CN103327603A - Three-dimensional node positioning method used for wireless sensor network based on APIT - Google Patents

Abstract

Provided is a three-dimensional node positioning method used for a wireless sensor network based on an APIT. If an unknown node has at least six neighboring beacon nodes, the relations of tetrahedrons composed of the neighboring beacon nodes of the unknown node and the unknown node are sequentially judged, if the unknown node is included in one tetrahedron, then the tetrahedron is cut through all middle vertical faces of the tetrahedron, by comparing RSSIs of the four beacon nodes forming the tetrahedron received by the unknown node, which cutting portion of the tetrahedron cut through the middle vertical faces the unknown node exists in is confirmed, the intersection of all the cutting portions including the known nodes is calculated to obtain a narrowed space where the unknown node exists, a centroil of the intersection of the narrowed spaces of all the tetrhedrons serves as an estimation position of the unknown node, and therefore the position coordinate of the unknown node is thereby calculated.

Description

The Nodes Three-dimensional positioning mode based on APIT that is used for wireless sensor network

Technical field

The present invention relates to wireless sensor network, relate in particular to a kind of Nodes Three-dimensional positioning mode based on APIT for wireless sensor network.

Background technology

At wireless sensor network (wireless sensor networks, WSN) in, positional information is most important to its monitoring, the position that event occurs or the node location of obtaining information are the important informations that comprises in the sensor node supervisory messages, do not have the supervisory messages of positional information often meaningless.Therefore node locating is one of the most basic function of wireless sensor network, plays a part crucial to the validity of its application.

Received signal strength indicator value (received signal strength indicator, RSSI) is subject to localization method researcher's favor always as the parameter that the most easily obtains among the WSN.Main thought based on the localization method of RSSI value is according to the RSSI attenuation model two internodal RSSI pad values to be directly changed into two internodal distances, at last the position coordinates by the distance calculating node to be positioned between a plurality of beaconing nodes (be equipped with the GPS navigation system or can directly obtain the node of positional information by alternate manner) and node to be positioned (node of Location-Unknown).

Yet RSSI is affected by environment larger, along with its performance performance of the variation of application scenarios differs.As: the relevance of RSSI and wireless signal is larger, if the close ground of sensor node, it transmits easily by geomagnetic noise.Spacious playground is lacked than hurst owing to barrier, so in the ward, the performance of RSSI performance better.

In view of the above, the accuracy of RSSI relies on its applied environment to a great extent, and under the scene of a lot of complex-terrains, RSSI can not change into exactly euclidean distance between node pair information and cause larger error.At this kind complex condition, people have proposed a kind ofly to use but strictly do not rely on localization method---the APIT localization method of RSSI value.It only need RSSI's " fuzzy value " come the distance of distance between comparison node, strictly RSSI is not converted into accurate distance value.So in complex environment, in multi-obstacle avoidance scene, near-earth scene, APIT has avoided the RSSI value because of the inaccurate situation that is interfered dexterously.

The APIT localization method is a kind of localization method that has nothing to do with range finding.In other words, this localization method is not the localization method that uses the physical parameter value that records to be directly changed into euclidean distance between node pair and then obtain node location to be positioned.The principle of APIT localization method is as follows:

Its theoretical support is some method of testing (perfect point-in-triangulation test in the best triangle, PIT), if namely have a direction, node M along this direction move can be simultaneously away from or near A, B, C, M is outside △ ABC, shown in Fig. 1 (b) so; Otherwise M is in △ ABC, shown in Fig. 1 (a).

In the APIT localization method, the RSSI value that usually receives more separately by exchange between neighbor node (node in communication range), the rule of utilization " RSSI is less, and euclidean distance between node pair is larger ", the distance of a certain anchor node of judging distance.Such as Fig. 2 (a), node M to be positioned and neighbor node 1 exchange message are as can be known, the RSSI value that node M receives anchor node B, C receives the RSSI value of anchor node B, C greater than node 1, and node M receives the RSSI value of anchor node A receives anchor node A less than node 1 RSSI value.According to the comparison of RSSI value, if node M moves to node 1 position, will be away from Node B, C and close node A.Successively neighbor node 2,3,4 is carried out identical judgement, node M to be positioned is in △ ABC.And in Fig. 2 (b) as can be known, if node M moves to neighbor node 2 positions, will simultaneously near A, B, C, conclude that so M is outside △ ABC.Finally, such as Fig. 2 (c), treat the affiliated leg-of-mutton overlapping region of location node and use the barycenter method, calculate its barycenter as the coordinate of node to be positioned.

