Kalman filtering: theory and practice
Kalman filtering: theory and practice
Synchronization of input and output measurements using a Kalman filter
MIC'06 Proceedings of the 25th IASTED international conference on Modeling, indentification, and control
New developments in state estimation for nonlinear systems
Automatica (Journal of IFAC)
Synchronization of input and output measurements using a Kalman filter
MIC'06 Proceedings of the 25th IASTED international conference on Modeling, indentification, and control
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Extended Kalman filters have long been applied to sensor fusion in navigation tasks. They can be used to estimate both the states and the parameters of the dynamic system. In recent years, so-called sigma-point Kalman filters with an improved estimation accuracy compared to extended Kalman filters have emerged. This work shows how these filters can be applied to calibrate an inertial measurement unit used for unaided navigation. Two different filter structures are proposed: a forward filter models the whole navigation process (states and parameters) while an inverse filter performs only a parameter estimation.