) be known; Further, 10nlg d ₀also be known.Can think X _σbe definite value, therefore can obtain the RSSI value P of receiving node by through type (2) _rSSI.

P _RSSI＝PL(d)＝-10nlg d+[10nlgd ₀+PL(d ₀)-X _σ] (2)

Because the item in bracket is below definite value, therefore can be write as the form of formula (3) as follows for formula (2).

RSSI＝PL(d)＝-10nlgd+a (3)

In formula (3), a=10nlg d ₀+ PL (d ₀)-X _σ, a is constant.Therefore the computational methods of the spacing of transmitting node and receiving node can be obtained according to formula (3) such as formula shown in (4).

$d={10}^{\frac{a-P_{\mathrm{RSSI}}}{10n}}---\left(4\right)$

In traditional DV-Distance algorithm, because the cumulative distance between unknown node to any beaconing nodes is all greater than the actual range between them, therefore when jumping figure is more, may be larger by the error of this jumping segment distance replacement actual range, therefore need to revise this error.

Corrected parameter λ _kcomputing formula such as formula (5):

${\mathrm{\λ}}_K=\frac{{\mathrm{\ΣL}}_{\mathrm{ij}}}{{\mathrm{\ΣD}}_{\mathrm{ij}}}---\left(5\right)$

In formula, K is unknown node, i and j is beaconing nodes i=1 ... n, j=1 ..., n and i ≠ j, i and j are positive integer, L _ijfor the actual distance between beaconing nodes i to beaconing nodes j, D _ijcumulative distance between beaconing nodes i to beaconing nodes j.

When the accumulative jumping distance of beaconing nodes i to unknown node k is D _kitime, the correction Cumulative Distance of beaconing nodes i to unknown node k can represent with formula (6).

L _Ki＝λ _K*D _Ki(6)

In formula, λ _kfor the corrected parameter of unknown node K, D _kifor unknown node K is to the cumulative distance of beaconing nodes i, L _kifor the revised cumulative distance of unknown node K to beaconing nodes i.

This is revised accumulative segment distance of jumping as the coverage calculated, then carry out unknown node location, to reduce error.

(2) second stage

When adopting the reference point combination at least determining a unknown node position during polygon positioning mode to be called that a positioning unit carries out target localization in two dimensional surface, a positioning unit at least needs three beaconing nodes, and the general position adopting trilateration to calculate node to be positioned.But when three beaconing nodes are positioned at straight line, the focus of three circles has two, can not determine the position of node to be positioned in this case.In like manner, when location expands to three dimensions, also there is same problem.During location, a positioning unit at least needs four beaconing nodes in three dimensions.Because RSSI exists range error, four spheres may not have intersection point; On the other hand, when four points are similar to coplanar, more than one of the intersection point of four spheres, is thus difficult to the position determining node to be positioned.In order to solve the position error problem in three dimensions, introduce the concept of coplane degree herein, that can get rid of that coplanar positioning unit brings can not orientation problem.

Coplane degree DCP represents the coplanar degree of four points in three dimensions, adopts tetrahedral radius ratio to react coplane degree.

The radius calculation formula of tetrahedron inscribed sphere and circumsphere is shown in formula (7) and formula (8):

$r_{\mathrm{in}}=3v/\underset{i=0}{\overset{3}{\mathrm{\Σ}}}{s}_i---\left(7\right)$

$r_{\mathrm{out}}=\frac{\sqrt{(a+b+c)(a+b-c)(a+c-b)(b+c-a)}}{24v}---\left(8\right)$

In formula, v is tetrahedral volume, S _ibe respectively the area in tetrahedron four faces, a, b, c are tetrahedron three groups of products to rib length respectively.Therefore the computing formula of tetrahedron radius ratio ρ can be obtained.

$\mathrm{\ρ}=\frac{{3r}_{\mathrm{in}}}{r_{\mathrm{out}}}=\frac{{216v}^2}{\underset{i=0}{\overset{3}{\mathrm{\Σ}}}{s}_i\sqrt{(a+b+c)(a+b-c)(a+c-b)(b+c-a)}}---\left(9\right)$

Wherein, ρ ∈ (0,1].When ρ close to 0 time tetrahedron four summits be similar to coplanar, ρ close to 1 time be positive tetrahedron.

Coplane degree DCP can be expressed as formula (10):

$\mathrm{DCP}=\left\{\begin{array}{cc}0& \mathrm{coplanar}\\ \mathrm{\ρ}& \mathrm{else}\end{array}\right.---\left(10\right)$

Location model in three dimensions as shown in Figure 1.

