阅读说明：本技术 结合MDS的DV-Hop无线传感器网络节点定位方法 (DV-Hop wireless sensor network node positioning method combining MDS ) 是由 马琳 黄鹏飞 王彬 徐玉滨 董赫 于 2019-11-19 设计创作，主要内容包括：结合MDS的DV-Hop无线传感器网络节点定位方法,本发明涉及无线传感器网络节点定位方法。本发明的目的是为了解决现有DV-Hop方法的定位精度十分有限,无法达到很高的定位精度的问题。过程为：一：信标节点以相同的功率向信标节点相邻节点发送数据包,利用RSS测距技术求得该相邻节点距离该信标节点的距离；二：接收节点同样以信号传播模型求得其与发送节点之间的直线距离；三：得到未知节点到该信标节点的估计距离；四：利用最小二乘法求出该未知节点的初始估计坐标；五：基于得到所有未知节点的初始估计坐标,每次从中选择三个未知节点,得到未知节点的坐标。本发明用于信号处理领域。(The invention discloses a DV-Hop wireless sensor network node positioning method combined with MDS, and relates to a wireless sensor network node positioning method. The invention aims to solve the problems that the positioning accuracy of the conventional DV-Hop method is very limited and cannot reach high positioning accuracy. The process is as follows: firstly, the method comprises the following steps: the beacon node sends data packets to the adjacent nodes of the beacon node with the same power, and the distance between the adjacent nodes and the beacon node is obtained by using an RSS (received signal strength) ranging technology; II, secondly: the receiving node also obtains the linear distance between the receiving node and the sending node by using a signal propagation model; thirdly, the method comprises the following steps: obtaining the estimated distance from the unknown node to the beacon node; fourthly, the method comprises the following steps: solving the initial estimated coordinates of the unknown node by using a least square method; fifthly: and selecting three unknown nodes each time based on the obtained initial estimated coordinates of all the unknown nodes to obtain the coordinates of the unknown nodes. The invention is used in the field of signal processing.)

1. The DV-Hop wireless sensor network node positioning method combining MDS is characterized in that: the method comprises the following specific processes:

the method comprises the following steps: the beacon node sends data packets to the adjacent nodes of the beacon node with the same power, and the distance between the adjacent nodes and the beacon node is obtained by using an RSS (received signal strength) ranging technology;

step two: in the first step, all nodes receiving the data packet forward the data packet to the adjacent nodes thereof by the same transmitting power; the receiving node also obtains the linear distance between the receiving node and the sending node by using a signal propagation model;

step three: repeating the second step until the data packet is sent to all nodes in the network; at this time, each unknown node stores the path and each distance from each beacon node to the node;

calculating the accumulated value of each distance of each path, selecting the path with the minimum accumulated value of each distance as the shortest path, and using the accumulated sum of each distance corresponding to the shortest path as the estimated distance from the unknown node to the beacon node;

step four: repeating the third step until the estimated distance between each unknown node and all beacon nodes is obtained; based on the estimated distance between each unknown node and all beacon nodes, the initial estimated coordinate of the unknown node is calculated by using a least square method;

step five: obtaining initial estimated coordinates of all unknown nodes based on the fourth step, selecting three unknown nodes each time, and if the maximum value of the distances between every two of the three nodes is larger than the communication radius R, not processing the three nodes to obtain the coordinates of the unknown nodes;

and if the maximum value of the distances between every two three nodes is smaller than or equal to the communication radius R, correcting by combining an MDS method to obtain the corrected coordinates of the unknown nodes.

