Speckle-metric-optimization-based adaptive optics for laser beam projection and coherent beam combining.

Maximization of a projected laser beam's power density at a remotely located extended object (speckle target) can be achieved by using an adaptive optics (AO) technique based on sensing and optimization of the target-return speckle field's statistical characteristics, referred to here as speckle metrics (SM). SM AO was demonstrated in a target-in-the-loop coherent beam combining experiment using a bistatic laser beam projection system composed of a coherent fiber-array transmitter and a power-in-the-bucket receiver. SM sensing utilized a 50 MHz rate dithering of the projected beam that provided a stair-mode approximation of the outgoing combined beam's wavefront tip and tilt with subaperture piston phases. Fiber-integrated phase shifters were used for both the dithering and SM optimization with stochastic parallel gradient descent control.

Experimental demonstration of coherent beam combining over a 7 km propagation path.

We demonstrate coherent combining (phase locking) of seven laser beams emerging from an adaptive fiber-collimator array over a 7 km atmospheric propagation path using a target-in-the-loop (TIL) setting. Adaptive control of the piston and the tip and tilt wavefront phase at each fiber-collimator subaperture resulted in automatic focusing of the combined beam onto an unresolved retroreflector target (corner cube) with precompensation of quasi-static and atmospheric turbulence-induced phase aberrations. Both phase locking (piston) and tip-tilt control were performed by maximizing the target-return optical power using iterative stochastic parallel gradient descent (SPGD) techniques. The performance of TIL coherent beam combining and atmospheric mitigation was significantly increased by using an SPGD control variation that accounts for the round-trip propagation delay (delayed SPGD).

Deep turbulence effects compensation experiments with a cascaded adaptive optics system using a 3.63 m telescope.

Compensation of extended (deep) turbulence effects is one of the most challenging problems in adaptive optics (AO). In the AO approach described, the deep turbulence wave propagation regime was achieved by imaging stars at low elevation angles when image quality improvement with conventional AO was poor. These experiments were conducted at the U.S. Air Force Maui Optical and Supercomputing Site (AMOS) by using the 3.63 m telescope located on Haleakala, Maui. To enhance compensation performance we used a cascaded AO system composed of a conventional AO system based on a Shack-Hartmann wavefront sensor and a deformable mirror with 941 actuators, and an AO system based on stochastic parallel gradient descent optimization with four deformable mirrors (75 control channels). This first-time field demonstration of a cascaded AO system achieved considerably improved performance of wavefront phase aberration compensation. Image quality was improved in a repeatable way in the presence of stressing atmospheric conditions obtained by using stars at elevation angles as low as 15 degrees.

Adaptive wavefront control with asynchronous stochastic parallel gradient descent clusters.

A scalable adaptive optics (AO) control system architecture composed of asynchronous control clusters based on the stochastic parallel gradient descent (SPGD) optimization technique is discussed. It is shown that subdivision of the control channels into asynchronous SPGD clusters improves the AO system performance by better utilizing individual and/or group characteristics of adaptive system components. Results of numerical simulations are presented for two different adaptive receiver systems based on asynchronous SPGD clusters-one with a single deformable mirror with Zernike response functions and a second with tip-tilt and segmented wavefront correctors. We also discuss adaptive wavefront control based on asynchronous parallel optimization of several local performance metrics-a control architecture referred to as distributed adaptive optics (DAO). Analysis of the DAO system architecture demonstrated the potential for significant increase of the adaptation process convergence rate that occurs due to partial decoupling of the system control clusters optimizing individual performance metrics.