CN104185272A - WSN location method based on WSDV-Hop (Weighted and Selected DV-Hop) - Google Patents

Abstract

The invention relates to a location algorithm in wireless sensor network (WSN), provides a WSN location method based on WSDV-Hop, and aims at reducing location errors and improving the location precision. According to error of the correction values of anchor nodes and the hop number between the anchor nodes and an unknown node, normalized weighting is carried out on the correction values of the anchor nodes to optimize the average hop distance of the unknown node; according to the hop number between the anchor nodes and the unknown node, an anchor node for location computation is selected to avoid error accumulation and reduce the computational complexity; and normalized weighted optimization is carried on the location coordinates, which are obtained by combined calculation of the different anchor nodes, to obtain a final location coordinate of the unknown node. The simulation result shows that the anchor node information can be fully utilized, the average location error of the nodes is effectively reduced, and the coverage rate of location is improved.

Description

WSN localization method based on optimizing Average hop distance and preferred anchor node

Technical field

The present invention relates to a kind of WSN localization method based on optimizing Average hop distance and preferred anchor node, specifically a kind of based on optimizing the Average hop distance of unknown node and the preferably weighting and preferred DV-Hop localization method (WSDV-Hop) of anchor node, belong to wireless sensor network field of locating technology.

Background technology

At wireless sensor network (wireless sensor network, WSN) a lot of fields of research, the physical location that often must know node just has application value, in some residing position of particular application data, than data itself, have more value, such as the position of fire generation, the waters of water level rising and Military Application field etc., so node locating research is must obligato link.And global position system GPS is due to the restriction of the aspects such as price, power consumption and volume, be difficult to be applied in WSN completely.In addition, some existing location algorithms are due to computation complexity and need the reasons such as related hardware equipment support, are not also suitable for WSN.Therefore, under resource-constrained prerequisite, design high position precision, amount of calculation moderate, without additional hardware condition and the node positioning method that is applicable to actual WSN environment, there is realistic meaning.

At present, in the main localization method of WSN, whether foundation needs distance actual between measured node can be divided into algorithm and the algorithm based on non-ranging based on range finding.Location algorithm based on range finding is first by the internodal distance of extra measurement device or angle, then calculates the coordinate of unknown node, and typical algorithm has: RSSI, TOA, TDOA, AOA etc.Location algorithm based on non-ranging only need to utilize between node the information such as jumping figure and in addition simple operation just can estimate internodal distance, main algorithm includes barycenter, convex programming, DV-Hop, MDS-MAP etc.Algorithm based on range finding can be obtained good positioning precision generally, but the energy consumption of required cost, node also can be larger.Algorithm based on non-survey certificate relies on internodal connectedness to position, and amount of calculation is little, realization is simple but position error is larger.By research and improvement, much can meet the location requirement of WSN, wherein DV-Hop is one of algorithm receiving much concern most.

DV-Hop algorithm is realized simple, and Average hop distance, jumping figure by node position to calculate and just can obtain the coordinate of unknown node, and algorithm cost is low, and calculating and communication overhead are moderate, lower to hardware requirement, are applicable to distributed network, favorable expandability.The part but DV-Hop algorithm also still comes with some shortcomings, such as unknown node in algorithm only utilizes corrected value from its nearest anchor node as Average hop distance, can make internodal estimated distance and final location Calculation produce larger error; The anchor node combination of choosing at random when location Calculation also can cause larger impact to positioning precision.

DV-Hop location algorithm

The core of DV-Hop algorithm is to utilize internodal estimated distance to replace actual measurement distance, and estimated distance is to multiply each other to obtain by the jumping figure between unknown node and anchor node and Average hop distance; Then by the coordinate of estimated distance and anchor node, calculate the elements of a fix of unknown node.DV-Hop algorithm is comprised of three phases:

The first step: obtain internodal minimum hop count

Anchor node sends in the mode of broadcast the self-position information tuple that comprises hop count field to neighbor node, the initial value of hop count field is made as 0.Receiving node adds 1 by jumping figure after receiving this information tuple, records position and the jumping figure of this anchor node, and this tuple is transmitted to its neighbor node.If node receives a plurality of tuples from same anchor node, node only retains the tuple information of jumping figure minimum.In network, each node can both be recorded oneself to the minimum hop count of each anchor node by this method, and obtains the positional information of anchor node.

