Before revision: For use in non-linear systems, the observation and state transition models may be linearized around the current mean and covariance estimate in a method analogous to the extended Kalman filter Naming and historical development Stanley F. Schmidt developed the Schmidt-Kalman filter as a method to account for unobservable biases while maintaining the low dimensionality required for implementation in real time systems.
After revision: For use in non-linear systems, the observation and state transition models may be linearized around the current mean and covariance estimate in a method analogous to the extended Kalman filter Naming and historical development Stanley F. Schmidt developed the Schmidt–Kalman filter as a method to account for unobservable biases while maintaining the low dimensionality required for implementation in real time systems.