The Kalman filter (KF) is a popular state estimation technique that is utilized in a variety of
applications, including positioning and navigation, sensor networks, battery management …

Since the landmark work of RE Kalman in the 1960s, considerable efforts have been
devoted to time series state space models for a large variety of dynamic estimation …

In this paper, in order to enhance the numerical stability of the unscented Kalman filter (UKF)
used for power system dynamic state estimation, a new UKF with guaranteed positive …

This paper derives a novel initial alignment method for the strapdown inertial navigation
system (SINS), which transforms the attitude alignment into an attitude estimation problem …

Tightly coupled GNSS/INS has been widely approved as a promising substitute for
standalone GNSS in urban areas navigation. However, due to the frequent GNSS signal …

This paper proposes a modified unscented Kalman filter (UKF) with both adaptivity and
robustness. In the proposed filter, the adaptivity is achieved by estimating the time-varying …

Having an accurate mathematical model is essential in design, control, and navigation
process of an autonomous underwater vehicle (AUV). Due to the modeling simplifications …

In this letter, a new class of cubature Kalman filters (CKF) based on a spherical simplex-
radial rule is proposed to further improve accuracy and efficiency of the traditional CKF. The …

In this paper, an observer-based H∞ sampled-data fuzzy control problem is addressed for a
class of nonlinear parabolic partial differential equation (PDE) systems. With the aid of the …

The sampling-based Kalman filters have been widely used for GNSS/INS of land vehicle
navigation. Although many nonlinear filters are proposed by employing different …