Distributed Localization Algorithm for Wireless Sensor Network Based on Multidimensional Scaling and the Shortest Path Distance Correction

• Published in: Transactions of Tianjin University Vol. 15; no. 4; pp. 237 - 244
• Main Author: 丁英强 杜留锋 杨挺 孙雨耕
• Format: Journal Article
• Language: English
• Published: Heidelberg Tianjin University 01.08.2009; School of Electrical Engineering and Automation, Tianjin University, Tianjin 300072, China%School of Mechatronics Engineering, Henan Institute of Science and Technology, Xinxiang 453003, China
• Subjects: Engineering; Humanities and Social Sciences; MDS; Mechanical Engineering; multidisciplinary; Science; 位置传感器; 定位算法; 无线传感器网络; 网络传感器; 自适应搜索算法; 距离估计; 距离和; local positioning region; wireless sensor network (WSN); relative coordinates; multidimensional scaling; relative coordi-nates
• ISSN: 1006-4982; 1995-8196
• DOI: 10.1007/s12209-009-0042-1

Sensor localization is crucial for the configuration and applications of wireless sensor network （WSN）. A novel distributed localization algorithm, MDS-DC was proposed for wireless sensor network based on multidi- mensional scaling （MDS） and the shortest path distance correction. In MDS-DC, several local positioning regions with reasonable distribution were firstly constructed by an adaptive search algorithm, which ensures the mergence between the local relative maps of the adjacent local position regions and can reduce the number of common nodes in the network. Then, based on the relationships between the estimated distances and actual distances of anchors,the distance estimation vectors of sensors around anchors were corrected in each local positioning region. During the computations of the local relative coordinates, an iterative process, which is the combination of classical MDS algorithm and SMACOF algorithm, was applied. Finally, the global relative positions or absolute positions of sensors were obtained through merging the relative maps of all local positioning regions. Simulation results show that MDS-DC has better performances in positioning precision, energy efficiency and robustness to range error, which can meet the requirements of applications for sensor localization in WSN.