@article{a7a3967f95c346bab638008acece5654,
title = "Joint sensor and relay power control in tracking Gaussian mixture targets by wireless sensor networks",
abstract = "This paper considers a wireless sensor network for locating a static target or tracking a dynamic target, which is characterized a priori by a Gaussian mixture distribution. An amplify- and-forward relay node acts as a wireless bridge in relaying the sensor{\textquoteright}s independent observations of the target to a fusion center (FC). Joint power allocation is considered for the sensors and relay to optimize a Bayesian filter, which is deployed at the FC for a global estimate of the target. The mean squared error of the Bayesian filter is already computationally intractable for fixed sensor and relay transmitter power, so power allocation to minimize its mean squared error is a very challenging problem. In this paper, the problem is addressed by an iterative procedure of very low computational complexity. Simulations are provided to support the efficiency of our proposed power allocation.",
keywords = "Bayesian filter, Data fusion, Fast computation, Gaussian mixture target, Relaying communication, Target localization, Target tracking, Wireless sensor networks",
author = "Bengua, {Johann A.} and Tuan, {Hoang Duong} and Duong, {Trung Q.} and Poor, {H. Vincent}",
note = "Funding Information: Manuscript received December 28, 2016; revised June 1, 2017 and August 18, 2017; accepted August 26, 2017. Date of publication September 4, 2017; date of current version December 11, 2017. The associate editor coordinating the review of this manuscript and approving it for publication was Prof. Kostas D. Berberidis. This work was supported in part by the Australian Research Council{\textquoteright}s Discovery Projects under Project DP130104617, in part by a U.K. Royal Academy of Engineering Research Fellowship under Grant RF1415/14/22, in part by the U.K. Engineering and Physical Sciences Research Council under Grant EP/P019374/1, and in part by the U.S. National Science Foundation under Grants CNS-145679 and CNS-1702808. (Corresponding author: Trung Q. Duong.) J. A. Bengua was with the Faculty of Engineering and Information Technology, University of Technology Sydney, Ultimo, NSW 2007, Australia. He is now with Teradata Australia and New Zealand (e-mail: jbengua@gmail.com). Funding Information: This work was supported in part by the Australian Research Council?s Discovery Projects under Project DP130104617, in part by a U.K. Royal Academy of Engineering Research Fellowship under Grant RF1415/14/22, in part by the U.K. Engineering and Physical Sciences Research Council under Grant EP/P019374/1, and in part by the U.S. National Science Foundation under Grants CNS-145679 and CNS-1702808. Publisher Copyright: {\textcopyright} 2017 IEEE.",
year = "2018",
month = jan,
day = "15",
doi = "10.1109/TSP.2017.2749211",
language = "English (US)",
volume = "66",
pages = "492--506",
journal = "IEEE Transactions on Signal Processing",
issn = "1053-587X",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
number = "2",
}