Second step: the distance between estimation unknown node and anchor node

Suppose that anchor node adds up to m, wherein arbitrary anchor node A _iin obtaining network all the other anchor node coordinates and and the minimum hop count between them after, can calculate the Average hop distance C of oneself _i, also referred to as network calibration value:

$C_i=\frac{\underset{j\≠i}{\overset{m}{\underset{j=1,}{\mathrm{\Σ}}}}\sqrt{{(x_i-x_j)}^2+{(y_i-y_j)}^2}}{\underset{j\≠i}{\overset{m}{\underset{j=1,}{\mathrm{\Σ}}}}{h}_{\mathrm{ij}}}---\left(1\right)$

In formula, (x _i, y _i), (x _j, y _j) be respectively anchor node A _iand A _jcoordinate; h _ijanchor node A _iand A _jbetween minimum hop count.

Each anchor node is broadcast to the corrected value of oneself in network, and unknown node only receives the corrected value of first acquisition, and the Average hop distance using it as self.Then, unknown node by by Average hop distance and the jumping figure apart from each anchor node obtaining before multiply each other obtain and each anchor node between estimated distance.

The 3rd step: calculate unknown node coordinate

If unknown node obtains the estimated distance between itself and three and above anchor node, can utilize trilateration coordinates computed.

Problem and analysis that algorithm exists

The advantage of DV-Hop location algorithm is that computational process is simple, and hsrdware requirements are lower, but also exists the shortcoming that position error is larger.By analysis and research, the source that error produces mainly comprise following some:

(1) anchor node combinatorial topology situation is uncontrollable.In actual WSN environment, sensor node often broadcasts sowing at random, and wherein anchor node distributes and probably occurs extremely irrational situation.And the topology of anchor node will have a huge impact for the positioning precision of node, some are distributed in the unknown node of network edge, can may occur owing to receiving the anchor node information of negligible amounts situation about cannot locate.

(2) between node, use and jump apart from replacing actual range.In DV-Hop algorithm, by the jumping segment distance between node, two internodal air line distances have been replaced.Due to the randomness that node is thrown in, the distance between the every jumping of node conventionally can be the same, and the multihop path being connected between anchor node and unknown node is not also straight line conventionally.Therefore, the impact due to factors such as jumping figure, jumping segment distances can make the estimated value of euclidean distance between node pair and actual value have larger error.

(3) Average hop distance is subject to single anchor node corrected value error effect.Because unknown node is used that anchor node corrected value receive at first as Average hop distance, and just there is certain error in anchor node corrected value self, and the limitation of single anchor node etc. all can cause the accumulation of error.

The error existing for DV-Hop algorithm produces reason, and improving one's methods that some are relevant is suggested in succession:

(1) in order to make unknown node more approach actual range to the estimated distance between each anchor node, the corrected value of all anchor nodes in network can be averaging, unknown node utilizes this mean value as Average hop distance.

(2) when calculating Average hop distance, unknown node introduces weight, according to and unknown node between jumping figure size, to the corrected value of different anchor nodes, give different weights, the Average hop distance that unknown node obtains like this can be better with reference to the anchor node of the whole network.

(3) on DV-Hop algorithm basis, three anchor nodes selecting approximate equilateral triangle by the triangle cosine law participate in location Calculation, and launch quadratic equation linearisation by Taylor, method by iteration is further optimized positioning precision, afterwards the unknown node after optimizing is upgraded to anchor node, participate in the location Calculation of all the other unknown node.

These improvement can improve the positioning precision of DV-Hop algorithm to a certain extent, but also all still exist some shortcomings, mainly comprise following 2 points:

1. the Average hop distance error of unknown node is still larger.Existing improving one's methods adds calculating by the corrected value of all anchor nodes mostly, is averaging or gives different weights, although do like this, considered the of overall importance of network, only relies on jumping figure well to the Average hop distance of unknown node, not revise.

2. the anchor node topology of How to choose participation location Calculation has larger impact to positioning result.When occurring anchor node combination conllinear or approaching the situations such as conllinear, position error has obvious increase.

Due to topology by the anchor node combination that above can know algorithm to produce error be mainly by the inaccurate of unknown node Average hop distance and participate in calculating for DV-Hop algorithm and relevant analysis of improving one's methods is not good, therefore the present invention improves from these two aspects respectively, and proposes Average hop distance based on corrected value error weighted optimization and the WSDV-Hop location algorithm based on jumping figure and elements of a fix value.