Here, because the amount of calculation that the barycenter of calculating delta-shaped region needs is larger, so generally, the researcher adopts the method for network scanning (GRID SCAN).Its purport is that whole plane is divided into large square such as some grades.The corresponding counter of each square.Judge each triangle that beaconing nodes consists of, if this triangle comprises node to be positioned, then each the square corresponding counter in this triangle adds one; If this triangle does not comprise node to be positioned, then each the square corresponding counter in this triangle subtracts one.Sieve is got all squares of rolling counters forward peak at last, asks for the mean value of these square barycenter as the estimated position of node to be positioned.Schematic diagram is shown in Fig. 3 (a), (b).

And when judging node to be positioned, if the neighbor node number of node to be positioned is less, the APIT localization method is often because " in-to-out error " and " out-to-in error " two kinds of situations appear in boundary effect.When nodal distance beaconing nodes to be positioned forms leg-of-mutton edge nearer the time, be easy to be judged as and be positioned at triangle originally being positioned at the outer node to be positioned of triangle, also be easy to and originally be positioned at outside the node locating to be positioned and triangle of triangle.Its schematic diagram such as Fig. 4.M is node to be positioned, and N is the neighbor node of M, and Fig. 4 (a) is the schematic diagram of " in-to-out error ", and M receives that the RSSI value of A, B, three beaconing nodes of C all receives the RSSI value of A, B, three nodes of C less than N.Principle M according to the APIT location should be judged as the outside that is positioned at △ ABC, but actual M is positioned at triangle inside.Fig. 4 (b) is the schematic diagram of " out-to-in error ", and M receives that the RSSI of A, two beaconing nodes of B receives the RSSI of A, B greater than N, and M receives that the RSSI of C node receives the RSSI that C is ordered less than the N point.Press the APIT localization method, it is inner that M is positioned at △ ABC by erroneous judgement, and reality is but outside at △ ABC.

The present localization method based on APIT also concentrates on the two dimensional surface mostly, and its weak point is that it can only be with whole network design at two dimensional surface, and for the node that is deployed in the three dimensions, two-dimensional location method is felt simply helpless.And in three-dimensional localization, it is large that the complexity of calculating, traffic etc. factors becomes, and causes the difficulty of three-dimensional localization to become large precision step-down.

Summary of the invention

The object of the invention is to provides a kind of three-dimensional node locating based on APIT and refinement method thereof not significantly to increase hardware, communication and computing cost as prerequisite.The method should be applicable in three dimensions the sensor network of extensive random placement, and simple, practicality is stronger, and than the APIT-3D localization method, aspect positioning accuracy, have by a relatively large margin to promote.

The Nodes Three-dimensional positioning mode based on APIT for wireless sensor network of the present invention, it comprises: if unknown node has at least 6 neighbours' beaconing nodes, then judge successively each tetrahedron that neighbours' beaconing nodes of this unknown node consists of and the relation of this unknown node; If this unknown node is contained in the tetrahedron, with these tetrahedral all middle vertical planes this tetrahedron is cut; Receive the RSSI that consists of these tetrahedral 4 beaconing nodes by this unknown node relatively, determine unknown node is present in tetrahedral which cutting part after the middle vertical plane cutting; The all cutting parts that comprises this unknown node of this tetrahedron are asked for the space that dwindles that common factor obtains the unknown node existence; With the barycenter of all tetrahedral common factors that dwindle the space estimated position as unknown node, thereby calculate the position coordinates of unknown node.

