Authors
Wenling Li, Yingmin Jia
Corresponding Author
Wenling Li
Available Online 1 September 2016.
DOI
https://doi.org/10.2991/jrnal.2016.3.2.13
Keywords
Sensor selection, Jump Markov system, Extended Kalman filter, Maneuvering target tracking, Clutter
Abstract
This paper studies the problem of sensor selection for maneuvering target tracking in the cluttered environment. By modeling the target dynamics as jump Markov linear systems, a decentralized tracking algorithm is developed by applying the extended Kalman filter and the probabilistic data association technique. A cost function that minimizes the expected filtered mean square position error is utilized and a sensor selection scheme is proposed. A numerical example is provided to illustrate the effectiveness of the proposed approach.

Copyright
© 2013, the Authors. Published by ALife Robotics Corp. Ltd.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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