On optimal state estimation with multiple packet dropouts

Author

Zhansheng Duan ; Li, X. Rong

Author_Institution

Dept. of Electr. Eng., Univ. of New Orleans, New Orleans, LA, USA

fYear

2010

fDate

26-29 July 2010

Firstpage

1

Lastpage

8

Abstract

Due to unreliable communication between local sensors and the processing center, packet dropouts may happen during transmission. Two existing methods for linear minimum mean-squared error (LMMSE) estimation with multiple packet dropouts were obtained completely or partially based on a stochastic parameter system constructed by augmenting the original state and measurement. They have a high computational load, unclear measurement residual characterization and tough requirements on initialization. To overcome these, an alternative form of LMMSE estimation with multiple packet dropouts is derived. Under a Gaussian assumption, the minimum mean-squared error (MMSE) estimation with multiple packet dropouts is also derived. Numerical examples are provided to compare performance of the proposed estimators.

Keywords

Gaussian processes; mean square error methods; state estimation; wireless sensor networks; Gaussian assumption; linear minimum mean-squared error estimation; optimal state estimation; packet dropouts; sensor communication; stochastic parameter system; Current measurement; Hafnium; Kalman filters; Noise measurement; Sensors; State estimation; LMMSE; MMSE; State estimation; hard decision; packet dropout;

fLanguage

English

Publisher

ieee

Conference_Titel

Information Fusion (FUSION), 2010 13th Conference on

Conference_Location

Edinburgh

Print_ISBN

978-0-9824438-1-1

Type

conf

DOI

10.1109/ICIF.2010.5711872

Filename

5711872