Kalman Filter (KF) that is also known as linear quadratic estimation filter estimates current
states of a system through time as recursive using input measurements in mathematical …

In this paper, a novel variational Bayesian (VB)-based adaptive Kalman filter (VBAKF) for
linear Gaussian state-space models with inaccurate process and measurement noise …

This paper presents a comprehensive review of state-of-the-art navigation methods
available for unmanned aerial vehicles (UAVs) used in parcel delivery. Particularly, the …

This article considers the application of variational Bayesian methods to joint recursive
estimation of the dynamic state and the time-varying measurement noise parameters in …

The central task of GPS/INS integration is to effectively blend GPS and INS data together to
generate an optimal solution. The present data fusion algorithms, which are mostly based on …

We present a position estimation scheme for cars based on the integration of global
positioning system (GPS) with vehicle sensors. The aim is to achieve enough accuracy to …

In this paper a Robust Adaptive Kalman Filter (RAKF) is introduced. The RAKF incorporates
measurement and process noise covariance adaptation procedures (R and Q adaptation …

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

In the normal operation conditions of a pico satellite, a conventional Unscented Kalman
Filter (UKF) gives sufficiently good estimation results. However, if the measurements are not …

This paper presents the Quaternion-based Robust Adaptive Unscented Kalman Filter
(QRAUKF) for attitude estimation. The proposed methodology modifies and extends the …