标题:Localization algorithm for mobile nodes in wireless sensor networks based on discrete-time h filtering and dynamic node model
作者:Wu, Xiaoming ;Wu, Hua ;Liu, Yang ;Zhang, Guangyuan ;Xing, Jianping
作者机构:[Wu, Xiaoming ;Wu, Hua ;Liu, Yang ;Zhang, Guangyuan ] School of Information Science and Electric Engineering, Shandong Jiaotong University, Jinan; 250 更多
通讯作者:Liu, Yang
来源:Journal of Communications
出版年:2015
卷:10
期:6
页码:415-422
DOI:10.12720/jcm.10.6.415-422
关键词:H filtering; Mobile node localization; Simple kinematic model; WSN
摘要:Precise localization of mobile nodes in uncertain conditions is a fundamental and crucial topic in wireless sensor networks. In this paper a discrete-time H∞ filtering and dynamic node model based algorithm is proposed. Accurate and complicate network models are not required and no assumptions are needed for the external noise characteristics but only have to be seen as energy-limited. State and measurement equation of unknown node are built with basic kinematic property and sensor node measurement method, including the impact of environment random uncertainties and node connection failure. The position of the mobile node is estimated by the filter using an integration of position information from other assisting nodes. Complying to Linear Matrix Inequality (LMI) criterion, a theorem of H filter designed for stochastic uncertain network is given. From the dynamics of the node, the solution existence of the proposed filter is obtained, and a low computational complexity method to get the optimum solution from the filter is provided in a simple motion model. The simulation results show that this method not only can achieve highly reliability but also the better localization accuracy under stochastic uncertainty wireless sensor network (WSN) conditions compared with the classic mobile MCL and MCB mobile schemes. © 2015 Journal of Communications.
收录类别:EI;SCOPUS
Scopus被引频次:1
资源类型:期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-84933510019&doi=10.12720%2fjcm.10.6.415-422&partnerID=40&md5=a9a494e158a55b487c1ccc55e2ae222f
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