Preferably, if unknown node has 2-5 neighbours' beaconing nodes, adopt following formula to calculate its position coordinates;

$\left\{\begin{array}{c}{x}_{\mathrm{estimate}}=\frac{\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}{x}_i*{10}^{\frac{{\mathrm{RSSI}}_i}{20}}}{\underset{i=1}{\overset{\mathrm{<figure-callout\; id="10"\; label="n"\; filenames="HDA0000144926720000013.png,HDA0000144926720000041.png"\; state="\{\{state\}\}">n</figure-callout>}}{\mathrm{\&Sigma;}}}{10}^{\frac{{\mathrm{RSSI}}_i}{20}}}\\ y_{\mathrm{estimate}}=\frac{\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}{y}_i*{10}^{\frac{{\mathrm{RSSI}}_i}{20}}}{\underset{i=1}{\overset{\mathrm{<figure-callout\; id="10"\; label="n"\; filenames="HDA0000144926720000013.png,HDA0000144926720000041.png"\; state="\{\{state\}\}">n</figure-callout>}}{\mathrm{\&Sigma;}}}{10}^{\frac{{\mathrm{RSSI}}_i}{20}}}\\ z_{\mathrm{estimate}}=\frac{\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}{z}_i*{10}^{\frac{{\mathrm{RSSI}}_i}{20}}}{\underset{i=1}{\overset{\mathrm{<figure-callout\; id="10"\; label="n"\; filenames="HDA0000144926720000013.png,HDA0000144926720000041.png"\; state="\{\{state\}\}">n</figure-callout>}}{\mathrm{\&Sigma;}}}{10}^{\frac{{\mathrm{RSSI}}_i}{20}}}\end{array}\right.$

Wherein, RSSI _iRepresent the RSSI value that unknown node receives i neighbours' beaconing nodes, n represents the number of neighbours' beaconing nodes of unknown node, (x _i, y _i, z _i) represent respectively the three-dimensional coordinate of each neighbours' beaconing nodes, (x _Estimate, y _Estimate, z _Estimate) be the position coordinates of unknown node.

Preferably, arrange that two variablees represent respectively that unknown node is judged as in the tetrahedron or outer; If the RSSI of tetrahedral 4 the neighbours' beaconing nodes of the formation that a certain neighbor node is received all is greater than or less than the RSSI that unknown node is received 4 neighbours' beaconing nodes, then represent the variable of unknown node outside tetrahedron and add one, otherwise another variable adds one; Judged that successively all neighbor nodes receive that RSSI and unknown node receive the magnitude relationship of RSSI, more set two variable sizes are to determine that unknown node is in tetrahedron or outside tetrahedron.

Preferably, determining that unknown node is present in the process of tetrahedral which cutting part after the middle vertical plane cutting, if

$(x_b-x_a)[x-\frac{(x_b+x_a)}{2}]+(y_b-y_a)[y-\frac{(y_b+y_a)}{2}]+(z_b-z_a)[z-\frac{(z_b+z_a)}{2}]>0$

Set up, AN＞BN then, then A, N lay respectively at the both sides of middle vertical plane; If AN＜BN, then A, N are positioned at the homonymy of middle vertical plane; Its middle conductor AB is a vertical limit of tetrahedral middle vertical plane, and line segment AB two-end-point coordinate is respectively A (x _a, y _a, z _a) B (x _b, y _b, z _b), N represents unknown node, and its coordinate is N (x, y, z).

Preferably, the described barycenter that dwindles the common factor in space obtains by following steps: whole space is divided into a plurality of equal-sized small cubes grids, the corresponding counter of each grid; Each tetrahedron is carried out following operation: if a tetrahedron comprises unknown node, then the counter of the grid in this tetrahedron adds one; If a tetrahedron does not comprise unknown node, then the counter of the grid in this tetrahedron subtracts one; If this tetrahedral grid and unknown node are positioned at the same side of middle vertical plane, the counter that this grid is corresponding adds one again; If this tetrahedral grid and unknown node be not in the same side of middle vertical plane, the counter that this grid is corresponding subtracts one; Screen at last the highest grid of rolling counters forward, ask for the barycenter of figure that these grids form as the described barycenter that dwindles the common factor in space.

Preferably, the described barycenter that dwindles the common factor in space obtains by following steps: whole space is divided into a plurality of equal-sized small cubes grids, the corresponding counter of each grid; To each tetrahedron and should be tetrahedral each middle vertical plane carry out following operation: if a tetrahedron comprises unknown node, then this tetrahedron is interior is in counter corresponding to the grid of a side of a middle vertical plane with unknown node and adds one.

