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Clouds play an important role in climate change, in the prediction of local weather, and also in aviation safety when instrument assisted flying is unavailable. Presently, various ground-based instruments used for the measurements of the cloud base height or velocity. Lidar techniques are powerful and have many applications in climate studies, including the clouds' temperature measurement, the aerosol particle properties, etc. Otherwise, it is very circumscribed in cloud velocity measurements because there is no Doppler effect if the clouds move in the perpendicular direction to the laser beam path of Doppler lidar.In this paper, we present a method for the measurement of cloud velocity using lidar's range detection and DIC (Digital Image Correlation) system to overcome the disadvantage of Doppler lidar. The lidar system acquires the distance to the cloud, and the cloud images are tracked using the developed fast correlation algorithm of DIC. We acquired the velocities of clouds using the calculated distance and DIC algorithm. The measurement values had a linear distribution.

Stabilization techniques for a wavefront correction system using a Shack-Hartmann wavefront sensor and a membrane deformable mirror (DM) for robust image acquisition were investigated in this research. Though stability of a closed-loop wavefront correction system is essential in practical fields, stability is decreased when the system spends voltage resources to correct non-meaningful residual distortions. In this research, adaptive limit control techniques were devised to ensure the long-term stability of a wavefront correction system. An adaptive deformation technique for the outer non-active actuators of a membrane deformable mirror was adopted to improve the correction efficiency of the wavefront correction system. The experimental results corrected for wavefront distortions by using a configured wavefront correction system were described in this research.

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