Fuzzy Rule-Based Adaptive Kalman Filter for State Estimation of Anti-Tank Threats

An Effective Attack-Resilient Kalman Filter-Based Approach for Dynamic State Estimation of Synchronous Machine

Kalman filtering has been widely considered for dynamic state estimation in smart grids. Despite its unique merits, the Kalman Filter (KF)-based dynamic state estimation can be undesirably influenced by cyber adversarial attacks that can potentially be launched against the communication links in the Cyber-Physical System (CPS). To enhance the security of KF-based state estimation, in this paper...

Extended Kalman Filter Based Fuzzy Adaptive Filter

Doppler and bearing tracking using fuzzy adaptive unscented Kalman filter

The topic of Doppler and Bearing Tracking (DBT) problem is to achieve a target trajectory using the Doppler and Bearing measurements. The difficulty of DBT problem comes from the nonlinearity terms exposed in the measurement equations. Several techniques were studied to deal with this topic, such as the unscented Kalman filter. Nevertheless, the performance of the filter depends directly on the...

Fuzzy Adaptive Extended Kalman Filter

Kalman filtering is a method for estimating state variables of a dynamic systems recursively from noise-contaminated measurements. For systems with nonlinear dynamics, a natural extension of the Linear Kalman Filter (LKF), called Extended Kalman filter (EKF) is used. The Kalman filter represents one of the most popular estimation techniques for integrating signals from navigation systems, like ...

Unscented Kalman Filter for Vehicle State Estimation

Vehicle Dynamics Control (VDC) systems require the information about system variables, which cannot be directly measured, e.g., the wheel slip or the vehicle side-slip angle. This paper presents a new concept for the vehicle state estimation under assumption that the vehicle is equipped with the standard VDC sensors. It is proposed to utilize an Unscented Kalman Filter (UKF) for estimation purp...