A robust Kalman filter scheme is proposed to resist the influence of the outliers in the
observations. Two kinds of observation error are studied, ie, the outliers in the actual …

The Kalman filter has been applied extensively in the area of kinematic geodetic positioning.
The reliability of the linear filtering results, however, is reduced when the kinematic model …

A robust Kalman filter is derived for rank deficient observation models. The datum for the
Kalman filter is introduced at the zero epoch by the choice of a generalized inverse. The …

In a robustly adaptive Kalman filter, the key problem is to construct an adaptive factor to
balance the contributions of the kinematic model information and the measurements on the …

In this paper, a robust unscented Kalman filter (UKF) based on the generalized maximum
likelihood estimation (M-estimation) is proposed to improve the robustness of the integrated …

After reviewing the two main approaches of adaptive Kalman filtering, namely, innovation-
based adaptive estimation (IAE) and multiple-model-based adaptive estimation (MMAE), the …

In this article, we focus on addressing the nonlinear filtering problem with unknown
measurement noise covariance and measurement outliers, which may be encountered in …

This paper presents a hypothesis test-constrained robust Kalman filter for INS/GNSS (inertial
navigation system/global navigation satellite system) integrated navigation in the presence …

When certain constraints in the kinematic state parameters of a multi-sensor navigation
system exist, they should be taken into account for the improvement of the positioning …

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 …