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.
3D city map reconstruction from UAV-based radio measurements
GLOBECOM 2017, IEEE Global Communications Conference, December 4-8, 2017, Singapore, Singapore
© 2017 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
PERMALINK : https://www.eurecom.fr/publication/5500