Description of drawings

From the following description to preferred embodiments and drawings that purport of the present invention and usefulness thereof are described, above and other purpose of the present invention, characteristics and advantage will be apparent, in the accompanying drawings:

Fig. 1 (a), (b) are the PIT schematic diagram;

Fig. 2 (a), (b), (c) are APIT location schematic diagram;

Fig. 3 (a), (b) are network scanning explanation schematic diagram;

Fig. 4 (a), (b) are respectively in-to-out error and out-to-in error schematic diagram;

Fig. 5 is by tetrahedron schematic diagram after 6 cuttings;

Fig. 6 causes the low two-dimensional representation of positioning accuracy for neighbours' Beacon Point is less;

Fig. 7 is the APIT-3D schematic diagram;

Fig. 8 is middle vertical plane cutting schematic diagram;

Fig. 9 is expense comparison diagram positioning time of the present invention and APIT-3D method.

Embodiment

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

Neighbor node: the node that can communicate by letter mutually is called neighbor node mutually.

Neighbours' beaconing nodes: refer to the beaconing nodes that to communicate by letter.

Beaconing nodes: the node with the self-align ability of GPS.

Cutting part: represent tetrahedron by an one rear various piece that forms of middle vertical plane cutting.

Dwindle the space: the tetrahedral common factor that comprises all cutting parts of unknown node.

At first, wireless sensor node is sowed in three dimensions at random.Wherein beaconing nodes has the self-align ability of GPS.All beaconing nodes obtain by GPS location after the self-position information, all node broadcasts self-position information and ID in self communication range.The all the sensors node receives the information of beaconing nodes broadcasting and the RSSI value that record receives signal.If unknown node is received the message number of different beaconing nodes and reached 4, carry out the APIT-3D localization method.If the information of not receiving is orientated unknown node as space center.If receiving the message number is 1～3, then unknown node is positioned the barycenter of the figure (point, line segment, triangle) that the beaconing nodes of received breath forms.

If unknown node receives the message number of different beaconing nodes and reach 6, judge that then unknown node is whether in the tetrahedron that beaconing nodes consists of.Concrete grammar is: arrange that two variablees represent respectively that unknown node is judged as in the tetrahedron or outer.If the RSSI of tetrahedral 4 beaconing nodes of the formation that a certain neighbor node is received all is greater than or less than the RSSI that unknown node is received 4 beaconing nodes, then represent the variable of unknown node outside tetrahedron and add one, otherwise another variable adds one.Judged that successively all neighbor nodes receive that RSSI and unknown node receive the magnitude relationship of RSSI, more set two variable sizes are to conclude the position relationship between tetrahedron and unknown node.Its basis for estimation is: given line segment AB two-end-point coordinate is respectively A (x _a, y _a, z _a) B (x _b, y _b, z _b), satisfy AN＞BN such as fruit dot N (x, y, z), namely A, N are positioned at the both sides of middle vertical plane, then have:

$(x_b-x_a)[x-\frac{(x_b+x_a)}{2}]+(y_b-y_a)[y-\frac{(y_b+y_a)}{2}]+(z_b-z_a)[z-\frac{(z_b+z_a)}{2}]>0---\left(1\right)$

Set up, as shown in Figure 7.

If the number of neighbours' beaconing nodes of certain unknown node is n, then can consist of C _n ⁴Individual tetrahedron is judged the relation of these tetrahedrons and unknown node successively.If unknown node is contained in the tetrahedron, adopt " middle vertical plane cutting " method.Receive the RSSI that consists of tetrahedral 4 beaconing nodes by comparing unknown node, determine unknown node is present in rear tetrahedral which part of middle vertical plane cutting, such as Fig. 8.Get at last the barycenter of common factor of the possible Existential Space after reduced in all tetrahedrons as the estimated position of location.

In asking the process of barycenter, take improved GRID SCAN method.Be about to whole space and be divided into a plurality of equal-sized small cubes grids, the corresponding counter of each grid.In the calibration process, the counter that will belong to the grid in the tetrahedron that comprises unknown node adds one, and all the other grid counters subtract one.If grid and unknown node are positioned at the same side of middle vertical plane, counter adds one again, otherwise subtracts one.Judge one by one each tetrahedron and its 6 middle vertical planes with this.Screen at last the highest grid of rolling counters forward, ask for the barycenter of figure that these grids form as positioning result.

For because the less low unknown node of positioning accuracy that causes of neighbours' beaconing nodes number, the present invention adopts the RSSI weighting to remedy the refinement method.Receive that according to unknown node the RSSI value of neighbours' beaconing nodes asks for weight, obtain the computing formula of position.

