The multiple-model linearization based on the unscented transform and its application in nodes’ locations in wireless sensor networks

Author

Wang, Jianwen ; Li, Hongjun ; Li, Xun ; Ma, Hongxu ; Huang, Qianwei

Author_Institution

Dept. of Autom. Control Nat., Univ. of Defense Technol. Changsha, Changsha

fYear

2007

fDate

15-18 Dec. 2007

Firstpage

1099

Lastpage

1103

Abstract

The unscented transform and the multiple-model method are employed to linearize nonlinear systems, and a new linearization method is designed called as the multiple-model linearization method based on the unscented transform (UT-MMLM). Because the UT-MMLM describes a nonlinear system by a linear systems´ set, it can further approach the original system. Based on this linear systems´ set, the multiple-model extended Kalman filter based on the unscented transform(UT- MMEKF) is designed. At last, the findings in this paper are used to locate nodes´ positions in wireless sensor networks(WSN).

Keywords

Kalman filters; linearisation techniques; nonlinear control systems; wireless sensor networks; extended Kalman filter; multiple-model linearization; nonlinear systems; unscented transform; wireless sensor networks; Algorithm design and analysis; Control systems; Kalman filters; Linear systems; Nonlinear control systems; Nonlinear filters; Nonlinear systems; Polynomials; Speech synthesis; Wireless sensor networks; Location; Multiple-Model; Nonlinear System; Wireless Sensor Network;

fLanguage

English

Publisher

ieee

Conference_Titel

Robotics and Biomimetics, 2007. ROBIO 2007. IEEE International Conference on

Conference_Location

Sanya

Print_ISBN

978-1-4244-1761-2

Electronic_ISBN

978-1-4244-1758-2

Type

conf

DOI

10.1109/ROBIO.2007.4522317

Filename

4522317