The CramrRao Estimation Error Lower Bound Computation for Deterministic Nonlinear Systems

For condouous-time nonlinear deterministie system models with diserete nonlinear measuremeuts in additive Gaussian white noise,the extended Kalman filter (EKF) convariance propagation equations linearized about the true unknown trajectory provide the Cramér-Rao lower bound to the estimadon error covariance matrix. A useful application is establishing the optimum filter performance for a given nonlinear estimation problem by developing a simulation of the nonlinear system and an EKF linearized about the true trajectory.