… Abstract In a robustly adaptive Kalman filter, the key problem is to construct an adaptive
factor to … What we pursue in this paper are some optimal adaptive factors under the particular …

A Kalman filter requires an exact knowledge of the process noise covariance matrix Q and
the measurement noise covariance matrix R . Here we consider the case in which the true …

… Adaptive filters are … this limitation of the normal Kalman filter algorithm. Adaptive Kalman
filter algorithm For adaptive Kalman filters, the measurement variance, rk, plays an important role…

… adaptive Kalman filter as an alternative for use with INS/GPS systems. In this contribution,
the general layout of the adaptive Kalman filtering … the adaptive Kalman filter outperforms the …

… In this paper, an optimization-based adaptive Kalman filtering method is proposed. The
method produces an estimate of the process noise covariance matrix Q by solving an …

… In this paper, we investigate the performance of two different adaptive Kalman filters for
vehicle navigation using GPS, one based on the fading memory and one based on the variance …

… These are artificially scaling the predicted Kalman filter covariance, the Adaptive Kalman
Filter … the use of adaptive Kalman filtering algorithms for improving Kalman filter performance. …

… This paper summarizes the development of an adaptive Kalman filter for … adaptive filter is
to reduce or bound these errors by modifying, or adapting, the models used in the Kalman filter …

… This paper investigates three adaptive Kalman filtering algorithms … adaptive Kalman filtering
algorithms are shown tu reduce the dependence on the a priori information used in the filter. …

… of Kalman filtering. For instance, the maximum likelihood (ML) method was employed in
adaptive Kalman filtering (… and residual based adaptive Kalman filtering techniques have been …