Title :
Tighter alternatives to the Cramer-Rao lower bound for discrete-time filtering
Author :
Reece, Steven ; Nicholson, David
Author_Institution :
Dept. of Eng. Sci., Oxford Univ., UK
Abstract :
The Cramer-Rao Lower Bound establishes a fundamental performance baseline for gauging parameter estimation accuracy in tracking and data fusion. However, it is known to be a weak lower bound for some problems. This paper presents a set of tighter alternatives: the Bhattacharyya, Bobrovsky-Zakai and Weiss-Weinstein lower bounds. General mathematical expressions are obtained for these bounds and their calculation is described. Then the bounds are applied to a nonlinear/non-Gaussian estimation problem. It is found that the alternative bounds are tighter than the Cramer-Rao bound, but they are still somewhat conservative.
Keywords :
discrete time filters; nonlinear estimation; nonlinear filters; sensor fusion; target tracking; tracking filters; Cramer-Rao lower bound; data fusion; discrete-time filtering; gauging parameter estimation; nonGaussian estimation; nonlinear estimation; target tracking; Communication system control; Control systems; Data engineering; Filtering; Filters; Parameter estimation; Sensor phenomena and characterization; Sensor systems; Signal processing algorithms; Target tracking;
Conference_Titel :
Information Fusion, 2005 8th International Conference on
Print_ISBN :
0-7803-9286-8
DOI :
10.1109/ICIF.2005.1591842