Title :
A note on Kalman filtering
Author :
Kwan, Chiman M. ; Lewis, Frank L.
Author_Institution :
Intelligent Autom. Corp., Rockville, MD, USA
fDate :
8/1/1999 12:00:00 AM
Abstract :
The purpose of this paper is to point out a confusing phenomenon in the teaching of Kalman filtering. Students are often confused by noting that the a posteriori error covariance of the discrete Kalman filter (DKF) is smaller than the error covariance of the continuous Kalman filter (CKF), which would mean that the DKF is better than CKF since it gives a smaller error covariance. However, simulation results show that CKF gives estimates much closer to the true states. We provide a simple qualitative argument to explain this phenomenon
Keywords :
Kalman filters; electrical engineering education; error analysis; filtering theory; state estimation; teaching; Kalman filtering; a posteriori error covariance; continuous Kalman filter; discrete Kalman filter; simulation results; teaching; Continuous time systems; Education; Estimation error; Filtering; Fluid flow measurement; Kalman filters; Random processes; Robotics and automation; Sampling methods; State estimation;
Journal_Title :
Education, IEEE Transactions on
