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 …

Due to its widespread application in the robotics field, the Kalman filter has received
increased attention from researchers. This work reviews some of the modifications …

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 …

In this paper, we propose a novel accurate method for dead-reckoning of wheeled vehicles
based only on an Inertial Measurement Unit (IMU). In the context of intelligent vehicles …

Connected and automated vehicles (CAVs) are expected to revolutionize the transportation
industry, mainly through allowing for a real-time and seamless exchange of information …

The unscented Kalman filter (UKF) has proved to be a promising methodology to integrate
INS and GPS for vehicular navigation. Nevertheless, the disturbance suppression of system …

Accurate estimation of the dynamic states of a synchronous machine (eg, rotor's angle and
speed) is essential in monitoring and controlling transient stability of a power system. It is …

Battery management system (BMS) is one of the key subsystems of electric vehicle, and the
battery state-of-charge (SOC) is a crucial input for the calculations of energy and power …

To solve the problem of unknown noise covariance matrices inherent in the cooperative
localization of autonomous underwater vehicles, a new adaptive extended Kalman filter is …

An accurate battery State of Charge estimation is of great significance for battery electric
vehicles and hybrid electric vehicles. This paper presents an adaptive unscented Kalman …