A method of multirate sensor fusion for target tracking and localization using extended Kalman Filter

摘要

This paper presents a method of target tracking and localization for surveillance vehicle with visual-inertia sensor-fusion using extended Kalman Filter (EKF). In this application, the visual information is obtained using rotating camera and laser range finder. The visual data are used to incorporate inertial measuring unit (IMU) in the determination of position and velocity of the surveillance vehicle and also used to determine the position and velocity of the target which is moving with respect to the moving surveillance vehicle. As the camera is rotating, the visual data is available in aperiodic intervals (i.e., the target/landmark is presented in the field of view). Here, an EKF is used as state estimator to describe the position and velocity of the surveillance vehicle from the noisy, multi-rate measurements given by the sensing system. The prediction and measurement models are developed for the movement of vehicle and sensing system. The numerical simulation is used to investigate the performance of the proposed method. The simulation results show that proposed method can be used for target tracking and is able to improve the localization performance.