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Localization Algorithm for Mobile Nodes in Wireless Sensor Networks Based on Discrete-Time H∞ Filtering and Dynamic Node Model

Xiaoming Wu1, Hua Wu1, Yang Liu1,2,3 , Guangyuan Zhang1, and Jianping Xing2
1.School of Information Science & Electric Engineering, Shandong Jiaotong University, Jinan 250357, China
2.School of Information Science & Engineering, Shandong University, Jinan 250100, China
3.School of Electronic & Information Engineering, Beihang University, Beijing 100191, China
Abstract—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.

Index Terms—WSN, mobile node localization, H∞ filtering, simple kinematic model

Cite: Xiaoming Wu, Hua Wu, Yang Liu, Guangyuan Zhang, and Jianping Xing, "Localization Algorithm for Mobile Nodes in Wireless Sensor Networks Based on Discrete-Time H∞ Filtering and Dynamic Node Model," Journal of Communications, vol. 10, no. 6, pp. 415-422, 2015. Doi: 10.12720/jcm.10.6.415-422
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