  Unmanned aerial vehicle (UAV)-to-ground (U2G) channel models play a pivotal
role for reliable communications between UAV and ground terminal. This paper
proposes a three-dimensional (3D) non-stationary hybrid model including both
large-scale and small-scale fading for U2G multiple-input-multiple-output
(MIMO) channels. Distinctive channel characteristics under U2G scenarios, i.e.,
3D trajectory and posture of UAV, fuselage scattering effect (FSE), and posture
variation fading (PVF), are incorporated into the proposed model. The channel
parameters, i.e., path loss (PL), shadow fading (SF), path delay, and path
angle, are generated incorporating machine learning (ML) and ray tracing (RT)
techniques to capture the structure-related characteristics. In order to
guarantee the physical continuity of channel parameters such as Doppler phase
and path power, the time evolution methods of inter- and intra- stationary
intervals are proposed. Key statistical properties , i.e., temporal
autocorrection function (ACF), power delay profile (PDP), level crossing rate
(LCR), average fading duration (AFD), and stationary interval (SI) are given,
and the impact of the change of fuselage and posture variation is analyzed. It
is demonstrated that both posture variation and fuselage scattering have
crucial effects on channel characteristics. The validity and practicability of
the proposed model are verified by comparing the simulation results with the
measured ones.
