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 …

The cubature Kalman filter (CKF), which is based on the third degree spherical–radial
cubature rule, is numerically more stable than the unscented Kalman filter (UKF) but less …

Filtering is a recursive estimation of hidden states of a dynamic system from noisy
measurements. Such problems appear in several branches of science and technology …

Cooperative tracking plays a key role in space situation awareness for scenarios with a
limited number of observations or poor performance of a single sensor or both. To use the …

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 investigates the particle filtering problem for a class of nonlinear/non-Gaussian
systems under the dynamic event-triggered protocol. In order to avert frequent data …

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 …

This paper presents a computationally efficient approach to evaluate multidimensional
expectation integrals. Specifically, certain nonproduct cubature points are constructed that …

This paper compares state estimation techniques for nonlinear stochastic dynamic systems,
which are important for target tracking. Recently, several methods for nonlinear state …

In this paper, the particle filtering problem is studied for a class of general nonlinear cyber-
physical systems with non-Gaussian noises under Round-Robin protocol (RRP) subject to …