Optimal State Estimation: Kalman, H Infinity, and Nonlinear Approaches
Optimal State Estimation: Kalman, H Infinity, and Nonlinear Approaches
Fir smoothing of discrete-time polynomial signals in state space
IEEE Transactions on Signal Processing
Linear optimal FIR estimation of discrete time-invariant state-space models
IEEE Transactions on Signal Processing
ADMA'10 Proceedings of the 6th international conference on Advanced data mining and applications - Volume Part II
IEEE Transactions on Signal Processing
Robust discrete-time minimum-variance filtering
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Improved robust H2 and H∞ filtering for uncertain discrete-time systems
Automatica (Journal of IFAC)
An Iterative Kalman-Like Algorithm Ignoring Noise and Initial Conditions
IEEE Transactions on Signal Processing
Unified forms for Kalman and finite impulse response filtering and smoothing
Automatica (Journal of IFAC)
Unified forms for Kalman and finite impulse response filtering and smoothing
Automatica (Journal of IFAC)
| Hi-index | 22.15 |
The Kalman filter and smoother are optimal state estimators under certain conditions. The Kalman filter is typically presented in a predictor/corrector format, but the Kalman smoother has never been derived in that format. We derive the Kalman smoother in a predictor/corrector format, thus providing a unified form for the Kalman filter and smoother. We also discuss unbiased finite impulse response (UFIR) filters and smoothers, which can provide a suboptimal but robust alternative to Kalman estimators. We derive two unified forms for UFIR filters and smoothers, and we derive lower and upper bounds for their estimation error covariances.