Wsn Nodes Positioning Methods Based On Least Squares And Support Vector Machine

Wireless Sensor Network(WSN), a new distributional observation network, was considered that is one of the ten new technologies in the 21st century,and it has the very broad application prospect. The nodes localization technology is one of the most supporting technologies in WSN. In order to provide the location information, sensor nodes should achieve self-localization first. It's very significant to achieve highly effective, reliable and accurate node localization for target tracking and route efficiency, and thus that also is the key technology to be solved in the present wireless sensor network. Currently, the popular study of nodes localization algorithm is generally implemented in the two-dimensional environment, which is lag far behind the actual application in three-dimensional environment. Therefore, three-dimensional nodes localization technology becomes the current hot spot and cutting-edge issue for WSN research. The least-square localization algorithm has been a classic two-dimensional nodes localization algorithm before. An extending to three-dimensional localization algorithm will be of great significance and application value. Combined with National Natural Science Foundation research project, this paper aims at the nodes localization technology in WSN. There will be a brief study of the typical least-square two-dimensional nodes localization algorithm, based on which an extending to three-dimensional localization algorithm will be worked out. And then, because the classical least-square algorithm is easily influenced by ranging errors between Nodes, which is a shortcoming, combined with strong learning ability and generalization ability of Support Vector Machines for Regression (SVR), this paper makes a research on LSSVR three-dimensional nodes localization algorithm (LSSVR3DNL). It greatly improved localization accuracy of nodes under three-dimensional environment with large ranging error, which will be significant to the application of WSN in the three-dimensional environment.Specifically, the paper general goes in this way:1. After consulting a great deal of relevant literature and analyzing the research situation and prospects of WSN, several major classifications of WSN localization technology and characteristics are summarized. In addition, depending on these different classifications and characteristics of the localization technology, this paper selects the anchor nodes localization method based on ranging as the direction of this research, laying foundations for later study.2. After analyzing the principles of nodes localization technology in WSN, it has made some discussion about six evaluation indicators of the localization algorithm. Including: localization error, the number of anchor nodes, nodes density, power consumption, fault tolerance. Among that localization error is the primary evaluation indicator of most positioning technologies. Reducing the positioning error to improve the positioning accuracy is an important goal to study a variety of new localization algorithms. This paper proposes a new three-dimensional nodes localization algorithm that based on LSSVR aiming at reduce ranging error caused by the least-square three-dimensional nodes localization algorithm.3. Taking the classical least-square two-dimensional localization algorithm as its research object, this article studies the principles of the least-square two-dimensional nodes localization and mathematical model. What's more, the two-dimensional is extended to three-dimensional proceeding from the mathematical model of least-square two-dimensional nodes localization. With the help of Matlab 7.0 simulation software, the least-square two-dimensional and three-dimensional nodes localization algorithms were programmed. After nodes localization simulations, it verifies the feasibility of extending two-dimensional to three-dimensional for the least-square localization theory.4. A three-dimensional localization algorithm based on LSSVR is proposed for the situation that the classical least-square algorithm is easily influenced by ranging error between nodes and its poor adaptability in different environments. A great deal of researches has been carried out for the optimizing process of parameters of kernel function, mesh width of oriented area, which are contained in LSSVR3DNL. It proposes method of exhaustion which is combined with practical experience, using the Matlab 7.0 simulation the algorithm. Simulation results show that the parameters obtained by this method make the LSSVR3DNL achieve high localization accuracy.5. The wireless sensor network positioning experiment in real environment was made after doing lots of theoretical analysis and simulation analysis, and conducted an experiment for LSSVR3DNL. A localization error rate less than 10% was gotten. This algorithm shows a good practical effects and value.6. This paper provides regression analysis and comparison on these two kinds of nodes localization algorithms in order to demonstrate the superiority of LSSVR3DNL over LS3DNL. The regression analysis indicates that the localization error of LS3DNL is more or less linear with nodes ranging error, while the relationship between the localization error of LSSVR3DNL and nodes ranging error is nonlinear. The comparison shows that the localization errors obtained by the two kinds of localization algorithms under the environment of small nodes ranging error are similar. However, when the nodes ranging error is over 16%, LSSVR3DNL can greatly improve localization accuracy with an average reduction of 25% of localization error, sometimes even to an utmost of 50%, compared with the traditional LS localization algorithm.To sum up, the paper integrates the theoretical study, simulation analysis and experimental validation to make a deep research on nodes self-localization technology in WSN. The new LSSVR3DNL proposed in this paper has strong adaptability to the environment. Nodes localization errors can be greatly reduced under three-dimensional environment with large ranging errors. It provides a new method for WSN nodes localization technology, which is a kind of useful exploration to the development of WSN.