3D city map reconstruction from UAV-based radio measurements

This paper considers the problem of 3D city map reconstruction. The key novelty here lies in the sole exploitation of UAV-bound radio measurements as a way to recover the map data, i.e. no image of the city is taken or processed. The proposed approach relies on the unique ability for a UAV- to-ground communication system to detect and classify line-of-sight (LoS) vs. non line-of-sight (NLoS) channels towards ground users using machine learning tools. Once classification is carried out, the LoS vs. NLoS data is fed as input to a building position and height reconstruction algorithm. The map reconstruction quality is analyzed as a function of user density and UAV altitude, revealing the notion of an optimal height for the UAV which is predicted using an analytical model.