Fuzzy variant of a statistical test point Kalman filter

Fixed-point FPGA Implementation of a Kalman Filter for Range and Velocity Estimation of Moving Targets

Tracking filters are extensively used within object tracking systems in order to provide consecutive smooth estimations of position and velocity of the object with minimum error. Namely, Kalman filter and its numerous variants are widely known as simple yet effective linear tracking filters in many diverse applications. In this paper, an effective method is proposed for designing and implementa...

Extended Kalman Filter Based Fuzzy Adaptive Filter

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 ...

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 Variational Bayesian Unscented Kalman Filter

We consider the problem of nonlinear filtering under the circumstance of unknown covariance statistic of the measurement noise. A novel adaptive unscented Kalman filter (UKF) integrating variational Bayesian methods and fuzzy logic techniques is proposed in this paper. It is called fuzzy adaptive variational Bayesian UKF (FAVBUKF). Firstly, the sufficient statistics of the measurement noise var...