Accession Number:

ADA458785

Title:

Kinematic and Attribute Fusion Using a Bayesian Belief Network Framework

Descriptive Note:

Research rept.

Corporate Author:

DEFENCE SCIENCE AND TECHNOLOGY ORGANISATION EDINBURGH (AUSTRALIA) INTELLIGENCE SURVEILLANCE AND RECONNAISSANCE DIV

Personal Author(s):

Report Date:

2006-08-01

Pagination or Media Count:

50.0

Abstract:

The focus of tracking applications has traditionally centred on kinematic state estimation. However, attribute information has the potential to not only provide identity and class information, but it may also improve data association and kinematic tracking performance, Bayesian Belief Networks provide a framework for specifying the dependencies between kinematic and attribute states. Algorithms based on this framework are developed for joint kinematic and attribute data association, kinematic tracking, attribute state estimation, and joint kinematic and attribute tracking. The algorithms are demonstrated using simulated tracking scenarios.

Subject Categories:

  • Statistics and Probability
  • Mechanics

Distribution Statement:

APPROVED FOR PUBLIC RELEASE