A stochastic analysis of a modified gain extended Kalman filter with applications to estimation with bearings only measurements 论文

1985IEEE Transactions on Automatic Control引用 294
Target Tracking and Data Fusion in Sensor NetworksAdaptive Control of Nonlinear SystemsInertial Sensor and Navigation

摘要

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.