CN102680995A - Mobile anchor node based weighted centroid locating method for wireless sensor network node - Google Patents

Abstract

The invention discloses a mobile anchor node based weighted centroid locating method for a wireless sensor network node and belongs to the field of application of the wireless sensor network and the random mobile technology and the wireless range finding technology. Since a mobile anchor node is utilized to substitute for a traditional anchor node, usage cost is reduced, and coverage rate for unknown nodes is increased. Locations of the unknown nodes can be obtained by scheduling moving path of the anchor node and by the aid of the weighted centroid algorithm. The mobile anchor node based weighted centroid locating method for the wireless sensor network node is low in cost, simple in algorithm, high in coverage rate of unknown nodes, accurate in locating, and applicable to practical use.

Description

A kind of based on the wireless sensor network node weighted mass center localization method that moves anchor node

Technical field

The present invention relates to a kind of sensor network node locating method, more relate to mobile technology and wireless distance finding technology at random based on mobile anchor node.

Background technology

Wireless sensor network is formed by being deployed in cheap microsensor nodes a large amount of in the monitored area; Form the ad hoc network system of a multi-hop through communication; The information of perceptive object in cooperation ground perception, collection and the processing network's coverage area; And sending to the observer, it is the prerequisite that realizes above-mentioned target that sensor network nodes is accurately located.Ordinary node is because computing power simple in structure is poor, and finite energy is so can not fully independently accomplish the location.By whether needing anchor node to participate in the assist location division; Existing location algorithm is divided into based on the anchor node location algorithm and need not the anchor node location algorithm; And the anchor node cost that adopts at present is high; Can not use in a large number, cause the unknown node coverage rate lowly, cause bigger positioning error thereby make node in position fixing process, can't obtain enough information.

Summary of the invention

It is high that the present invention mainly solves traditional anchor node cost, and coverage rate is low, existing location algorithm complicacy and the big problem of positioning error.

The technical scheme that the present invention addresses the above problem employing is: adopt mobile anchor node to produce virtual anchor node and replace traditional anchor node; Solved the high problem of a large amount of anchor node costs of using; And by Gauss's Markov mobility model; Adopt control technology to make anchor node move according to the mobile route after optimizing, anchor node is through sending the unknown node around the present position signalisation, and unknown node records the distance between self and the virtual anchor node through the RSSI technology simultaneously.Node to be measured increases the weight near the virtual anchor node of self in accomplishing the self poisoning process, realize self poisoning through the weighted mass center algorithm.Thereby it is low to obtain a kind of cost, and coverage rate is high, and algorithm is simple, the node positioning method that error is little.

Description of drawings

Fig. 1 is that the anchor node mobile route is optimized process flow diagram in the inventive method;

Fig. 2 is that stop place and system generate error synoptic diagram between the point of destination in the actual moving process of anchor node; β representes the actual angle that departs from model generation direction that moves; D representes that actual stop place departs from the distance of point of destination;

Fig. 3 is the covering synoptic diagram of virtual anchor node to unknown node; Wherein A is an anchor node; N is a unknown node; R is the communication radius of anchor node; N is in the communication range of A, and A can accomplish the covering to N;

Fig. 4 is the motion track of anchor node in the position fixing process, shows among the figure that anchor node can cover unknown node fully;

Embodiment

In conjunction with Fig. 1～Fig. 4 this embodiment is described, this embodiment is a kind of based on the wireless sensor network node weighted mass center localization method that moves anchor node, and concrete steps are following:

Step 1: accomplish sensor network nodes and dispense, node is in sleep state;

Step 2: the anchor node that will have the GPS positioning equipment is installed on the controlled mobile device, gets into zone to be measured;

Step 3: mobile device obtains a point of destination according to Gauss's Markov mobility model; Before this point of destination moves; Distance between the historical coordinate position of prejudging this point of destination and storing before, mobile device only think that this point of destination is effective in this distance during greater than the value set, and mobile to this point; Otherwise regenerate a point of destination, effective until point of destination;

Next step translational speed of mobile device wherein, angle of turn and next point of destination are obtained by Gauss's Markov mobility model, like formula (1), formula (2):

$\left\{\begin{array}{c}{v}_k={\mathrm{\αv}}_{k-1}+{(1-\mathrm{\α})v}_{\mathrm{mean}}+{\mathrm{\γ}}_v\sqrt{1-{\mathrm{\α}}^2}\\ d_k={\mathrm{\αd}}_{k-1}+{(1-\mathrm{\α})d}_{\mathrm{mean}}+{\mathrm{\γ}}_d\sqrt{1-{\mathrm{\α}}^2}\end{array}\right.---\left(1\right)$

$\left\{\begin{array}{c}{x}_k=x_{k-1}+v_{k-1}\×\cos \left(d_{k-1}\right)\×t\\ y_k=y_{k-1}+v_{k-1}\×\sin \left(d_{k-1}\right)\×t\end{array}\right.---\left(2\right)$

Gauss's Markov mobility model parameter: v _k, d _kSpeed and direction when k the time interval, t began in the moving process, d _kWith direct north be 90 ° for referencial use.v _Mean, d _MeanBeing initial velocity and initial motion direction, is the constant of initial setting.γ _v, γ _dBe the stochastic variable that satisfies Gaussian distribution, α is that the degree of randomness of anchor node is regulated parameter.

After generating one group of parameter, can be through the determining program that pre-sets, whether judgement should be organized data effective, judges flow process (shown in Figure 1) as follows:

1. anchor node moves to a point of destination, to around broadcast position information;

2. generate next target coordinate;

3. judge whether target coordinate is effective: whether the distance of coordinates computed point and historical position point greater than setting value, if greater than then should be effectively, anchor node be put mobile to this;

4. otherwise regenerate target coordinate, and repeat said process, until satisfying condition.