Suppose A, B, C, D are four beaconing nodes in three dimensions, and their coordinate in three-dimension monitor region is known, and its coordinate is respectively (x ₁, y ₁, z ₁) (x ₂, y ₂, z ₂) (x ₃, y ₃, z ₃) (x ₄, y ₄, z ₄).Make K be node to be positioned, its coordinate is (x, y, z).Be d by the DV-Distance algorithm distance that can obtain between beaconing nodes and node K to be positioned _kA, d _kB, d _kC, d _kD.Then can list such as formula the equation group shown in (11) according to the computational methods of 2 distances in three dimensions:

$\left\{\begin{array}{c}\sqrt{{(x_1-x)}^2+{(y_1-y)}^2+{(z_1-z)}^2}-d_{\mathrm{KA}}=0\\ \sqrt{{(x_2-x)}^2+{(y_2-y)}^2+{(z_2-z)}^2}-d_{\mathrm{KB}}=0\\ \sqrt{{(x_3-x)}^2+{(y_3-y)}^2+{(z_3-z)}^2}-d_{\mathrm{KC}}=0\\ \sqrt{{(x_4-x)}^2+{(y_4-y)}^2+{(z_4-z)}^2}-d_{\mathrm{KD}}=0\end{array}\right.---\left(11\right)$

Formula (11) is solved, obtains the position coordinates of unknown node K such as formula (12):

$\left[\begin{array}{c}x\\ y\\ z\end{array}\right]=\frac{1}{2}{\left[\begin{array}{ccc}{x}_2-x_1& y_2-y_1& z_2-z_1\\ x_3-x_1& y_3-y_1& z_3-z_1\\ x_4-x_1& y_4-y_1& z_4-z_1\end{array}\right]}^{-1}\left[\begin{array}{c}{x}_2^2-x_1^2+y_2^2-y_1^2+z_2^2-z_1^2+d_{\mathrm{KA}}^2-d_{\mathrm{KB}}^2\\ x_3^2-x_1^2+y_3^2-y_1^2+z_3^2-z_1^2+d_{\mathrm{KA}}^2-d_{\mathrm{KC}}^2\\ x_4^2-x_1^2+y_4^2-y_1^2+z_4^2-z_1^2+d_{\mathrm{KA}}^2-d_{\mathrm{KD}}^2\end{array}\right]---\left(12\right)$

(3) phase III

In order to improve the precision of location algorithm, usually orientation problem can be converted into optimization problem.If i=1,2 ..., n is beaconing nodes ID, and their coordinate in three-dimension monitor region is known, and coordinate is (x respectively ₁, y ₁, z ₁) (x ₂, y ₂, z ₂) ... (x _n, y _n, z _n).K is node to be positioned, and its coordinate is (x, y, z).Be d by the RSSI mode measurement distance obtained between beaconing nodes i and node K to be positioned _i, can positioning and optimizing problem be herein converted into such as formula the Unconstrained Optimization Problem shown in (13):

$\min F(x,y,z)=\underset{i=1}{\overset{n}{\mathrm{\Σ}}}[{(x_i-x)}^2+{(y_i-y)}^2+{(z_i-z)}^2-{d_i}^2]---\left(13\right)$

STEP 1: the estimated value that formula (12) is obtained as initial value, given initial matrix H ₀, departure ε, calculates g ₀, make k=0;

STEP 2: make p _k=-H _kg _k;

STEP 3: can step-length α be determined by accurate linear search method _k, shown in (14):

f(x _k+α _kp _k)＝min f(x _k+αp _k) (14)

STEP 4: calculate if || g _k+1||≤ε, then illustrate the x that this iterative computation obtains _k+1met the error requirements of defined, stop iteration and export result of calculation, obtaining approximate solution is x ^*=x _k+1, otherwise perform next step;

STEP 5: make s _k=x _k+1-x _k, y _k=g _k+1-g _k, adopt formula (15) to calculate w _k;

$w_k={\left(y_k^T{H}_k{y}_k\right)}^{\frac{1}{2}}(\frac{s_k}{y_k^T{s}_k}-\frac{H_k{y}_k}{y_k^T{H}_k{y}_k})---\left(15\right)$

STEP 6: according to formula (16) BFGS correction formula, calculates order k=k+1, turns STEP2.

$H_{k+1}^{\%}=H_k-E_k=H_k-\frac{H_k{y}_k{y}_k^T{H}_k}{y_k^T{H}_k{y}_k}+\frac{s_k{s}_k^T}{y_k^T{s}_k}+w_k{w}_k^T---\left(16\right)$

(4) fourth stage

When DV-Distance algorithm application being located in three dimensions, due to the restriction of coplane degree threshold value, the unknown node making degree of communication few can not complete location, and becoming can not location node, thus location node coverage rate is reduced.For this problem, the present invention proposes the thought of Dynamic expansion beaconing nodes, oriented unknown node is upgraded to beaconing nodes, thus add the quantity of beaconing nodes in network, thus Signal Coverage Percentage and positioning precision can be improved.

