Title :
Asymptotic Optimality of the Minimum-Variance Fixed-Interval Smoother
Author :
Einicke, Garry A.
Author_Institution :
CSIRO, Pullenvale, Qld.
fDate :
4/1/2007 12:00:00 AM
Abstract :
This correspondence investigates the asymptotic performance of the discrete-time and continuous-time, time-varying, minimum-variance, fixed-interval smoothers. Comparison theorems are generalized to provide sufficient conditions for the monotonic convergence of the underlying Riccati equations. Under these conditions, the energy of the estimation errors asymptotically approach a lower bound and attain lscr2 /L2 stability
Keywords :
Riccati equations; continuous time filters; discrete time filters; matrix algebra; smoothing methods; time-varying filters; Riccati equations; asymptotic optimality; continuous-time smoothers; discrete-time smoother; minimum-variance fixed-interval smoother; time-varying smoothers; Asymptotic stability; Convergence; Difference equations; Differential equations; Estimation error; Filtering; Noise measurement; Riccati equations; Smoothing methods; Sufficient conditions; Kalman filtering; Riccati equations; noncausal filtering; smoothing; stability;
Journal_Title :
Signal Processing, IEEE Transactions on
DOI :
10.1109/TSP.2006.889402
