Dynamic target navigation based on multisensor Kalman filtering and neighbor discovery algorithm

Author

Kosugi, Kazuya ; Namerikawa, Toru

Author_Institution

Dept. of Syst. Design Eng., Keio Univ., Yokohama, Japan

fYear

2011

fDate

13-18 Sept. 2011

Firstpage

1392

Lastpage

1397

Abstract

This paper deals with an estimate algorithm which considers optimal control input for dynamic target navigation by using wireless sensor networks and distributed Kalman filter. We propose a novel sensor scheduling algorithm based on a neighbor discovery algorithm for discrete-time linear time-invariant systems. Then we propose an estimate algorithm by sharing predicted estimate values and analyze characteristic of this algorithm. Finally, experimental results show effectiveness of the proposed method in sensor networked feedback systems.

Keywords

Kalman filters; discrete time systems; feedback; linear systems; mobile robots; optimal control; path planning; scheduling; sensor fusion; time-varying systems; wireless sensor networks; discrete-time linear time-invariant systems; distributed Kalman filter; dynamic target navigation; estimate algorithm; multisensor Kalman filtering; neighbor discovery algorithm; optimal control input; predicted estimate values; sensor networked feedback systems; sensor scheduling algorithm; wireless sensor networks; Covariance matrix; Estimation error; Heuristic algorithms; Kalman filters; Noise; Prediction algorithms; Distributed control; Guidance control; Multisensor Kalman Filtering; Sensor Networks; Sensor scheduling;

fLanguage

English

Publisher

ieee

Conference_Titel

SICE Annual Conference (SICE), 2011 Proceedings of

Conference_Location

Tokyo

ISSN

pending

Print_ISBN

978-1-4577-0714-8

Type

conf

Filename

6060552