Global sensor selection for maneuvering target tracking in clutter

DOI

10.2991/jrnal.2016.3.2.13How to use a DOI?

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 Atlantis Press.

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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TY  - JOUR
AU  - Wenling Li
AU  - Yingmin Jia
PY  - 2016
DA  - 2016/09/01
TI  - Global sensor selection for maneuvering target tracking in clutter
JO  - Journal of Robotics, Networking and Artificial Life
SP  - 128
EP  - 131
VL  - 3
IS  - 2
SN  - 2352-6386
UR  - https://doi.org/10.2991/jrnal.2016.3.2.13
DO  - 10.2991/jrnal.2016.3.2.13
ID  - Li2016
ER  -