DocumentCode
1996571
Title
A hybrid bootstrap filter for target tracking in clutter
Author
Gordon, Neil
Author_Institution
Defence Res. Agency, Farnborough, UK
Volume
1
fYear
1995
fDate
21-23 Jun 1995
Firstpage
628
Abstract
The problem of tracking multiple targets with multiple sensors in the presence of interfering measurements is considered. A new hybrid bootstrap filter is proposed. The bootstrap filter is an approach where random samples are used to represent the target posterior distributions. By using this approach, the author circumvents the usual problem of an exponentially increasing number of association hypotheses as well as allowing the use of any nonlinear/non-Gaussian system and/or measurement models
Keywords
Monte Carlo methods; clutter; filtering theory; sensor fusion; state estimation; target tracking; clutter; hybrid bootstrap filter; measurement models; multiple sensors; multiple targets; nonlinear/nonGaussian system models; posterior distributions; random samples; target tracking; Bayesian methods; Clutter; Filters; Information filtering; Interference; Merging; Noise measurement; Probability density function; Sensor systems; Target tracking;
fLanguage
English
Publisher
ieee
Conference_Titel
American Control Conference, Proceedings of the 1995
Conference_Location
Seattle, WA
Print_ISBN
0-7803-2445-5
Type
conf
DOI
10.1109/ACC.1995.529326
Filename
529326
Link To Document