An approach to ground target localization for UAVs based on multi-sensor fusion

In this paper, an approach based on multiple airborne sensors fusion to ground target localization for UAVs is proposed, which is the basis of UAVs applications, such as obstacle avoidance, target confirmation, etc. Challenges from accuracy improvement and system disturbance are considered. Sensor information is obtained by a visual sensor, GPS, and IMU modules. Traditional methods are mainly aimed at an upright position for visual sensors. First of all, an online multi-sensor calibration method using GPS is designed, calibrating the orientation of the visual sensor to the UAVs location. Then the target can be detected using Adaboost algorithm based on acquisition information of different visual sensors. And information obtained by real-time GPS, IMU, altimeter, and visual image based on Kalman filter is fused for target localization. Finally a D-S method for estimating the confidence level of target location is designed for perception disturbance. Experiments are implemented on rotor aircrafts and fixed-wing UAVs and the results show that the method, as feasible as it is, can effectively percept disturbance and improve location accuracy of a certain target.