  In this paper, we investigate the potential of reconfigurable intelligent
surfaces (RISs) in facilitating passive/device-free three-dimensional (3D)
drone localization within existing cellular infrastructure operating at
millimeter-wave (mmWave) frequencies and employing multiple antennas at the
transceivers. The developed localization system operates in the bi-static mode
without requiring direct communication between the drone and the base station.
We analyze the theoretical performance limits via Fisher information analysis
and Cram\'er Rao lower bounds (CRLBs). Furthermore, we develop a low-complexity
yet effective drone localization algorithm based on coordinate gradient descent
and examine the impact of factors such as radar cross section (RCS) of the
drone and training overhead on system performance. It is demonstrated that
integrating RIS yields significant benefits over its RIS-free counterpart, as
evidenced by both theoretical analyses and numerical simulations.
