Vision-Based Geolocation of Ground Target Using On-Board Gimbal Camera of UAV

This paper presents an algorithm for vision-based geolocation of a ground target using on-board gimbal camera of UAV. Assume the initial location of the target is inaccurately given, initial pan/tilt angles of the gimbal camera enable the target to be captured inside the image frame. An object detection and tracking algorithm are incorporated to calculate the offset of the bounding box from the image center, which corrects the pan/tilt angles of the gimbal in order for the target to be exactly centered in the image frame. Once the target is locked on the image frame, the exact position of the target is calculated using the inertial information of the UAV as well as the measured pan/tilt angles of the gimbal camera. As the measurements for geolocationing are vulnerable to disturbances and are very noisy, the extended Kalman filter (EKF) and the unscented Kalman filter (UKF) are adopted to smooth the noisy measurements while providing reliable geolocationing of the target. Based on the extensive verification results over the simulation environment, the proposed algorithm has been implemented on an actual hardware mounted on a UAV test-bed to validate the performance via flight tests.