Be the unknown node of 2-5 for neighbours' beaconing nodes number, adopt following calibration formula:

$\left\{\begin{array}{c}{x}_{\mathrm{estimate}}=\frac{\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}{x}_i*{10}^{\frac{{\mathrm{RSSI}}_i}{20}}}{\underset{i=1}{\overset{\mathrm{<figure-callout\; id="10"\; label="n"\; filenames="HDA0000144926720000013.png,HDA0000144926720000041.png"\; state="\{\{state\}\}">n</figure-callout>}}{\mathrm{\&Sigma;}}}{10}^{\frac{{\mathrm{RSSI}}_i}{20}}}\\ y_{\mathrm{estimate}}=\frac{\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}{y}_i*{10}^{\frac{{\mathrm{RSSI}}_i}{20}}}{\underset{i=1}{\overset{\mathrm{<figure-callout\; id="10"\; label="n"\; filenames="HDA0000144926720000013.png,HDA0000144926720000041.png"\; state="\{\{state\}\}">n</figure-callout>}}{\mathrm{\&Sigma;}}}{10}^{\frac{{\mathrm{RSSI}}_i}{20}}}\\ z_{\mathrm{estimate}}=\frac{\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}{z}_i*{10}^{\frac{{\mathrm{RSSI}}_i}{20}}}{\underset{i=1}{\overset{\mathrm{<figure-callout\; id="10"\; label="n"\; filenames="HDA0000144926720000013.png,HDA0000144926720000041.png"\; state="\{\{state\}\}">n</figure-callout>}}{\mathrm{\&Sigma;}}}{10}^{\frac{{\mathrm{RSSI}}_i}{20}}}\end{array}\right.---\left(2\right)$

Wherein, RSSI _iRepresent the RSSI value that unknown node receives i neighbours' beaconing nodes.N represents the number of neighbours' beaconing nodes of unknown node.(x _i, y _i, z _i) represent respectively the three-dimensional coordinate of each neighbours' beaconing nodes.

Formula (2) is derived by formula (3).

$\left\{\begin{array}{c}{x}_{\mathrm{estimate}}=\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}\frac{x_i}{d_i}/\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}\frac{1}{d_i}\\ y_{\mathrm{estimate}}=\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}\frac{y_i}{d_i}/\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}\frac{1}{d_i}\\ Z_{\mathrm{estimate}}=\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}\frac{z_i}{d_i}/\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}\frac{1}{d_i}\end{array}\right.---\left(3\right)$

D in the formula (3) _iRepresent the distance between unknown node and i neighbours' beaconing nodes.And have by formula (3):

$\underset{d_a{d}_b{d}_c{d}_d\&RightArrow;0}{\lim }\sqrt{{(x-x_{\mathrm{estimate}})}^2+{(y-y_{\mathrm{estimate}})}^2+{(z-z_{\mathrm{estimate}})}^2}=0---\left(4\right)$

Set up.Draw from formula (4) analysis, the distance between unknown node and beaconing nodes levels off to 0, and the error of this refinement method is less, levels off to 0.

The relative APIT-3D localization method of expense that experiment showed, the method only has a little increase, sees Fig. 9.

Although illustrated and described the preferred embodiments of the present invention, it is contemplated that, those skilled in the art can design various modifications of the present invention in the spirit and scope of claims.

Claims (6)

1. Nodes Three-dimensional positioning mode based on APIT that is used for wireless sensor network is characterized in that:

If unknown node has at least 6 neighbours' beaconing nodes, then judge successively each tetrahedron that neighbours' beaconing nodes of this unknown node consists of and the relation of this unknown node;

If this unknown node is contained in the tetrahedron, with these tetrahedral all middle vertical planes this tetrahedron is cut; Receive the RSSI that consists of these tetrahedral 4 beaconing nodes by this unknown node relatively, determine unknown node is present in tetrahedral which cutting part after the middle vertical plane cutting; The all cutting parts that comprises this unknown node of this tetrahedron are asked for the space that dwindles that common factor obtains the unknown node existence;

With the barycenter of all tetrahedral common factors that dwindle the space estimated position as unknown node, thereby calculate the position coordinates of unknown node.

