Estimation of Sideslip Angle Based on Extended Kalman Filter

Predictive Angle Tracking Algorithm Based on Extended Kalman Filter

In the case of moving sources, various target angle tracking algorithms have been proposed and reported in the literature for multiple narrow-band targets. Yang and Kaveh proposed an iterative adaptive eigen-subspace method in conjunction with the multiple signal classification (MUSIC) algorithm to track the DOA angles of multiple targets (Yang & Kaveh, 1988). Due to the data association proble...

Sideslip Angle Estimation Based on GPS and Magnetometer Measurements

This paper proposes a cost-effective method to estimate the vehicle sideslip angle on various frictional surfaces on banked roads. This paper demonstrates that the vehicle sideslip can be estimated by combining measurements of Global Positioning System (GPS), Inertial Measurement Unit (IMU), and a magnetometer in the Kalman filter framework. Among all the measurements, the magnetometer is the m...

Extended Kalman Filter Based Pose Estimation Using Multiple Cameras

In this work, we solve the pose estimation problem for robot motion by placing multiple cameras on the robot. In particular, we combine the Extended Kalman Filter (EKF) with the multiple cameras. An essential strength of our approach is that it does not require finding image feature correspondences among cameras which is a difficult classical problem. The initial pose, the tracked features, and...

Extended Kalman Filter Based Fuzzy Adaptive Filter

Vehicle sideslip angle measurement based on sensor data fusion using an integrated ANFIS and an Unscented Kalman Filter algorithm

Most existing ESC (Electronic Stability Control) systems rely on the measurement of both yaw rate and sideslip angle. However, one of the main issues is that the sideslip angle cannot be measured directly because the sensors are too expensive. For this reason, sideslip angle estimation has been widely discussed in the relevant literature. The modeling of sideslip angle is complex due to the non...