Work

Posterior Cramer-Rao bounds for discrete-time nonlinear filtering

Year: 1998

Type: article

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.

Source: IEEE Transactions on Signal Processing

DOI: 10.1109/78.668800

Authors: P. Tichavsky, C.H. Muravchik, A. Nehorai

Institutions: Czech Academy of Sciences, Czech Academy of Sciences, Institute of Information Theory and Automation, Universidad Nacional de La Plata, University of Illinois Chicago

Language: English

Topic: Target Tracking and Data Fusion in Sensor Networks

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green