A mathematical framework to predict the Unscented Kalman Filter (UKF) performance improvement relative to the Extended Kalman Filter (EKF) using a quantitative measure of non-linearity is presented. It is also shown that the range of performance …
This article deals with state estimation of nonlinear stochastic dynamic systems. The stress is laid on general introduction of the selected estimation methods, description of their application in navigation systems, and treatment of the error …
The extrapolated single propagation technique (ESPT) based particle filter is proposed. Instead of propagating all the sample state vectors using multiple numerical integrations, only one sample state vector is propagated in the ESPT. Other sample …
A theoretical performance analysis of Kalman Filters for Global Navigation Satellite System GNSS-based space vehicle position estimation in varying Position Dilution of Precision (PDOP) conditions is presented. The PDOP indicates the possible …
A priori state vector and error covariance computation for the Unscented Kalman Filter (UKF) is described. The original UKF propagates multiple sigma points to compute the a priori mean state vector and the error covariance, resulting in a higher …