Paper Info
Title
The single-group PHD filter: An analytic solution
Abstract
In many group target tracking scenarios, a collection of targets move in a correlated manner as part of a formation, such as a convoy of vehicles. The focus of this paper is in the estimation of the evolution over time of a single-group of targets, referred to as a single-cluster, based on a sequence of partial observation sets. Based on Finite Set Statistics, the paper presents a first-moment recursion for a single-group filter and an analytic solution under linear-Gaussian assumptions. The method is demonstrated on simulated data in a cluttered environment.
Year
Venue
Keywords
2011
Information Fusion
Gaussian distribution,clutter,statistical analysis,target tracking,tracking filters,analytic solution,cluttered environment,finite set statistics,first-moment recursion,linear-Gaussian assumptions,partial observation sets,probability hypothesis density filter,single-cluster,single-group PHD filter,target collection,target tracking,Finite Set Statistics,Gaussian mixture,PHD filters,cluster processes
Field
DocType
ISBN
Gaussian filter,Mathematical optimization,Finite set statistics,Clutter,Computer science,Algorithm,Artificial intelligence,Analytic solution,Recursion,Machine learning,Statistical analysis
Conference
978-1-4577-0267-9
Citations 
PageRank 
References 
17
1.03
0
Authors
2
Name
Order
Citations
PageRank
Anthony Swain1412.66
Daniel E. Clark236036.76