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.
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;
Conference_Titel :
Statistical Signal Processing, 2005 IEEE/SP 13th Workshop on
Conference_Location :
Novosibirsk
Print_ISBN :
0-7803-9403-8
DOI :
10.1109/SSP.2005.1628644