Step 4: move anchor node and in zone to be measured, move; Whenever move a setting cycle and just stop, obtain instant coordinate position through GPS, and with information storage in internal memory; Simultaneously with certain communication radius to around broadcast message; Like Fig. 2, the anchor node communication range unknown node all can obtain this information, broadcasting is accomplished continued and is moved forward;

Anchor node generates the angle of turn of next cycle through mobility model; Translational speed and mobile point of destination move by above-mentioned three groups of parameters, because the mobile device angle of turn; The existing of translational speed error (like Fig. 3); There is error in the position that causes mobile device to stop with the actual position that generates, and abandons the coordinate points that model generates this moment, preserves and send the value that GPS measures.

Step 5: unknown node is waken up the back and is received the coordinate information that anchor node sends, and simultaneously through the distance of RSSI technology acquisition with anchor node, and stores the information that obtains;

The wireless distance finding model that adopts among the present invention is logarithm one a normal distribution model, representes like formula (3):

PL(d)＝PL ₀+10ηlg(d/d ₀)+X _σ (3)

Wherein, PL ₀Be illustrated in reference distance d ₀The loss of signal at place, the typical case gets d ₀=1m; PL (d) representes the path loss of receiving end, the distance between d expression signal transmitting terminal and the signal receiving end; η is the radio-frequency channel damped expoential, and η is confirmed by numerous on site measured, generally gets between 2～4; X _σFor average is 0 Gaussian number, its variance scope is generally between 4～10.

Unknown node obtains the coordinate information of anchor node in the tradition centroid algorithm location algorithm, and the polygonal barycenter of forming with these coordinate informations is as self-position, and the information that unknown node obtains is located accurate more more for a long time.Use virtual anchor node among the present invention, can obtain unlimited many coordinate informations in theory, can obtain the quantity of information in the practical application based on field requirement setup parameter control unknown node.The present invention also considers to increase the weight near the anchor node of unknown node, introduces weighting algorithm.

Step 6: behind the certain hour, mobile device is accomplished the covering task, like Fig. 4.Unknown node has obtained enough information, accomplishes self poisoning through the weighted mass center algorithm;

During the unknown node location, the coordinate information that a certain unknown node obtains is (x ₁, y ₁), (x ₂, y ₂) ... (x _n, y _n), respective distances is s ₁, s ₂S _nThen this unknown node obtain self-position (x, y) represent by formula (4):

$\left\{\begin{array}{c}x=\frac{\frac{x_1}{s_1}+\frac{x_2}{s_2}+\·\·\·+\frac{x_n}{s_n}}{\frac{1}{s_1}+\frac{1}{s_2}+\·\·\·+\frac{1}{s_n}}\\ y=\frac{\frac{y_1}{s_1}+\frac{y_2}{s_2}+\·\·\·\frac{y_n}{s_n}}{\frac{1}{s_1}+\frac{1}{s_2}+\·\·\·+\frac{1}{s_n}}\end{array}\right.---\left(4\right)$

Claims (4)

1. the wireless sensor network node weighted mass center localization method based on mobile anchor node is characterized in that its step is following

Step 1: accomplish sensor network nodes and dispense, node is in sleep state;

Step 2: the anchor node that will have the GPS positioning equipment is installed on the controlled mobile device, gets into zone to be measured;

Step 3: mobile device is before next point of destination moves; Distance between the historical coordinate position of prejudging this point of destination and storing before; Only this distance during greater than the value set mobile device think that this point of destination is effective; And begin to move, otherwise regenerate point of destination, effective until point of destination;

Step 4: move anchor node and in zone to be measured, move; Whenever move a setting cycle and just stop, obtain instant coordinate position through GPS, and with information storage in self EMS memory; Simultaneously with certain communication radius to around broadcast message, broadcasting is accomplished continued and is moved forward;

Anchor node generates the angle of turn of next cycle through mobility model; Translational speed and mobile point of destination move by above-mentioned three groups of parameters, because the mobile device angle of turn; The existence of translational speed error; There is error in the position that causes self stopping with the actual position that generates, and abandons the coordinate points that model generates this moment, preserves and send the value that GPS measures.

Step 5: unknown node is received the coordinate information that anchor node sends after being waken up, simultaneously through the distance between acquisition of RSSI technology and the anchor node, and stores the information that obtains;

Step 6: behind the certain hour, mobile device is accomplished the assist location task, and unknown node is accomplished self poisoning through the weighted mass center algorithm.

2. according to claim 1 a kind of based on the wireless sensor network node weighted mass center localization method that moves anchor node; It is characterized in that in the step 3 whether anchor node was prejudged this point of destination before next point of destination moves effective; Criterion is: whether the distance between the history point that this point of destination and anchor node once stopped is greater than predefined value; If greater than this would be an available point, otherwise regenerate, until effectively.

3. according to claim 1 and 2 a kind of based on the wireless sensor network node weighted mass center localization method that moves anchor node; It is characterized in that in the step 4; Since during anchor node moves, the existence of angle of turn and translational speed error, and causing the final position that stops of anchor node might not be the target coordinate position that generates in advance; The point of destination information that this moment, anchor node generated before giving up is to the instantaneous value that unknown node is broadcasted and storage obtains through GPS.

4. according to claim 1 a kind of based on the wireless sensor network node weighted mass center localization method that moves anchor node; It is characterized in that step 6; Unknown node has increased the weights of distance when calculating self-position, the weights of the virtual anchor node that distance is near more are heavy more.

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