DocumentCode
1893721
Title
Comparison of two IMM tracking and classifier architectures based on Extended and Unscented Kalman Filter with CRLB
Author
Farina, A. ; Immediata, S. ; Meloni, M. ; Timmoneri, L. ; Vigilante, D.
fYear
2005
fDate
17-20 July 2005
Firstpage
485
Lastpage
490
Abstract
On the basis of the BT kinematics model it is possible to build up an interactive multiple model (IMM) for target tracking using EKFs and UKFs. The performance evaluation (accuracies and classification) of the designed IMM tracking algorithm is predicted via Monte Carlo simulation and compared with the CRLB achievable for the same study case
Keywords
Kalman filters; Monte Carlo methods; filtering theory; kinematics; performance evaluation; signal classification; target tracking; tracking filters; BT kinematics model; CRLB; Cramer Rao lower bound; EKF; IMM target tracking; Monte Carlo simulation; UKF; classifier architecture; extended Kalman filter; interactive multiple model; performance evaluation; unscented Kalman filter; Acceleration; Algorithm design and analysis; Computer architecture; Equations; Filtering; Gravity; Kinematics; Nonlinear filters; Radar tracking; Target tracking;
fLanguage
English
Publisher
ieee
Conference_Titel
Statistical Signal Processing, 2005 IEEE/SP 13th Workshop on
Conference_Location
Novosibirsk
Print_ISBN
0-7803-9403-8
Type
conf
DOI
10.1109/SSP.2005.1628644
Filename
1628644
Link To Document