Kalman Filter-Aware Air-Ground Cooperative System Target Pose with Noise

This article uses the Kalman filter to acquire the ground target pose when noise is introduced into the air-ground cooperative system. To obtain ground environmental information, a vision sensor is mounted on the drone to capture image information. Then, kalman filter is adopted into the perception system to acquire the pose of the target. This application effectively mitigates the noise resulting from drone vibration or moving obstacles such as birds. Subsequently, the optimal path can be planned for the target unmanned vehicle by A-star algorithm, following which the vehicle can be guided to reach the desired destination. Ultimately, experimental results are provided to validate the effectiveness and the feasibility of the proposed application.