Paper Info
Title
Posterior Cramer-Rao bounds for discrete-time nonlinear filtering
Abstract
A mean-square error lower bound for the discrete-time nonlinear filtering problem is derived based on the van Trees (1968) (posterior) version of the Cramer-Rao inequality. This lower bound is applicable to multidimensional nonlinear, possibly non-Gaussian, dynamical systems and is more general than the previous bounds in the literature. The case of singular conditional distribution of the one-step-ahead state vector given the present state is considered. The bound is evaluated for three important examples: the recursive estimation of slowly varying parameters of an autoregressive process, tracking a slowly varying frequency of a single cisoid in noise, and tracking parameters of a sinusoidal frequency with sinusoidal phase modulation
Year
DOI
Venue
1998
10.1109/78.668800
IEEE Transactions on Signal Processing
Keywords
Field
DocType
autoregressive processes,discrete time filters,frequency estimation,least mean squares methods,noise,nonlinear dynamical systems,nonlinear filters,phase modulation,recursive estimation,spectral analysis,time-varying systems,tracking filters,Cramer-Rao inequality,autoregressive process,discrete-time nonlinear filtering,mean-square error lower bound,multidimensional nonlinear dynamical systems,noise,nonGaussian dynamical systems,one-step-ahead state vector,posterior Cramer-Rao bounds,recursive estimation,single cisoid,singular conditional distribution,sinusoidal frequency,sinusoidal phase modulation,slowly varying frequency,slowly varying parameters,tracking
Cramér–Rao bound,Autoregressive model,Mathematical optimization,State vector,Conditional probability distribution,Nonlinear system,Control theory,Upper and lower bounds,Kalman filter,Dynamical systems theory,Mathematics
Journal
Volume
Issue
ISSN
46
5
1053-587X
Citations 
PageRank 
References 
386
30.80
6
Authors
3
Search Limit
100386
Name
Order
Citations
PageRank
P. Tichavsky157166.59
C. Muravchik254368.59
Nehorai, Arye31934309.00