Authors: Ting Yang; Qing Yang; Lihua Cheng
Addresses: School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, China ' Department of Computer Science, Montana State University, Bozeman 59717, MT, USA ' School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, China
Abstract: Ranging technology which estimates the distance between two communicating wireless nodes has been widely used as a necessary component in localisation solutions for wireless sensor networks (WSN). Because of low system cost and less computational complexity, link quality indicator (LQI) based ranging techniques are increasingly applied in Zigbee sensor networks. However, due to the environmental affects and electronic noise generated by hardware, raw LQI data could not be directly aligned with distances. To eliminate errors in LQI data and obtain higher ranging accuracy, we design and evaluate a novel LQI-based ranging technique which includes three essential data processing components: pre-correction, error compensation and mixed regression analysis. The proposed ranging technique is implemented and evaluated on a Zigbee sensor prototype - Tarax. Experiment results show that the average ranging error is less than 1 m, confirming that the proposed technique is able to achieve higher ranging accuracy and suitable for localisation applications in WSN.
Keywords: LQI; link quality indicator; ranging techniques; Zigbee networks; WSNs; wireless sensor networks; distance estimation; localisation; pre-correction; error compensation; mixed regression analysis.
International Journal of Sensor Networks, 2015 Vol.19 No.2, pp.130 - 138
Received: 10 Jul 2013
Accepted: 29 Sep 2013
Published online: 04 Sep 2015 *