3D Source Tracking Using a Position-Unknown AOA Sensor with Measurement Drift and UAV Moving Direction Optimization

This work solves the angle-of-arrival (AOA) source tracking problem in 3-dimensional (3D) space utilizing a position-unknown unmanned aerial vehicle (UAV). An AOA sensor is carried by a mobile UAV, and the conventional self-positioning module, such as the global positioning system (GPS), is not allowed due to environmental limitations. Thus, to guarantee the feasibility of this source tracking problem, at least two position-known landmarks are required. Firstly, the detailed problem formulation is provided with the consideration of measurement drift caused by sensor-vehicle installation errors. Secondly, all the unknown states are estimated using a proposed extended Kalman filter (EKF). Thirdly, a UAV moving direction optimization algorithm is developed to promote the estimation accuracies of the source, UAV and measurement drift. Finally, simulation examples demonstrate the characteristics of the proposed method.