Brief paper: Consistency and robustness of PDAF for target tracking in cluttered environments

Authors:
Y. Bar-Shalom;K. Birmiwal
Affiliations:
On leave at the Department of Engineering-Economic Systems, Stanford University, Stanford, CA 94305, U.S.A.;Department of Electrical Engineering, University of Connecticut, Storrs, CT 0628, U.S.A.
Venue:
Automatica (Journal of IFAC)
Year:
1983

Citing 3
Cited 0

Tracking in a cluttered environment with probabilistic data association

Automatica (Journal of IFAC)
Correspondence item: An innovations approach to fault detection and diagnosis in dynamic systems

Automatica (Journal of IFAC)
Derivation and evaluation of improved tracking filter for use in dense multitarget environments

IEEE Transactions on Information Theory

Quantified Score

Hi-index	22.14

Visualization

Abstract

This paper presents a simulation-based investigation of the consistency of the PDAF via statistical tests of its actual errors versus the filter calculated covariances. These tests confirm the goodness of the approximation done at every stage in the PDAF, where a Gaussian mixture is replaced by an 'umbrella' Gaussian using moment matching. Two versions of the PDAF are examined: a parametric one that uses a Poisson model for the number of clutter originated measurements and a nonparametric one that uses a diffuse prior. While no new theoretical results are presented, the methodology of testing filter consistency can prove to be useful in the general evaluation of filters that contain approximations.