@inproceedings{0df73349338948e1afb6318ee02579db,
title = "Distributed joint estimation and identification for sensor networks with unknown inputs",
abstract = "In this paper we consider the problem of distributed, joint, state estimation and identification for a class of stochastic systems with unknown inputs (UI). A distributed Expectation-Maximization (EM) algorithm is presented to estimate the local state at each sensor node by using the local observations in the E-step, and three different consensus schemes are proposed to diffuse the local state estimate to each sensor's neighbours and to derive the global state estimate at each node. In the M-step, each sensor identifies the local unknown inputs by using the global state estimate. A numerical example of target tracking in distributed sensor network is given to verify the three different distributed EM algorithms compared with the centralized EM based measurement-level and track-level fusion.",
author = "Hua Lan and Bishop, {Adrian N.} and Quan Pan",
year = "2014",
doi = "10.1109/ISSNIP.2014.6827600",
language = "English",
isbn = "9781479928439",
series = "IEEE ISSNIP 2014 - 2014 IEEE 9th International Conference on Intelligent Sensors, Sensor Networks and Information Processing, Conference Proceedings",
publisher = "IEEE Computer Society",
booktitle = "IEEE ISSNIP 2014 - 2014 IEEE 9th International Conference on Intelligent Sensors, Sensor Networks and Information Processing, Conference Proceedings",
address = "United States",
note = "9th IEEE International Conference on Intelligent Sensors, Sensor Networks and Information Processing, IEEE ISSNIP 2014 ; Conference date: 21-04-2014 Through 24-04-2014",
}