Title :
Networked fusion kalman filtering with multiple uncertainties
Author :
Bo Chen ; Wenan Zhang ; Guoqiang Hu ; Li Yu
Author_Institution :
Zhejiang Univ. of Technol., Hangzhou, China
fDate :
7/1/2015 12:00:00 AM
Abstract :
This paper investigates the problem of fusion filtering for a class of networked multisensor fusion systems with multiple uncertainties, including sensor failures, stochastic parameter uncertainties, random observation delays, and packet dropouts. A novel model is proposed to describe the random observation delays and packet dropouts, and a robust optimal fusion filter for the addressed networked multisensor fusion systems is designed using the innovation analysis method. The dimension of the designed filter is the same as that of the original system, which helps to reduce computation cost compared with the augmentation method. Moreover, robust reduced-dimension observation-fusion Kalman filters are proposed to further reduce the computation burden. Note that the designed fusion filter gain matrices can be computed off-line, as they depend only on the upper bounds of random delays and on the occurrence probabilities of delays and sensor failures. Some sufficient conditions are presented for stability and optimality of the designed fusion filters, and a steady-state fusion filter is also given for the networked multisensor fusion systems. Simulations show the effectiveness of the proposed fusion filters.
Keywords :
Kalman filters; delays; matrix algebra; probability; sensor fusion; stability; augmentation method; innovation analysis method; matrix algebra; multiple uncertainty; networked fusion Kalman filtering; networked multisensor fusion system; occurrence probability; packet dropout; random observation delay; robust optimal fusion filter; robust reduced-dimension observation-fusion Kalman filter; stability; stochastic parameter uncertainty; Delays; Estimation; Kalman filters; Noise; Robustness; Stochastic processes; Uncertainty;
Journal_Title :
Aerospace and Electronic Systems, IEEE Transactions on
DOI :
10.1109/TAES.2015.130803