The unscented Kalman filter (UKF) has proved to be a promising methodology to integrate
INS and GPS for vehicular navigation. Nevertheless, the disturbance suppression of system …

The classical unscented Kalman filter (UKF) requires prior knowledge on statistical
characteristics of system noises for state estimation of a nonlinear dynamic system. If the …

Abstract Inertial Navigation System/Celestial Navigation System (INS/CNS) integration,
especially for the tightly-coupled mode, provides a promising autonomous tactics for …

The INS/GNSS integration is the commonly used technique for hypersonic vehicle
navigation. However, owing to the complicated flight dynamics with high maneuverability …

Unscented Kalman filter (UKF) has been extensively used for state estimation of nonlinear
stochastic systems, which suffers from performance degradation and even divergence when …

The unscented Kalman filter (UKF) is a promising approach for the state estimation of
nonlinear dynamic systems due to its simple calculation process and superior performance …

In this paper, a new adaptive Kalman filter algorithm is proposed to cope with the unknown a
priori covariance matrix of process noise for the linear discrete-time systems. The process …

This paper presents a new optimal data fusion methodology based on the adaptive fading
unscented Kalman filter for multi-sensor nonlinear stochastic systems. This methodology has …

SINS/GPS integrated systems are influenced by non-Gaussian noise and unknown
measurement noise due to exogenous disturbances and inaccurate noise statistics. To …

Adaptive and robust methods are two opposite strategies to be adopted in the Kalman filter
when the difference between the predictive observation and the actual observation, ie the …