Title :
Distributed fusion filter for stochastic singular systems with unknown disturbance
Author :
Qu, Dongmei ; Ma, Jing ; Sun, Shuli
Author_Institution :
Sch. of Math. Sci., Heilongjiang Univ., Harbin, China
Abstract :
Based on the decomposition in canonical form, an optimal state filter in the linear unbiased minimum variance sense is given for single-sensor stochastic singular systems with unknown disturbance and correlated noises in the case of Y-observable system, which is independent of the unknown disturbance. When the system is measured by multiple sensors, the computation formula for the filtering error cross-covariance matrix between any two sensor subsystems is derived. Further, the distributed information fusion state filter is given based on the fusion algorithm weighted by matrix in the linear minimum variance sense. The simulation research shows the effectiveness.
Keywords :
correlation methods; covariance matrices; filtering theory; sensor fusion; stochastic systems; Y-observable system; canonical form; computation formula; correlated noises; decomposition; distributed fusion filter; distributed information fusion state filter; filtering error cross-covariance matrix; fusion algorithm; linear minimum variance sense; linear unbiased minimum variance sense; multiple sensors; optimal state filter; sensor subsystems; single-sensor stochastic singular systems; unknown disturbance; Educational institutions; Kalman filters; Matrix decomposition; Maximum likelihood detection; Nonlinear filters; Sensor systems; canonical decomposition; information fusion; stochastic singular systems; unknown disturbance;
Conference_Titel :
Intelligent Control and Automation (WCICA), 2010 8th World Congress on
Conference_Location :
Jinan
Print_ISBN :
978-1-4244-6712-9
DOI :
10.1109/WCICA.2010.5555033