Adaptive wavefront control algorithms for closed loop adaptive optics

Adaptive optics (AO) is a technology for correcting the optical effects of atmospheric turbulence in real time, and greatly enhancing the performance of ground-based optical systems beyond the limits previously imposed by the atmosphere. Optimal control algorithms for AO systems can in theory provide significant additional improvements beyond the standard control approaches presently in use, but these methods depend upon accurate knowledge of atmospheric conditions. Since these conditions vary on time scales of minutes, it becomes necessary to constantly update the control algorithm so that it adjusts to the changing atmospheric statistics. This paper presents a method for adaptively optimizing the reconstructor of a closed-loop AO system in real time. The method relies on recursive least squares techniques to track the temporal and spatial correlations of the turbulent wave-front. The performance of this method is examined for a sample scenario in which the AO control algorithm attempts to compensate for signal processing latency by reconstructing the future value of the wave-front from a combination of past and current wave-front sensor measurements. For this case, the adaptive reconstruction algorithm yields Strehl ratios within a few percent of those obtained by an optimal reconstructor derived from a priori knowledge of the strength of the turbulence and the velocity of the wind. This level of performance can be a dramatic improvement over the Strehls achievable with a conventional least squares reconstructor.