Title :
Nonlinear Target Identification and Tracking Using UKF
Author :
Khairnar, D.G. ; Nandakumar, S. ; Merchant, S.N. ; Desai, U.B.
Author_Institution :
Indian Inst. of Technol., Mumbai
Abstract :
In this paper, we implemented target identification algorithm using Dempster Shafer theory (DST) and tracking algorithm using extended Kalman filter (EKF) and unscented Kalman filter (UKF). A tracking filter is developed and simulated based on UKF to track nonlinear, ballistic and reentry targets. Comparison of EKF and UKF for nonlinear targets tracking are presented based on the simulation results. Simulated results gives more supporting points to use UKF for nonlinear target tracking rather using EKF.
Keywords :
Kalman filters; ballistics; inference mechanisms; military computing; military radar; nonlinear filters; radar tracking; target tracking; Dempster Shafer theory; ballistic target tracking; extended Kalman filter; nonlinear target identification; radar target identification; reentry target tracking; tracking algorithm; tracking filter; unscented Kalman filter; Airborne radar; Aircraft; Equations; Radar applications; Radar imaging; Radar theory; Radar tracking; Signal processing algorithms; Target recognition; Target tracking;
Conference_Titel :
Granular Computing, 2007. GRC 2007. IEEE International Conference on
Conference_Location :
Fremont, CA
Print_ISBN :
978-0-7695-3032-1
DOI :
10.1109/GrC.2007.97