The method and the step that expand beaconing nodes are as follows:

STEP1: first round location is carried out to unknown node, when positioning unknown node, the DCP value of compute location unit, selects best located unit to position according to DCP value;

STEP2: the unknown node after the first round successfully locates is upgraded to beaconing nodes, and give its neighbor node their broadcast of position information, the beaconing nodes of location is taken turns as second;

STEP3: adopt the method in STEP1 to carry out second to the node that the first round cannot locate and take turns location.After not having the unknown node of locating to receive the information of new beaconing nodes, after selecting the positioning unit meeting coplane degree threshold value, enter second and take turns location; Otherwise continue reception information, wait for next round location, until all node locating completes.

In order to verify the performance of the 3D-IDCP algorithm that the present invention proposes, MATLAB2009a is adopted to emulate algorithm.In emulation experiment, node is by random placement in the three dimensions of 100m × 100m × 100m, and node communication radius is set to 40m, and the mean value of 50 execution results is got in experiment.This paper algorithm and DV-Hop and DV-Distance are extended to algorithm 3DV-Hop in three dimensions and 3DV-Distance algorithm is analyzed.Fig. 3 is the design sketch of algorithm, and all beaconing nodes and unknown node are all arranged in three dimensions, and wherein circle represents beaconing nodes, and triangle represents unknown node, the position of the unknown node that cross representative is calculated according to 3D-IDCP algorithm.

Fig. 4 is the comparison diagram of the 3D-IDCP algorithm that proposes of the present invention and 3DV-Hop and 3DV-Distance algorithm position error.As seen from Figure 4, under anchor node is respectively 10%, 15%, 20%, 25%, 30%, 35% situation, 3D-IDCP position error is all less than other two kinds of algorithms.When anchor node ratio increases, the position error of three kinds of algorithms all reduces, and 3D-IDCP Algorithm Error in this paper declines at most, and error reduces about 30%.

Fig. 5 is the comparison diagram of the 3D-IDCP algorithm that proposes of the present invention and 3DV-Hop and 3DV-Distance algorithm Signal Coverage Percentage.What Signal Coverage Percentage represented is the ratio that unknown node can successfully be located.When network-in-dialing degree increases, the coverage rate of three kinds of location algorithms all increases.Time network-in-dialing degree is increased to 10,3D-IDCP algorithm coverage rate reaches 1, represents that in network, all unknown node all can complete location.As seen from Figure 5, the Signal Coverage Percentage of 3D-IDCP algorithm in this paper is obviously better than other two kinds of algorithms.

Claims (8)

1., based on the WSN Three dimensional Targets localization method that the jumping distance of coplane degree is revised, it is characterized in that, comprise the following steps:

Step 1: adopt the distance between RSSI ranging technology measurement adjacent node;

Step 2: receive and forward beaconing nodes information by distance vector exchange agreement, obtains the minimum hop count value of all nodes and beaconing nodes and accumulative jumping distance;

Step 3: according to minimum hop count value in step 2 and accumulative jumping distance, calculate corrected parameter, jump distance according to corrected parameter correction is accumulative;

Step 4: the coplanar angle value calculating each positioning unit, selects best located unit based on coplanar angle value;

Step 5: adopt four sides mensuration to calculate unknown node coordinate according to the best located unit selected;

Step 6: adopt quasi-Newton method to be optimized unknown node coordinate;

Step 7: the node that success is located is promoted to beaconing nodes participation second and takes turns location.

2. the jumping based on coplane degree according to claim 1 is apart from the WSN Three dimensional Targets localization method revised, it is characterized in that: RSSI (Received Signal Strength Indicator in step 1, RSSI) technology, according to the signal strength signal intensity that receiving node receives, the distance between transmitting node to receiving node can be estimated.Signal strength signal intensity is converted to and apart from formula used is:

$d={10}^{\frac{10\mathrm{nlg}{d}_0+\mathrm{PL}\left(d_0\right)-X_{\mathrm{\σ}}-P_{\mathrm{RSSI}}}{10n}}$

In formula, d is the distance between transmitting node to receiving node, and n is wireless channel attenuation coefficient, and general value is 2 ~ 4, d ₀be be known distance, generally obtain by experiment, PL (d ₀) be receiving node be known distance d from transmitting node distance ₀time received signal strength, X _σbe average be 0, variance is σ ²gaussian random noise variable, P _rSSIfor the RSSI value that receiving node receives.