Summary of the invention

Goal of the invention: the present invention is directed to the reason that in DV-Hop algorithm, positioning precision is not high and analyze, find source of error to improve, proposition is based on optimizing Average hop distance and the preferably weighting and preferred DV-Hop (Weighted and Selected DV-Hop, WSDV-Hop) localization method of anchor node.

Technical scheme: after having analyzed DV-Hop Algorithm Error source, known algorithm produces error be mainly by the inaccurate of unknown node Average hop distance and select to participate in the topology situation of the anchor node combination of calculating not good due to, so the present invention propose weighted optimization Average hop distance and preferably the WSDV-Hop localization method of anchor node be mainly divided into three parts.

A WSN localization method based on optimizing Average hop distance and preferred anchor node, comprising:

1. optimize Average hop distance

Unknown node can receive the corrected value from a plurality of anchor nodes, then to each corrected value, gives different weights, and weights size determines by two factors, and the one, anchor node corrected value mistake extent, another is the jumping figure between anchor node and unknown node.Finally each anchor node corrected value normalization weighting is processed, obtained Average hop distance.

Asking for like this Average hop distance is to consider based on two aspects: first, for whole network, the corrected value that single anchor node is estimated may produce larger deviation, and only uses the corrected value of an anchor node also to waste the numerous information in network.Secondly, for unknown node, different to the reflection of its localized network state apart from the anchor node that its jumping figure is different, from the less anchor node of its jumping figure, can embody better near the connection situation of localized network unknown node.Meanwhile, self error of anchor node corrected value is less, just more can reduce the error of unknown node Average hop distance.

2. preferred anchor node

Unknown node optimizes apart from oneself nearer a part of anchor node and participates in location Calculation, makes the jumping figure value between these anchor nodes and unknown node be less than the average number of hops between all anchor nodes and this unknown node.

This is that anchor node is more apart from the jumping figure of unknown node due to when the nodes skewness, and the possibility of the jumping section path deviation straight line between them is larger, and consequent estimated distance error is also larger.So first anchor node is done to certain screening, select apart from the less anchor node of unknown node jumping figure, so not only can reduce in advance the impact of the accumulation of error on location Calculation, also can reduce certain amount of calculation simultaneously.

3. optimum position coordinate figure

Using the coordinate figure of the unknown node calculating by the combination of different anchor nodes candidate's coordinate in network all, by weighted optimization, calculate optimum coordinate figure.Suppose that in network, having n unknown node, the anchor node optimizing is m, for arbitrary unknown node N _u, u=1,2 ... n randomly draws three producible being combined as in anchor node kind, use trilateration to calculate node coordinate, be designated as E _k, can be used as N _ucandidate's elements of a fix.To each candidate's coordinate, between three anchor nodes that the weights size of giving adopts according to it and required unknown node, jumping figure sum decides, and jumping figure sum is less gives larger weights, for jumping figure sum larger give less weights.The elements of a fix that finally obtain are right result after individual candidate's elements of a fix value normalization weighting is processed.

Beneficial effect: on the basis of DV-Hop algorithm, the present invention proposes to calculate Average hop distance and the WSDV-Hop localization method based on the preferred anchor node of jumping figure and optimum position coordinate based on corrected value error weighted optimization.The method has not only improved the accuracy of Average hop distance, avoids the impact of bad anchor node combinatorial topology on elements of a fix accuracy, and has selected preferably elements of a fix value.By the emulation comparison with DV-Hop algorithm, WDV-Hop algorithm and SDV-Hop algorithm, WSDV-Hop algorithm all improves at aspects such as node locating precision, Signal Coverage Percentages.

Accompanying drawing explanation

Fig. 1 is the flow chart of WSDV-Hop localization method;

Fig. 2 is Signal Coverage Percentage comparative graph;

Fig. 3 is average position error and anchor node Figure of the quantitative relationship;

Fig. 4 is average position error and unknown node Figure of the quantitative relationship;

Fig. 5 is average position error and communication radius graph of a relation.

Embodiment

Below in conjunction with specific embodiment, further illustrate the present invention, should understand these embodiment is only not used in and limits the scope of the invention for the present invention is described, after having read the present invention, those skilled in the art all fall within the application's claims limited range to the modification of the various equivalent form of values of the present invention.

1. optimize Average hop distance

Unknown node can receive the corrected value from a plurality of anchor nodes, then to each corrected value, gives different weights, and weights size determines by two factors, and the one, anchor node corrected value mistake extent, another is the jumping figure between anchor node and unknown node.Finally each anchor node corrected value normalization weighting is processed, obtained Average hop distance.

