Title :
Research on adaptive information fusion Kalman filter algorithm
Author_Institution :
IEEE Conference Publishing, Piscataway, NJ, USA
Abstract :
In the extended Kalman filter (EKF) and the unscented Kalman filter (UKF) of non-linear system, the mathematical model and the noise statistics are essential; this limitation was settled by adaptive algorithm. The adaptive extended Kalman filter (AEKF) and adaptive unscented filter (AUKF) were proposed to solve the filtering problem of the system with unknown mathematical model or noise statistics in information fusion. The simulation result shows that the adaptive algorithm in EKF and UKF can improve the performance of filter and decrease the computing time.
Keywords :
adaptive Kalman filters; nonlinear filters; sensor fusion; statistical analysis; AEKF; AUKF; adaptive extended Kalman filter; adaptive information fusion Kalman filter algorithm; adaptive unscented Kalman filter; computing time reduction; filter performance improvement; mathematical model; noise statistics; nonlinear system; Equations; Filtering algorithms; Filtering theory; Heuristic algorithms; Kalman filters; Mathematical model; Noise;
Conference_Titel :
Microwave and Millimeter Wave Technology (ICMMT), 2012 International Conference on
Conference_Location :
Shenzhen
Print_ISBN :
978-1-4673-2184-6
DOI :
10.1109/ICMMT.2012.6230454
