Bounding the Estimation Error Covariance for Nonlinear Systems
Abstract
This paper presents preliminary work on computing upper bounds on the estimation error covariance in the framework of the extended Kalman filter. The approach taken is using quadratic constraints to bound the dynamic nonlinearities and use of semidefinite programs to find the upper bound of each entry of the estimation error covariance matrix.
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