2. preferred anchor node

Unknown node optimizes apart from oneself nearer a part of anchor node and participates in location Calculation, makes the jumping figure value between these anchor nodes and unknown node be less than the average number of hops between all anchor nodes and this unknown node.

3. optimum position coordinate figure

Using the coordinate figure of the unknown node calculating by the combination of different anchor nodes candidate's coordinate in network all, by weighted optimization, calculate optimum coordinate figure.Suppose that in network, having n unknown node, the anchor node optimizing is m, for arbitrary unknown node N _u, u=1,2 ... n randomly draws three producible being combined as in anchor node kind, use trilateration to calculate node coordinate, be designated as E _k, can be used as N _ucandidate's elements of a fix.To each candidate's coordinate, between three anchor nodes that the weights size of giving adopts according to it and required unknown node, jumping figure sum decides, and jumping figure sum is less gives larger weights, for jumping figure sum larger give less weights.The elements of a fix that finally obtain are right result after individual candidate's elements of a fix value normalization weighting is processed.

By above three parts, DV-Hop algorithm is improved and obtains WSDV-Hop algorithm, when asking for Average hop distance, consider each anchor node corrected value error and jumping figure, by the Average hop distance to corrected value weighted optimization unknown node; According to the preferred anchor node of the jumping figure between unknown node and anchor node, participate in location Calculation; The elements of a fix value of finally combination of different anchor nodes being calculated to gained is weighted optimization, usings the elements of a fix value of normalization weighting as the final elements of a fix of unknown node.

The thought of corresponding WSDV-Hop algorithm, the key step of WSDV-Hop algorithm is also comprised of weighted optimization Average hop distance, preferred anchor node and optimum position coordinate figure three parts; Concrete steps based on optimizing the WSN localization method of Average hop distance and preferred anchor node are:

The first step: the Average hop distance that calculates unknown node according to anchor node corrected value error weighted optimization.

Supposing has M anchor node, n unknown node, unknown node N in network _u(u=1,2 ..., n), by formula (1), can obtain anchor node A _icorrected value C _i.

Due to two anchor node A _iand A _jbetween actual range be:

${\mathrm{Dreal}}_{i,j}=\sqrt{{(x_i-x_j)}^2+{(y_i-y_j)}^2}---\left(2\right)$

And anchor node A _iand A _jbetween the estimated distance that obtains according to corrected value be:

Dest _i,j＝C _i×h _ij (3)

Anchor node A so _ithe error of corrected value is:

${\mathrm{\ϵ}}_i=\left(\underset{j\≠i}{\overset{M}{\underset{j=1,}{\mathrm{\Σ}}}}\frac{|{\mathrm{Dreal}}_{i,j}-{\mathrm{Dest}}_{i,j}|}{h_{\mathrm{ij}}}\right)/(M-1)---\left(4\right)$

Suppose unknown node N _uwith anchor node A _ibetween jumping figure be designated as hop _u,i, can give anchor node A so _ithe weights of corrected value are:

$W_i=\frac{\frac{1}{{\mathrm{hop}}_{u,i}\×{\mathrm{\ϵ}}_i}}{\underset{i=1}{\overset{M}{\mathrm{\Σ}}}\frac{1}{{\mathrm{hop}}_{u,i}\×{\mathrm{\ϵ}}_i}}---\left(5\right)$

Like this design to the corrected value weighting of different anchor nodes be based on: when corrected value error less, or anchor node is less from unknown node jumping figure, the weights that this corrected value is given are so just larger, could fair, comprehensively reflect the Average hop distance based on the whole network anchor node corrected value like this.

Then according to each anchor node corrected value and corresponding weight value, just can weighted calculation go out unknown node N _uaverage hop distance:

$C_u=\underset{i=1}{\overset{M}{\mathrm{\Σ}}}{W}_i{C}_i---\left(6\right)$

By normalization weighting, process, the weights of each anchor node are different, and the weights that anchor node less from unknown node jumping figure and that self-correcting value error is less is given are larger, and the weights sum that simultaneously makes each anchor node corrected value is 1.

Second step: preferred anchor node.

