Title :
A stochastic analysis of a modified gain extended Kalman filter with applications to estimation with bearings only measurements
Author :
Song, Taek L. ; Speyer, Jason L.
Author_Institution :
University of Texas at Austin, Austin, TX, USA
fDate :
10/1/1985 12:00:00 AM
Abstract :
A new globally convergent nonlinear observer, called the modified gain extended Kalman observer (MGEKO), is developed for a special class of systems. This observer structure forms the basis of a new stochastic filter mechanization called the modified gain extended Kalman filter (MGEKF). A sufficient condition for the estimation errors of the MGEKF to be exponentially bounded in the mean square is obtained. Finally, the MGEKO and the MGEKF are applied to the three-dimensional bearings-only measurement problem where the extended Kalman filter often shows erratic behavior.
Keywords :
Direction-of-arrival estimation; Kalman filtering, nonlinear systems; Missile guidance; Observers, nonlinear systems; Convergence; Gain measurement; Kalman filters; Nonlinear filters; Observers; Riccati equations; Stability analysis; State-space methods; Stochastic processes; Sufficient conditions;
Journal_Title :
Automatic Control, IEEE Transactions on
DOI :
10.1109/TAC.1985.1103821