Object tracking through the atmosphere using adaptive optics

An increasing number of both civilian and military applications require the motion description of translating targets from a sequence of frames acquired through long atmospheric paths. These images are randomly distorted, due to atmospheric turbulence, although adaptive optics systems can partially compensate for this distortion in real time. In these adverse conditions, a velocimetry technique that is based on the spatio-temporal Fourier transform of a series of images presents several advantageous features. In those cases where the target is very dim or an additional processing time reduction is needed, low-light-level images are recorded. Consequently, we have developed a simulation algorithm that generates atmospherically distorted low-light-level images corresponding to different atmospheric conditions and different degrees of compensation. In this paper, simulated low-light-level images are used to analyze the technique accuracy for estimating the object velocity for several atmospheric conditions and for different correction degrees.