First obtain unknown node N _uthe jumping figure mean value of all anchor nodes of distance:

$\stackrel{\‾}{{\mathrm{hop}}_u}=\frac{\underset{i=1}{\overset{M}{\mathrm{\Σ}}}{\mathrm{hop}}_{u,i}}{M}---\left(7\right)$

As certain anchor node A _iwith unknown node N _ujumping figure while being greater than average number of hops,

${\mathrm{hop}}_{u,i}>\stackrel{\‾}{{\mathrm{hop}}_u}---\left(8\right)$

Cast out this anchor node, all the other anchor nodes that are not rejected can participate in location Calculation, and the anchor node number after is preferably designated as m.

The 3rd step: optimum position coordinate figure.

Anchor node after supposing is preferably designated as A _r(r=1,2 ..., m).Unknown node N _uafter the first step is tried to achieve Average hop distance, according to formula (3) and distance A _rjumping figure multiply each other, obtain and anchor node A _rbetween estimated distance Dest _u,r.Because the random combine of every three anchor nodes is total kind, utilize so these anchor node combinations, to estimated distance Dest _u,remploying trilateration is calculated, and can obtain individual unknown node N _uthe estimation elements of a fix, be designated as E _k, wherein

Suppose for calculated candidate elements of a fix E _kthree anchor nodes and the jumping figure of unknown node be respectively hop _r, hop _p, hop _q, (r, p, q=1,2 ..., m), remember the jumping figure of these three anchor nodes and unknown node and for S _k, S _k=hop _r+ hop _p+ hop _q, the weights of giving so candidate's elements of a fix Ek are:

$W_k=\frac{\frac{1}{S_k}}{\underset{k=1}{\overset{C_m^3}{\mathrm{\Σ}}}\frac{1}{S_k}}---\left(9\right)$

After being normalized weighting and processing, the weights of each candidate's elements of a fix are different, give in anchor node combination with unknown node jumping figure and less those candidate's coordinate figures with larger weights, guarantee that weights sum is 1 simultaneously.

Finally calculate the elements of a fix of unknown node.

The corresponding weight value obtaining according to each candidate's elements of a fix value and formula (9) just can calculate the elements of a fix of unknown node:

$N_u=\underset{k=1}{\overset{C_m^3}{\mathrm{\Σ}}}{W}_k{E}_k---\left(10\right)$

By the impact that makes its randomness that can reduce better network topology situation produce node locating the weighting correction of candidate's elements of a fix value, reduce position error.

The flow chart of WSDV-Hop algorithm is as shown in Figure 1:

Concrete steps are as follows:

(1) in network, each anchor node calculates the minimum hop count between itself and each anchor node;

(2) anchor node calculates corrected value and the corrected value error of oneself, and corrected value and control information thereof are broadcasted at the whole network;

(3) unknown node receives the information that anchor node sends, and obtains the minimum hop count apart from anchor node, and according to corrected value error size with apart from the jumping figure of anchor node to each anchor node corrected value normalization weighted optimization, as Average hop distance;

(4) unknown node is calculated the mean value of jumping figure between itself and all anchor nodes;

(5) the jumping figure mean value of trying to achieve in the jumping figure between each anchor node and unknown node and step (4) is compared, if jumping figure value is greater than mean value, cast out this anchor node, otherwise preserve this anchor node as preferred anchor node;

(6) Average hop distance of unknown node anchor node after preferably by distance and jumping figure multiply each other obtain its with preferred anchor node between estimated distance;

(7) by every three random combines of preferred anchor node, and utilize the estimated distance of step (6) gained to calculate candidate's elements of a fix by trilateration;

(8) different anchor node combinations are calculated to candidate's elements of a fix of gained, according to formula (9) and (10), candidate's elements of a fix value of different anchor node combination calculating gained is normalized to weighted optimization, obtain the elements of a fix of unknown node.

Simulation analysis

The present invention uses MATLAB software, choose the part (being designated as WDV-Hop algorithm) of only using separately optimization Average hop distance in WSDV-Hop algorithm idea, in WSDV-Hop, only use separately the part (being designated as SDV-Hop algorithm) of preferred anchor node and optimum position coordinate figure, and traditional DV-Hop algorithm and WSDV-Hop algorithm carry out emulation comparison.Investigate node localization coverage, the performances such as average position error under different anchor node numbers, unknown node number, communication radius, with the quality of measure algorithm.

