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|Title:||Distributed localization of a RF target in NLOS environments||Authors:||Xu, Wenjie
Tay, Wee Peng
Razul, Sirajudeen G.
Expectation Maximization Algorithms
DRNTU::Engineering::Electrical and electronic engineering
|Issue Date:||2015||Source:||Xu, W., Quitin, F., Leng, M., Tay, W. P., & Razul, S. G. (2015). Distributed localization of a RF target in NLOS environments. IEEE Journal on Selected Areas in Communications, 33(7), 1317-1330. doi:10.1109/JSAC.2015.2430152||Series/Report no.:||IEEE Journal on Selected Areas in Communications||Abstract:||We propose a novel distributed expectation maximization (EM) method for non-cooperative RF target localization using a wireless sensor network. We consider the scenario where few or no sensors receive line-of-sight signals from the target. In the case of non-line-of-sight signals, the signal path consists of a single reflection between the transmitter and receiver. Each sensor is able to measure the time difference of arrival of the target's signal with respect to a reference sensor, as well as the angle of arrival of the target's signal. We derive a distributed EM algorithm where each node makes use of its local information to compute summary statistics, and then shares these statistics with its neighbors to improve its estimate of the target localization. We show that our distributed algorithm converges, and simulation results suggest that our method achieves an accuracy close to the centralized EM algorithm. We apply the distributed EM algorithm to a set of experimental measurements with a network of four nodes, which confirm that the algorithm is able to localize a RF target in a realistic non-line-of-sight scenario.||URI:||https://hdl.handle.net/10356/104816
|ISSN:||0733-8716||DOI:||10.1109/JSAC.2015.2430152||Rights:||© 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: https://doi.org/10.1109/JSAC.2015.2430152.||Fulltext Permission:||open||Fulltext Availability:||With Fulltext|
|Appears in Collections:||EEE Journal Articles|
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