2. the Nodes Three-dimensional positioning mode based on APIT for wireless sensor network as claimed in claim 1 is characterized in that:

If unknown node has 2-5 neighbours' beaconing nodes, adopt following formula to calculate its position coordinates;

$\left\{\begin{array}{c}{x}_{\mathrm{estimate}}=\frac{\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}{x}_i*{10}^{\frac{{\mathrm{RSSI}}_i}{20}}}{\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}{10}^{\frac{{\mathrm{RSSI}}_i}{20}}}\\ y_{\mathrm{estimate}}=\frac{\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}{y}_i*{10}^{\frac{{\mathrm{RSSI}}_i}{20}}}{\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}{10}^{\frac{{\mathrm{RSSI}}_i}{20}}}\\ z_{\mathrm{estimate}}=\frac{\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}{z}_i*{10}^{\frac{{\mathrm{RSSI}}_i}{20}}}{\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}{10}^{\frac{{\mathrm{RSSI}}_i}{20}}}\end{array}\right.$

Wherein, RSSI _iRepresent the RSSI value that unknown node receives i neighbours' beaconing nodes, n represents the number of neighbours' beaconing nodes of unknown node, (x _i, y _i, z _i) represent respectively the three-dimensional coordinate of each neighbours' beaconing nodes, (x _Estimate, y _Estimate, z _Estimate) be the position coordinates of unknown node.

3. the Nodes Three-dimensional positioning mode based on APIT for wireless sensor network as claimed in claim 1 is characterized in that: judge this unknown node whether the concrete grammar in the tetrahedron that neighbours' beaconing nodes consists of be:

Arrange that two variablees represent respectively that unknown node is judged as in the tetrahedron or outer;

If the RSSI of tetrahedral 4 the neighbours' beaconing nodes of the formation that a certain neighbor node is received all is greater than or less than the RSSI that unknown node is received 4 neighbours' beaconing nodes, then represent the variable of unknown node outside tetrahedron and add one, otherwise another variable adds one;

Judged that successively all neighbor nodes receive that RSSI and unknown node receive the magnitude relationship of RSSI, more set two variable sizes are to determine that unknown node is in tetrahedron or outside tetrahedron.

4. such as claim 1 or the 3 described Nodes Three-dimensional positioning modes based on APIT for wireless sensor network, it is characterized in that: determining that unknown node is present in the process of tetrahedral which cutting part after the middle vertical plane cutting, if

$(x_b-x_a)[x-\frac{(x_b+x_a)}{2}]+(y_b-y_a)[y-\frac{(y_b+y_a)}{2}]+(z_b-z_a)[z-\frac{(z_b+z_a)}{2}]>0$

Set up, AN＞BN then, then A, N lay respectively at the both sides of middle vertical plane; If AN＜BN, then A, N are positioned at the homonymy of middle vertical plane;

Its middle conductor AB is a vertical limit of tetrahedral middle vertical plane, and line segment AB two-end-point coordinate is respectively A (x _a, y _a, z _a) B (x _b, y _b, z _b), N represents unknown node, and its coordinate is N (x, y, z).

5. such as claim 1 or the 3 described Nodes Three-dimensional positioning modes based on APIT for wireless sensor network, it is characterized in that: the described barycenter that dwindles the common factor in space obtains by following steps:

Whole space is divided into a plurality of equal-sized small cubes grids, the corresponding counter of each grid; Each tetrahedron is carried out following operation:

If a tetrahedron comprises unknown node, then the counter of the grid in this tetrahedron adds one; If a tetrahedron does not comprise unknown node, then the counter of the grid in this tetrahedron subtracts one; If this tetrahedral grid and unknown node are positioned at the same side of middle vertical plane, the counter that this grid is corresponding adds one again; If this tetrahedral grid and unknown node be not in the same side of middle vertical plane, the counter that this grid is corresponding subtracts one;

Screen at last the highest grid of rolling counters forward, ask for the barycenter of figure that these grids form as the described barycenter that dwindles the common factor in space.

6. such as claim 1 or the 3 described Nodes Three-dimensional positioning modes based on APIT for wireless sensor network, it is characterized in that: the described barycenter that dwindles the common factor in space obtains by following steps:

Whole space is divided into a plurality of equal-sized small cubes grids, the corresponding counter of each grid; Each tetrahedron and this tetrahedral each middle vertical plane are carried out following operation:

If a tetrahedron comprises unknown node, then be in counter corresponding to the grid of a side of a middle vertical plane with unknown node in this tetrahedron and add one.

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