  This paper deals with the implementation of the extended robust Kalman filter
(ERKF) which was developed considering uncertainties in the parameter matrices
of the underlying state-space model. A key contribution of this work is the
demonstration of a method for real-time computation of the filter on parallel
computing devices. The solution of the filter is expressed as a set of
simultaneous linear equations, which can then be evaluated based on QR
decomposition using Givens rotation. This paper also presents the application
of the ERKF in the development of an attitude and position reference system for
a cargo transport vehicle. This work concludes by analyzing the performance of
the ERKF and verifying the validity of the Givens rotation method.