3. the jumping based on coplane degree according to claim 1 is apart from the WSN Three dimensional Targets localization method revised, it is characterized in that: by distance vector exchange agreement in step 2, jumping figure and cumulative distance are initialized as 0, each node compares the jumping figure value of the same beaconing nodes received, retain the information that wherein jumping figure is minimum, then the cumulative jumping segment distance from each beaconing nodes jumping figure is added 1, is finally transmitted to other neighbor nodes.

4. the jumping based on coplane degree according to claim 1 is apart from the WSN Three dimensional Targets localization method revised, and it is characterized in that: calculate corrected parameter in step 3 and adopt following formula:

${\mathrm{\λ}}_K=\frac{\mathrm{\Σ}{L}_{\mathrm{ij}}}{\mathrm{\Σ}{D}_{\mathrm{ij}}}$

In formula, K is unknown node, i and j is beaconing nodes i=1 ... n, j=1 ..., n and i ≠ j, i and j are positive integer, L _ijfor the actual distance between beaconing nodes i to beaconing nodes j, D _ijcumulative distance between beaconing nodes i to beaconing nodes j.

5. the jumping based on coplane degree according to claim 1 is apart from the WSN Three dimensional Targets localization method revised, and it is characterized in that: revise cumulative distance in step 3 and adopt following formula:

L _Ki＝λ _K*D _Ki

In formula, λ _kfor the corrected parameter of unknown node K, D _kifor unknown node K is to the cumulative distance of beaconing nodes i, L _kifor the revised cumulative distance of unknown node K to beaconing nodes i.

6. the jumping based on coplane degree according to claim 1 is apart from the WSN Three dimensional Targets localization method revised, and it is characterized in that: in step 4, a positioning unit comprises 4 beaconing nodes, and the computational methods of its coplanar angle value adopt following computing formula:

$\mathrm{\ρ}=\frac{216v^2}{\underset{i=0}{\overset{3}{\mathrm{\Σ}}}{s}_i\sqrt{(a+b+c)(a+b-c)(a+c-b)(b+c-a)}}$

In formula, v is the tetrahedral volume of four node compositions, and a, b, c are respectively tetrahedron three groups of products to rib length, S _ibe respectively the area in tetrahedron four faces.

7. the jumping based on coplane degree according to claim 1 is apart from the WSN Three dimensional Targets localization method revised, and it is characterized in that: calculate unknown node coordinate in step 5 and adopt following formula:

$\left[\begin{array}{c}x\\ y\\ z\end{array}\right]=\frac{1}{2}{\left[\begin{array}{ccc}{x}_2-x_1& y_2-y_1& z_2-z_1\\ x_3-x_1& y_3-y_1& z_3-z_1\\ x_4-x_1& y_4-y_1& z_4-z_1\end{array}\right]}^{-1}\left[\begin{array}{c}{x}_2^2-x_1^2+y_2^2-y_1^2+z_2^2-z_1^2+d_{\mathrm{KA}}^2-d_{\mathrm{KB}}^2\\ x_3^2-x_1^2+y_3^2-y_1^2+z_3^2-z_1^2+d_{\mathrm{KA}}^2-d_{\mathrm{KC}}^2\\ x_4^2-x_1^2+y_4^2-y_1^2+z_4^2-z_1^2+d_{\mathrm{KA}}^2-D_{\mathrm{kd}}^2\end{array}\right]$

In formula, the coordinate that (x, y, z) is unknown node K, (x ₁, y ₁, z ₁) (x ₂, y ₂, z ₂) (x ₃, y ₃, z ₃) (x ₄, y ₄, z ₄) be the coordinate of four beaconing nodes in positioning unit, d _kA, d _kB, d _kC, d _kDbe respectively the correction cumulative distance between unknown node K and beaconing nodes.

8. the jumping based on coplane degree according to claim 1 is apart from the WSN Three dimensional Targets localization method revised, it is characterized in that: in step 6, adopt quasi-Newton method to be optimized positioning result, positioning and optimizing problem is converted into Unconstrained Optimization Problem, determines that target function is:

$\min F(x,y,z)=\underset{i=1}{\overset{n}{\mathrm{\Σ}}}[{(x_i-x)}^2+{(y_i-y)}^2+{(z_i-z)}^2-{d_i}^2]$

In formula, the coordinate that (x, y, z) is unknown node K, (x _i, y _i, z _i) be the coordinate of beaconing nodes i, i=1,2 ..., n, i are positive integer, d _ifor the cumulative distance of beaconing nodes i to unknown node K.