Title :
Fusion filtering method based on pseudo-measurement model library for multisensor systems with delay measurements
Author :
Ye Haihong ; Wen Chenglin ; Feng Xiaoliang
Author_Institution :
Coll. of Autom., Hangzhou Dianzi Univ., Hangzhou, China
fDate :
May 31 2014-June 2 2014
Abstract :
Information transferring process in sensor network will appear delay, out-of-sequence even dropout. How to make full use of such information is extremely important to improve the state estimation accuracy. In this paper, it presents a new method, which can effectively improve the estimation accuracy. Firstly, a local pseudo-measurement model library is established to deal with the measurement with several steps delay, then sent the local estimates to the fusion center; Secondly, in the fusion center, under the unbiased linear minimum variances weighting fused rule, the fusion Kalman filter based on a matrix weighted fusion algorithm processes the local estimates, thus obtain the global results. Simulations verify the effectiveness of this method.
Keywords :
Kalman filters; delay estimation; filtering theory; sensor fusion; wireless sensor networks; delay measurements; fusion Kalman filter; fusion center; fusion filtering method; information transferring process; linear minimum variances weighting fused rule; matrix weighted fusion algorithm; multisensor systems; pseudo-measurement model library; state estimation accuracy; wireless sensor network; Computational modeling; Current measurement; Delays; Kalman filters; Libraries; Delay measurement; Pseudo-measurement model library; Wireless sensor network; weighted fusion filter;
Conference_Titel :
Control and Decision Conference (2014 CCDC), The 26th Chinese
Conference_Location :
Changsha
Print_ISBN :
978-1-4799-3707-3
DOI :
10.1109/CCDC.2014.6853101