In this study, a novel robust measure of non‐linearity‐based cubature Kalman filter
(RMoNCKF) is proposed to obtain good performance with lower computational burden. The …

The paper addresses state estimation of nonlinear stochastic dynamic systems. In particular,
the stress is laid on the selection and performance monitoring of estimators based on …

Grid-based Nonlinear Estimation and its Applications presents new Bayesian nonlinear
estimation techniques developed in the last two decades. Grid-based estimation techniques …

Cubature Kalman Filters (CKF) and other related techniques based on evaluation of non-
linear functions at so-called “sigma-points” are a popular and effective modern non-linear …

In this paper, an adaptive cubature Kalman filter (ACKF) is proposed to improve the
performance of the conventional cubature Kalman filter. The ACKF uses a new cubature rule …

The paper presents the Noise covariance matrices Estimation with Gaussianity Assessment
(NEGA) method that describes the noise characteristics of a linear time-varying state-space …

We consider measures of nonlinearity (MoNs) of a polynomial curve in two-dimensions (2D),
as previously studied in our Fusion 2010 and 2019 ICCAIS papers. Our previous work …

The paper introduces a novel approach to an estimator design, the cooperative filter design,
for state estimation of nonlinear systems. The approach is based on the idea of combining …

A new nonlinear filtering algorithm based on sparse-grid Gauss-Hermite filter (SGHF)
incorporated with the technique of algorithm adapting to dimensions based on their …

In the nonlinear estimation problem, the direct evaluation of posterior density function (PDF)
is always intractable due to the complex nonlinear integral. In this paper, we propose a …