In emulation, node random placement is in the region of 100m * 100m, and average position error and Signal Coverage Percentage adopt respectively following formula:

$\mathrm{AverageError}=\frac{\underset{i=1}{\overset{N}{\mathrm{\Σ}}}\sqrt{{(x^{\′}-x)}^2+{(y^{\′}-y)}^2}}{N*R}---\left(12\right)$

$\mathrm{Coverage}=\frac{N_{\mathrm{located}}}{N}\×100\%---\left(13\right)$

In formula, R is node communication radius, and N is unknown node sum, the actual coordinate that (x, y) is node, (x ', y ') be the elements of a fix.N _locatedrepresent the successfully unknown node number of location.

1 Signal Coverage Percentage

Unknown node in network is set and adds up to 100, node communication radius is made as 20m, changes anchor node number, from 10, is increased to 40, emulation relatively adopts the node localization coverage of above-mentioned several algorithm gained, and after emulation 100 times, required Signal Coverage Percentage mean value as shown in Figure 2.

As can be seen from Figure 2 these four kinds of algorithm Signal Coverage Percentages all can increase along with the increase of anchor node quantity.WSDV-Hop algorithm can complete location by all unknown node when anchor node quantity reaches 35.And all the other algorithms will be realized location completely, need to continue to increase anchor node number, and when anchor node number less (such as lower than 20), Signal Coverage Percentage is lower.

Two kinds of algorithms of WSDV-Hop and SDV-Hop, when anchor node quantity increases, are realized completely and being located comparatively fast.This is because these two kinds of algorithms adopt preferred anchor node, the situation that the node that can avoid the combination of bad anchor node topology to cause cannot be located.The location coverage effect of WSDV-Hop algorithm is better than again SDV-Hop algorithm, because before preferred anchor node, when unknown node is asked for Average hop distance in WSDV-Hop algorithm, optimize anchor node corrected value, reduced the error of estimated distance between unknown node and anchor node.

The relation of 2 average position errors and anchor node quantity

Simulated conditions is with 3.1, and setting unknown node number is 100, changes anchor node number, and emulation relatively adopts the average position error of four kinds of algorithm gained, and experimental result as shown in Figure 3.

As can be seen from Figure 3, at anchor node number, from the less initialization phase progressively increasing, average position error reduces more obvious, and along with further the increasing of anchor node quantity, average position error slowly reduces.The plots changes of these four kinds of location algorithms is consistent.This is for example, because (be increased to 20 from 10) when anchor node quantity increases, and the range of choice that can be used for the anchor node of location Calculation becomes large, so position error can reduce.For example, and when anchor node is increased to some (more than 20), between unknown node and anchor node, the error change of estimated distance is less, thereby the position error of each unknown node also tends towards stability, and the reduction of the average position error of network also tends towards stability.

Along with the variation of anchor node number, the position error of these three kinds of algorithms of WDV-Hop, SDV-Hop and WSDV-Hop is all lower than DV-Hop algorithm, and wherein the position error of WSDV-Hop algorithm is minimum.Because WDV-Hop algorithm has been considered the corrected value of a plurality of anchor nodes, the Average hop distance value of unknown node is optimized, so average position error decreases than DV-Hop algorithm, and along with the increase of anchor node quantity, the amplitude of reduction is more obvious.SDV-Hop algorithm is owing to considering the distribution of anchor node in network, preferred anchor node, and the positioning result that different anchor nodes combinations are drawn also optimizes, thereby position error is lower compared with WDV-Hop algorithm.WSDV-Hop algorithm is owing to combining the thought of WDV-Hop and SDV-Hop algorithm, and average position error has had again further reduction.And along with the increase of anchor node quantity, this advantage of improving one's methods is also more for obvious.

The relation of 3 average position errors and unknown node quantity

Anchor node quantity is set as 20, and the quantity that changes unknown node is incremented to 400 from 100.The impact of the variation that Fig. 4 has compared 4 kinds of algorithms unknown node quantity in the situation that anchor node quantity is certain on average position error.As seen from Figure 4, anchor node invariable number, unknown node number is more, and average position error is just larger.Wherein the average position error of DV-Hop algorithm is maximum, and the average position error of WDV-Hop and SDV-Hop algorithm is relatively low, and the average position error of WSDV-Hop algorithm is minimum.This is because unknown node is optimized weighting processing to Average hop distance in WSDV-Hop algorithm, reduced the impact of the accumulation of error of euclidean distance between node pair on location Calculation, considered the distribution of anchor node simultaneously, and the elements of a fix have been optimized, therefore average position error is minimum, and positioning precision is the highest.

