The presented work is focusing on the wind estimation and airframe identification based on real flight experiments as part of the SkyScanner project. The overall objective of this project is to estimate the local wind field in order to study the formation of cumulus-type clouds with a fleet of autonomous mini-UAVs involving many aspects including flight control and energy harvesting. For this purpose, a small UAV has been equipped with airspeed and angle of attack sensors. Flight data are recorded on-board at high speed for post-analyses. An approach based on Unscented Kalman Filter (UKF) is proposed for nonlinear wind estimation. As a first result, wind updraft estimation is highlighted by exploiting recorded flight test data. In addition to this, a motor test bench has been developed in order to establish a model of the propulsion system from wind tunnel experiments. It will be combined with a classical aerodynamic model for airframe identification Preliminary flight results are presented.