Precise drone location and tracking by adaptive matched filtering from a top-view ToF camera

Nowadays the use of drones is rapidly growing, and the autonomous navigation capability depends on knowing their position at any time. The precision and robustness of a local positioning system for these devices is of particular importance in takeoff and landing maneuvers, especially in GPS-denied environments. The main contribution of this work lies in the development of a precise local positioning and tracking system for drones. For this purpose, a ToF camera has been installed on the ceiling in order to make use of its depth maps. Taking as a reference the disturbance caused by a quadrotor in one of these maps, a novel 2D matched filter has been designed based on a Gaussian wavelet. This filter allows the system to quickly detect all drones flying in the scene. Moreover, it is dynamically adapted to the image portion that they occupy, taking into account the variation of this parameter with their flying altitude, which has also been theoretically determined. The whole algorithm leads to a precise 3D drone positioning. In addition, the proposed system is also robust against short-time occlusions, since the measurements history can be used to predict future positions, thus avoiding the complete loss of tracking. (C) 2019 Elsevier Ltd. All rights reserved.