Title :
A variation on the extended Kalman filter
Author_Institution :
Dept. of Aeronaut. & Astronaut., Air Force Inst. of Technol., Wright-Patterson AFB, OH, USA
Abstract :
Using the Bayesian probability density update relations for a discrete time nonlinear system and making Gaussian density approximations leads to a variation on the traditional extended Kalman filter (EKF) which permits additional freedom in the filter design
Keywords :
Bayes methods; Kalman filters; discrete time systems; nonlinear control systems; probability; state estimation; Bayesian probability density update relations; Gaussian density approximations; discrete time nonlinear system; extended Kalman filter; filter design; Bayesian methods; Discrete time systems; Equations; Extraterrestrial measurements; Filtering; Kalman filters; Measurement standards; Nonlinear systems; Space technology; Taylor series;
Conference_Titel :
Decision and Control, 1994., Proceedings of the 33rd IEEE Conference on
Conference_Location :
Lake Buena Vista, FL
Print_ISBN :
0-7803-1968-0
DOI :
10.1109/CDC.1994.411163