2. The method for DV-Hop wireless sensor network node location in combination with MDS of claim 1, wherein: in the first step, the beacon node sends data packets to the adjacent nodes of the beacon node with the same power, and the distance between the adjacent nodes and the beacon node is obtained by using an RSS (received signal strength) ranging technology; the specific process is as follows:

the wireless sensor network has N nodes in total, wherein the N nodes comprise m beacon nodes and N-m unknown nodes, the coordinates of the beacon nodes are known, and the coordinate positions of the unknown nodes are unknown;

all the beacon nodes transmit data packets to the adjacent nodes of the beacon nodes with the same power;

assuming that the power received by a neighboring node of a certain beacon node from the beacon node is p, the following results are obtained according to a signal propagation model:

wherein n is the dissipation index; d₀Is a reference distance; p is a radical of₀Is the received power at the reference distance; d is the distance of the adjacent node from the beacon node;

finding the distance between the adjacent node and the beacon node as

3. The method for DV-Hop wireless sensor network node location in combination with MDS according to claim 1 or 2, wherein: in the fourth step, based on the estimated distance between each unknown node and all beacon nodes, the initial estimated coordinate of the unknown node is calculated by using a least square method; the specific process is as follows:

for any unknown node x' ═ (x, y)^TForm the following system of equations

Wherein (x)_i,y_i)^TCoordinates of the i-th beacon node, d_iThe estimated distance between the unknown node and the ith beacon node obtained in the third step is N, where N is the number of beacon nodes, and i is 1, 2.., N; x is the abscissa of any unknown node x ', and y is the ordinate of any unknown node x'; t is transposition;

according to the least square method, the following matrixes A and b are obtained

In the formula, the matrix A and the matrix b are intermediate variables;

then the least square method is used to obtain the initial estimated coordinates of the unknown node as

4. The method for DV-Hop wireless sensor network node location in combination with MDS of claim 3, wherein: in the fifth step, initial estimated coordinates of all unknown nodes are obtained based on the fourth step, three unknown nodes are selected from the initial estimated coordinates every time, and if the maximum value of the distances between every two of the three nodes is larger than the communication radius R, no processing is performed to obtain the coordinates of the unknown nodes;

if the maximum value of the distances between every two three nodes is smaller than or equal to the communication radius R, correcting by combining an MDS method to obtain the coordinates of the corrected unknown nodes; the specific process is as follows:

assuming that the initial estimated coordinates of the selected three unknown nodes form a matrix of

Wherein the content of the first and second substances,

firstly, according to the MDS technology, the distance square matrix between three unknown nodes is obtained by using the initial estimated coordinates of the three unknown nodes

Wherein d is_ijRepresenting the estimated distance between the unknown nodes i and j; thereby obtaining a matrix B

Wherein J is an intermediate variable, and is I-ee^TI is a 3-order identity matrix, e ═ 1,1]^T(ii) a B is an intermediate variable;

and then carrying out eigenvalue decomposition on the matrix B:

B＝UΛU^T(10)

wherein U and Λ are intermediate variables;

U＝[u₁u₂u₃](11)

wherein λ is₁、λ₂、λ₃Is the eigenvalue of the matrix B, λ₁≥λ₂≥λ₃；u₁、u₂And u₃Are each lambda₁、λ₂、λ₃Feature vectors corresponding to the 3 feature values;

the relative coordinate matrices of the three unknown nodes are:

wherein the content of the first and second substances,

the corrected result of the initial estimated coordinates of the unknown nodes is as follows:

obtaining the corrected coordinates of the unknown nodes;

where R is a rotation matrix, ρ is a scale factor, and c is a constant.

5. The method for DV-Hop wireless sensor network node location in combination with MDS of claim 4, wherein: the rotation matrix R is

A scale factor of rho

A constant c is

6. The method for DV-Hop wireless sensor network node location in combination with MDS of claim 5, wherein: in the first step, the dissipation index n is 2; reference distance d₀The value is 1 m.

Technical Field

The invention relates to a wireless sensor network node positioning method, and belongs to the field of signal processing.

Background

In recent years, with the development of embedded technology, wireless sensor network technology has come up. The wireless sensor network is small in size, and can read data from the surrounding environment and transmit the data to an application program capable of processing the data through a wireless channel. In a wireless sensor network, it is crucial to acquire the specific location of a wireless sensing node in the network. If the specific location of the node is not known, the collected data loses meaning.

