Node Localization in 3-D by Magnetic-Induction Communications in Wireless Sensor Networks
Abstract
This paper proposes a localization method for wireless sensor nodes that utilize tri-directional coils for near-field magnetic induction (MI) communications. Taking advantage of magnetic field measurements of the tri-directional coils, the proposed localization algorithm uses only two anchor nodes to locate a sensor node in the 3-D space. Assuming each anchor node sequentially transmits the communication signal by three orthogonal Tx coils, and the sensor node receives the signals at the three orthogonal Rx coils simultaneously, the communication distance and the polar angles of transmission are estimated in a local coordinate system of the anchor node. These estimates from the two anchor nodes yield two sets of 8 possible locations of the sensor node. Then a Rotation Matrix (RM) between the transmitter and receiver is derived to narrow down to two possible location vectors with the opposite directions in each anchor node. Finally, we use the maximum likelihood method to estimate the accurate location from the two sets of two location vectors. Simulations results show that the proposed RM-based method can achieve high localization accuracy because the derived closed-form formula of distance estimation achieves good accuracy under large measurement errors.
Recommended Citation
H. Huang and Y. R. Zheng, "Node Localization in 3-D by Magnetic-Induction Communications in Wireless Sensor Networks," Proceedings of OCEANS 2017 MTS/IEEE Anchorage (2017, Anchorage, AK), vol. 78, Institute of Electrical and Electronics Engineers (IEEE), Sep 2017.
Meeting Name
OCEANS '17 MTS/IEEE Anchorage (2017, Sep. 18-21, Anchorage, AK)
Department(s)
Electrical and Computer Engineering
Keywords and Phrases
Anchorages (foundations); Location; Magnetism; Matrix algebra; Maximum likelihood estimation; Closed-form formulae; Communication distance; Communication signals; Local coordinate system; Localization accuracy; Localization algorithm; Maximum likelihood methods; Transmitter and receiver; Sensor nodes
International Standard Book Number (ISBN)
978-1-5090-6429-8
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2017 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.
Publication Date
01 Sep 2017