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Volumetric Wavefront Sensing for the Characterization of Distributed-Volume Aberrations

Award Information
Agency: Department of Defense
Branch: Air Force
Contract: FA9451-18-P-0259
Agency Tracking Number: F18A-006-0175
Amount: $149,993.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: AF18A-T006
Solicitation Number: 2018.0
Timeline
Solicitation Year: 2018
Award Year: 2018
Award Start Date (Proposal Award Date): 2018-08-09
Award End Date (Contract End Date): 2019-08-09
Small Business Information
1501 S. Sunset St.
Longmont, CO 80501
United States
DUNS: 079204036
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Troy Rhoadarmer
 (720) 684-8069
 troy.rhoadarmer@guidestaroptical.com
Business Contact
 Aaron Buckner
Phone: (310) 435-5492
Email: aaron.buckner@guidestaroptical.com
Research Institution
 University of California, Los Angeles
 Brian Roe
 
UCLA Mechanical and Aerospace Engineering Department BOX 951597, 48-121 E4
Los Angeles, CA 90095
United States

 (310) 983-3408
 Nonprofit college or university
Abstract

Modern Directed Energy (DE) missions require target engagements at low elevation angles and long ranges.These engagement geometries require propagation through distributed-volume turbulence. To correct for distributed-volume turbulence effects, an estimation of the turbulence along the propagation path is required. Correcting for these image aberrations will improve the quality of the target image, allowing for faster and more accurate target identification. Guidestar Optical Systems, Inc. proposes to team with the University of California, Los Angeles (UCLA) to develop a holographic imaging system that generates a volumetric estimate of the distributed turbulence phase aberrations.Our team will exploit methods developed recently at UCLA for adaptive identification, prediction, and control of optical wavefronts. These techniques will be integrated with novel methods for digital holography and image sharpening approaches in ways that are optimal for real time predictive dynamic schemes.The research will employ control-theoretic methods to analyze and optimize the nonlinear interaction between wavefront prediction and image sharpening, with the ultimate objective of optimizing the convergence of the coupled wavefront prediction and image sharpening and minimizing the effects of sensor noise, speckle, and other disturbances.

* Information listed above is at the time of submission. *

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