The common positioning algorithm comprises a distance-based method and a non-distance-based method, and DV-Hop is a non-distance-based method for calculating Hop count based on distance vectors. The core idea is to introduce the concept of average hop distance, and to express the distance between the beacon node and the unknown node by the product of hop count and average hop distance, and then to calculate the position of the unknown node by using the least square method or trilateration method. The DV-Hop algorithm has the advantages of low requirement on the hardware of the node and simple realization. However, the DV-Hop method has very limited positioning accuracy and cannot achieve very high positioning accuracy.

Disclosure of Invention

The invention aims to solve the problems that the existing DV-Hop method is very limited in positioning accuracy and cannot achieve high positioning accuracy, and provides a DV-Hop wireless sensor network node positioning method combining MDS.

The DV-Hop wireless sensor network node positioning method combining MDS comprises the following specific processes:

the method comprises the following steps: the beacon node sends data packets to the adjacent nodes of the beacon node with the same power, and the distance between the adjacent nodes and the beacon node is obtained by using an RSS (received signal strength) ranging technology;

step two: in the first step, all nodes receiving the data packet forward the data packet to the adjacent nodes thereof by the same transmitting power; the receiving node also obtains the linear distance between the receiving node and the sending node by using a signal propagation model;

step three: repeating the second step until the data packet is sent to all nodes in the network; at this time, each unknown node stores the path and each distance from each beacon node to the node;

calculating the accumulated value of each distance of each path, selecting the path with the minimum accumulated value of each distance as the shortest path, and using the accumulated sum of each distance corresponding to the shortest path as the estimated distance from the unknown node to the beacon node;

step four: repeating the third step until the estimated distance between each unknown node and all beacon nodes is obtained; based on the estimated distance between each unknown node and all beacon nodes, the initial estimated coordinate of the unknown node is calculated by using a least square method;

step five: obtaining initial estimated coordinates of all unknown nodes based on the fourth step, selecting three unknown nodes each time, and if the maximum value of the distances between every two of the three nodes is larger than the communication radius R, not processing the three nodes to obtain the coordinates of the unknown nodes;

and if the maximum value of the distances between every two three nodes is smaller than or equal to the communication radius R, correcting by combining an MDS method to obtain the corrected coordinates of the unknown nodes.

The invention has the beneficial effects that:

the invention relates to a method for realizing the positioning of a wireless sensor network node by utilizing a wireless sensor network, Signal measurement, Signal processing technology and the like, and provides a DV-Hop wireless sensor network node positioning method based on multi-dimensional scale transformation (MDS) assistance, wherein the method measures the distance between adjacent nodes by receiving the RSS (Received Signal Strength) distance measurement technology and applies the MDS algorithm to obtain a more accurate positioning result; firstly, obtaining an accumulated distance between an unknown node and a beacon node by using a signal propagation model; then, calculating a primary positioning result by using a least square method; and finally, correcting the initial positioning result by using an MDS method, wherein the positioning precision is high and is not limited. The experimental result shows that the probability of the positioning error being less than 2m is 65%, and the probability of being less than 5m is about 90%. Compared with the traditional DV-Hop method, the method provided by the invention can greatly improve the positioning accuracy, can be better applied to wireless sensor network positioning, and solves the problems that the positioning accuracy of the existing DV-Hop method is very limited and cannot reach very high positioning accuracy.

Drawings

FIG. 1 is a distribution diagram of beacon nodes and unknown nodes according to the present invention, where the triangles represent beacon nodes and the circles represent unknown nodes;

FIG. 2 is a graph of shortest paths from an unknown node to a beacon node, where A is the beacon node, U is the unknown node, and there are two paths from A to U, which are respectively represented by solid lines and dashed lines; A. nodes between the U can be beacon nodes or unknown nodes, and only represent intermediate nodes;

FIG. 3 is a schematic diagram of an unknown node before and after coordinate correction, a dot represents an initial estimated coordinate of the unknown node, a square represents a relative coordinate of the unknown node, and a triangle represents a coordinate after correction of the unknown node;

FIG. 4 is a diagram of a beacon node and an unknown node distribution in a simulation experiment, where a triangle represents a beacon node and a circle represents an unknown node;

fig. 5 is a graph of probability of cumulative distribution of positioning errors for a simulation experiment.

Detailed Description