Power efficient state estimation using multiple sensors

Author

Leong, Alex S. ; Dey, Subhrakanti ; Evans, Jamie S.

Author_Institution

Dept. of Electr. & Electron. Eng., Univ. of Melbourne, Melbourne, VIC

fYear

2008

fDate

7-10 Dec. 2008

Firstpage

1

Lastpage

6

Abstract

This paper considers state estimation of scalar linear systems using analog amplify and forwarding with multiple sensors, under a multiple access communication scheme. Optimal state estimation can be achieved using a Kalman filter. We show that in many situations, the error covariance decays at a rate of 1/M when the number of sensors M is large. Optimal allocation of transmission powers subject to constraints on the error covariance or sum power is also considered.

Keywords

Kalman filters; linear systems; multi-access systems; sensor fusion; state estimation; wireless sensor networks; Kalman filter; analog amplify-and-forward scheme; error covariance; multiple access communication scheme; multiple sensors; power efficient state estimation; scalar linear system; wireless sensor network; Kalman filters; Linear systems; Military computing; Parameter estimation; Quantization; Sensor fusion; Sensor systems; Sensor systems and applications; State estimation; Wireless sensor networks;

fLanguage

English

Publisher

ieee

Conference_Titel

Information Theory and Its Applications, 2008. ISITA 2008. International Symposium on

Conference_Location

Auckland

Print_ISBN

978-1-4244-2068-1

Electronic_ISBN

978-1-4244-2069-8

Type

conf

DOI

10.1109/ISITA.2008.4895539

Filename

4895539