2004 IEEE Radar Conference

Innovative Radar Technologies - Expanding System Capabilities

 
 
 April 26-29, 2004 Wyndham Philadelphia at Franklin Plaza Philadelphia, Pennsylvania
 
 
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Session 4B.3
A constrained extended Kalman filter for target tracking

Anders Erik Nordsjo - Saab Bofors Dynamics

Tue, 27 April 2004, 4:10 PM - 5:30 PM


Abstract

An Extended Kalman Filter, EKF is proposed for tracking of the position and velocity of a moving target. The suggested method is based on a nonlinear model which, in addition, incorporates means for estimation of possible nonlinearities in the measurements of the target position. In many practical scenarios, the initial estimates of target position and velocity will deviate significantly from the true ones. In order to reduce the impact of erroneous initial conditions and hence, obtain a faster initial convergence to an acceptable trajectory, a certain constrained form of the EKF, named the CEKF, is introduced. Although the original Kalman filter for a purely linear system is inherently stable, there is no guarantee that the linearized model used in the EKF gives a stable algorithm. Hence, it is interesting to note that the proposed CEKF under certain mild conditions renders an exponentially stable algorithm. It is shown that this latter method can conveniently be formulated as a nonlinear minimization problem with a quadratic inequality constraint.

Bio

Dr. Anders Erik Nordsjo - Saab Bofors Dynamics

Anders Erik Nordsjo received M.Sc. and Ph.D. degrees in electrical engineering from the Royal Institute of Technology, (KTH), Stockholm, Sweden. Previously employed at ITT, Ericsson and KTH, he worked in the areas of data communication and mobile phone systems. He is currently with Saab Bofors Dynamics working with radar system analysis. His research interests include nonlinear system identification, detection, estimation and tracking techniques, in particular with application to radar.

 
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