Target Tracking Performance Evaluation - A General Software Environment for Filtering
2007 (English)In: Proceedings of the 2007 IEEE Aerospace Conference, 2007, 1-13 p.Conference paper (Refereed)
In this paper, several recursive Bayesian filtering methods for target tracking are discussed. Performance for target tracking problems is usually measured using the second-order moment. For nonlinear or non-Gaussian applications, this measure is not always sufficient. The Kullback divergence is proposed as an alternative to mean square error analysis, and it is extensively used to compare estimated posterior distributions for various applications. The important issue of efficient software development, for nonlinear and non-Gaussian estimation, is also addressed. A new framework in C++ is detailed. Utilizing modern design techniques an object oriented filtering and simulation framework is provided to allow for easy and efficient comparisons of different estimators. The software environment is extensively used in several applications and examples.
Place, publisher, year, edition, pages
2007. 1-13 p.
C++ listings, Filtering theory, Recursive filter, Software engineering
Engineering and Technology Control Engineering
IdentifiersURN: urn:nbn:se:liu:diva-37436DOI: 10.1109/AERO.2007.353044Local ID: 35745ISBN: 1-4244-0525-4ISBN: 1-4244-0525-4OAI: oai:DiVA.org:liu-37436DiVA: diva2:258285
2007 IEEE Aerospace Conference, Big Sky, MT, Usa, March, 2007