Title: Navigation algorithm for WSN mobile node on MH particle filtering improvement

Authors: Mingli Ding; Dongmei Yang; Lili Zhuang; Xiaobing Li

Addresses: Department of Automatic Test and Control, Harbin Institute of Technology, No. 92 XIDAZHI Street, Harbin 150001, China ' Department of Automatic Test and Control, Harbin Institute of Technology, No. 92 XIDAZHI Street, Harbin 150001, China ' Department of Automatic Test and Control, Harbin Institute of Technology, No. 92 XIDAZHI Street, Harbin 150001, China ' Department of Automatic Test and Control, Harbin Institute of Technology, No. 92 XIDAZHI Street, Harbin 150001, China

Abstract: A new approach is developed to localise and navigate Wireless Sensor Network (WSN) mobile node with Received Signal Strength Indicator (RSSI) signal, the approach is economical, convenient and reliable in noisy environment. An efficient Metropolis-Hasting (MH) particle filter algorithm was proposed to process the signal for ensures the monotonic increasing relationship between RSSI value and the distance between nodes. The coordinate space quantised with RSSI value was selected to describe the state and position of robots to avoid model error. The navigation system consists of several beacon nodes, and each of them is a distributed measurement and control unites. The outputs from every beacon nodes are collected by the navigation control centre, and the final outputs for mobile robots are calculated based on data fusion. Therefore, the real-time performance of this navigation system is enhanced. Furthermore, this system could adapt dynamic or unknown scenarios due to the coordinate of beacon node is not required before navigation. The simulation and experimental results show the effectiveness of this navigation algorithm.

Keywords: wireless sensor networks; WSNs; particle filters; autonomous navigation; RSSI; mobile nodes; Metropolis-Hasting particle filtering; received signal strength; RSS indicator; robot positioning; mobile robots; robot navigation; navigation control; data fusion; simulation.

DOI: 10.1504/IJSNET.2013.056599

International Journal of Sensor Networks, 2013 Vol.14 No.2, pp.92 - 101

Available online: 28 Sep 2013 *

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