The relation of 4 average position errors and node communication radius

Set anchor node and unknown node quantity, by changing the communication radius of node, investigate the average position error Performance Ratio of 4 kinds of algorithms.In l-G simulation test, unknown node number is made as 100, and the quantity of anchor node is 20, and the communication radius of node is incremented to 40m from 10m, and simulation result as shown in Figure 5.

As can be seen from Figure 5, when the communication radius of node becomes large, the average position error of 4 kinds of algorithms all can reduce, and wherein the average position error of WSDV-Hop algorithm is minimum, next is SDV-Hop algorithm and WDV-Hop algorithm, and the average position error of DV-Hop algorithm is maximum.

When communication radius increases, the neighbor node number of each node also can increase, and that is to say that the chance of the intercommunication of node increases.Like this unknown node and anchor node between jumping figure also can reduce, the possibility of the jumping section path deviation straight line between them can reduce because of reducing of jumping figure, so the error of estimated distance will decline to some extent between unknown node and anchor node, finally make the average position error of all nodes in network reduce.WSDV-Hop algorithm is owing to having adopted optimization Average hop distance, preferably anchor node and optimum position coordinate, and the impact that the error that the estimated distance of DV-Hop algorithm first two steps gained can be produced cause drops to minimum, so average position error best performance.

In conjunction with Fig. 2, to Fig. 5, can find out, under different condition, above-mentioned 4 kinds of algorithms are arranged at the height of node localization coverage and average position error performance, are WSDV-Hop, SDV-Hop, and WDV-Hop, DV-Hop, can draw consistent conclusion from 4 width analogous diagram.

Claims (4)

1. the WSN localization method based on optimizing Average hop distance and preferred anchor node, is characterized in that, the method comprises three parts:

(1). optimize Average hop distance

Unknown node can receive the corrected value from a plurality of anchor nodes, then to each corrected value, gives different weights, and weights size determines by two factors, and the one, anchor node corrected value mistake extent, another is the jumping figure between anchor node and unknown node; Finally each anchor node corrected value normalization weighting is processed, obtained Average hop distance;

(2). preferred anchor node

Unknown node optimizes apart from oneself nearer a part of anchor node and participates in location Calculation, makes the jumping figure value between these anchor nodes and unknown node be less than the average number of hops between all anchor nodes and this unknown node;

(3). optimum position coordinate figure

Using the coordinate figure of the unknown node calculating by the combination of different anchor nodes candidate's coordinate in network all, by weighted optimization, calculate optimum coordinate figure; Suppose that in network, having n unknown node, the anchor node optimizing is m, for arbitrary unknown node N _u, u=1,2 ... n randomly draws three producible being combined as in anchor node kind, use trilateration to calculate node coordinate, be designated as E _k, can be used as N _ucandidate's elements of a fix; To each candidate's coordinate, between three anchor nodes that the weights size of giving adopts according to it and required unknown node, jumping figure sum decides, and jumping figure sum is less gives larger weights, for jumping figure sum larger give less weights.

2. the WSN localization method based on optimizing Average hop distance and preferred anchor node as claimed in claim 1, is characterized in that, the concrete steps of optimizing Average hop distance are as follows:

(11) in network, each anchor node calculates the minimum hop count between itself and each anchor node;

(12) anchor node calculates corrected value and the corrected value error of oneself, and corrected value and control information thereof are broadcasted at the whole network;

(13) unknown node receives the information that anchor node sends, and obtains the minimum hop count apart from anchor node, and according to corrected value error size with apart from the jumping figure of anchor node to each anchor node corrected value normalization weighted optimization, as Average hop distance;

Supposing has M anchor node, n unknown node, unknown node N in network _u(u=1,2 ..., n), by formula (1), can obtain anchor node A _icorrected value C _i;

$C_i=\frac{\underset{j\≠i}{\overset{m}{\underset{j=1,}{\mathrm{\Σ}}}}\sqrt{{(x_i-x_j)}^2+{(y_i-y_j)}^2}}{\underset{j\≠i}{\overset{m}{\underset{j=1,}{\mathrm{\Σ}}}}{h}_{\mathrm{ij}}}---\left(1\right)$

In formula, (x _i, y _i), (x _j, y _j) be respectively anchor node A _iand A _jcoordinate; h _ijanchor node A _iand A _jbetween minimum hop count;

Due to two anchor node A _iand A _jbetween actual range be:

