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Research on Localization Algorithms in Wireless Sensor Network Based on Multidimensional Scaling
Author: MaZuoAn
Tutor: XuYouYun
School: Shanghai Jiaotong University
Course: Electronics and Communication Engineering
Keywords: Wireless sensor networks Multidimensional Scaling Monte Carlo localization algorithm Power Control Clustering Locate
CLC: TN929.5
Type: Master's thesis
Year: 2012
Downloads: 97
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Abstract
Wireless sensor network is a combination of new network technologies, wireless sensors, wireless communication, and embedded systems technology has aroused a great deal of attention since been proposed after. Wireless sensor network is widely used in environmental monitoring, disaster prediction and search and rescue, the military field, the field of medical and health, smart home, smart factory, longrange unmanned surveillance are indispensable. Monitored events after an important issue of concern is the location of the incident, the position information is the most important part in the data collection of sensor nodes, there is no monitoring of the position information is usually meaningless. So, how to become a research focus sensor network node positioning. This paper studies the various positioning algorithms in wireless sensor networks, and focuses on the positioning technology based on multidimensional scaling analysis. On this basis, for the inadequacies of the multidimensional scaling analysis of positioning technology, the improved algorithm. This paper first introduces the knowledge of the wireless sensor networks, the existing wireless sensor network positioning algorithm classification and brief several typical positioning algorithm. Although a wide range of existing positioning algorithm, but according to the need ranging, the need for anchor nodes, absolute positioning or relative positioning of reasonable classification. Which does not require ranging algorithm as it applies to lowpower, lowcost areas of concern. Based on multidimensional scaling analysis (Multidimensional Scaling, MDS) technology positioning algorithm is a localization algorithm can be applied to nonranging environment. Better positioning accuracy of the localization algorithm based on multidimensional scaling analysis usually has fewer anchor nodes as well as nonranging conditions. This article indepth study of the localization algorithm based on multidimensional scaling analysis, the MDSMAP algorithm requires centralized processing nodes in the network are more evenly distributed inadequacies proposed an improved distributed localization algorithm MDSMAP ( Advanced MDSMAP, AMDSMAP). The AMDSMAP localization algorithm using the node the node sends signal power node to determine the connection relation originally hop node redrawing semijump and hop, and even finer hierarchical control. The results of this division is the spacing between the nodes closer to the true distance; improved localization algorithm MDSMAP, a single unknown node allpass network anchor node itself, rather than the entire network using MDS positioning algorithm the distributed positioning AMDSMAP positioning algorithm compared to MDSMAP localization algorithm not only improved positioning accuracy and positioning algorithm is a distributed, making it more suitable for largescale wireless transmission sense of the network. The simulation shows that the the AMDSMAP algorithm positioning accuracy of at least 10% higher than the MDSMAP algorithm. Subsequently, this paper the AMDSMAP as well as the localization algorithm MDSMAP environment uneven distribution of nodes (such as Ctype network) positioning accuracy is poor, is proposed based on the anchor node clustering MDSMAP localization algorithm, based on anchor node how clustering MDSMAP algorithm in the positioning accuracy of the Ctype network is slightly better than the MDSMAP (P) algorithm, but the performance of the algorithm by the anchor node distribution effect is large, so this article in this study based on reasonable to place the anchor node algorithm for high positioning accuracy. Through the anchor node is placed in a larger area of ??the unknown node density, more uniform distribution of the anchor node, each anchor node cluster head positioning unknown node within the cluster, and then the coordinates fusion between different clusters , and finally through the anchor node transformed relative coordinates to absolute coordinates, more than 10% of the improvement of the positioning accuracy and can maintain a stable performance after the improved algorithm. Again, this article also indepth learning Monte Carlo Localization (MCL) positioning algorithm based on a combination of the the MCL and Distributed MDSMAP localization algorithm advantage of the adaptive mobile network positioning algorithm (MCLMDS) mobile networks, MCL Distributed MDSMAP positioning algorithm FirstMDS positioning algorithm to locate the node, then positioning results using the MCL algorithm filtration principle of verification, if validation by using the results of this positioning, otherwise, the positioning of the MCL algorithm results. MCLMDS algorithm combines two advantages of the algorithm, and in a variety of network connectivity, the anchor node ratio and node movement speed positioning accuracy of the MCL algorithm with MDS algorithm public minimum.

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