${\mathrm{Dreal}}_{i,j}=\sqrt{{(x_i-x_j)}^2+{(y_i-y_j)}^2}---\left(2\right)$

And anchor node A _iand A _jbetween the estimated distance that obtains according to corrected value be:

Dest _i,j＝C _i×h _ij (3)

Anchor node A so _ithe error of corrected value is:

${\mathrm{\ϵ}}_i=\left(\underset{j\≠i}{\overset{M}{\underset{j=1,}{\mathrm{\Σ}}}}\frac{|{\mathrm{Dreal}}_{i,j}-{\mathrm{Dest}}_{i,j}|}{h_{\mathrm{ij}}}\right)/(M-1)---\left(4\right)$

Suppose unknown node N _uwith anchor node A _ibetween jumping figure be designated as hop _u,i, can give anchor node A so _ithe weights of corrected value are:

$W_i=\frac{\frac{1}{{\mathrm{hop}}_{u,i}\×{\mathrm{\ϵ}}_i}}{\underset{i=1}{\overset{M}{\mathrm{\Σ}}}\frac{1}{{\mathrm{hop}}_{u,i}\×{\mathrm{\ϵ}}_i}}---\left(5\right)$

Then according to each anchor node corrected value and corresponding weight value, just can weighted calculation go out unknown node N _uaverage hop distance:

$C_u=\underset{i=1}{\overset{M}{\mathrm{\Σ}}}{W}_i{C}_i---\left(6\right)$

By normalization weighting, process, the weights of each anchor node are different, and the weights that anchor node less from unknown node jumping figure and that self-correcting value error is less is given are larger, and the weights sum that simultaneously makes each anchor node corrected value is 1.

3. the WSN localization method based on optimizing Average hop distance and preferred anchor node as claimed in claim 2, is characterized in that, preferably the concrete steps of anchor node are as follows:

First obtain unknown node N _uthe jumping figure mean value of all anchor nodes of distance;

$\stackrel{\‾}{{\mathrm{hop}}_u}=\frac{\underset{i=1}{\overset{M}{\mathrm{\Σ}}}{\mathrm{hop}}_{u,i}}{M}---\left(7\right)$

As certain anchor node A _iwith unknown node N _ujumping figure while being greater than average number of hops,

${\mathrm{hop}}_{u,i}>\stackrel{\‾}{{\mathrm{hop}}_u}---\left(8\right)$

Cast out this anchor node, all the other anchor nodes that are not rejected can participate in location Calculation, and the anchor node number after is preferably designated as m.

4. the WSN localization method based on optimizing Average hop distance and preferred anchor node as claimed in claim 3, is characterized in that, the concrete steps of optimum position coordinate figure are as follows:

Anchor node after supposing is preferably designated as A _r(r=1,2 ..., m); Unknown node N _uafter the first step is tried to achieve Average hop distance, according to formula (3) and distance A _rjumping figure multiply each other, obtain and anchor node A _rbetween estimated distance Dest _u,r; Because the random combine of every three anchor nodes is total kind, utilize so these anchor node combinations, to estimated distance Dest _u,remploying trilateration is calculated, and can obtain individual unknown node N _uthe estimation elements of a fix, be designated as E _k, wherein

Suppose for calculated candidate elements of a fix E _kthree anchor nodes and the jumping figure of unknown node be respectively hop _r, hop _p, hop _q, (r, p, q=1,2 ..., m), remember the jumping figure of these three anchor nodes and unknown node and for S _k, S _k=hop _r+ hop _p+ hop _q, give so candidate's elements of a fix E _kweights be:

$W_k=\frac{\frac{1}{S_k}}{\underset{k=1}{\overset{C_m^3}{\mathrm{\Σ}}}\frac{1}{S_k}}---\left(9\right)$

After being normalized weighting and processing, the weights of each candidate's elements of a fix are different, give in anchor node combination with unknown node jumping figure and less those candidate's coordinate figures with larger weights, guarantee that weights sum is 1 simultaneously;

Finally calculate the elements of a fix of unknown node;

The corresponding weight value obtaining according to each candidate's elements of a fix value and formula (9) just can calculate the elements of a fix of unknown node:

$N_u=\underset{k=1}{\overset{C_m^3}{\mathrm{\Σ}}}{W}_k{E}_k---\left(10\right)$

By the impact that makes its randomness that can reduce better network topology situation produce node locating the weighting correction of candidate's elements of a fix value, reduce position error.