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Applied Optics

Applied Optics

APPLICATIONS-CENTERED RESEARCH IN OPTICS

  • Vol. 33, Iss. 27 — Sep. 20, 1994
  • pp: 6533–6546

Phase-diversity wave-front sensor for imaging systems

Richard L. Kendrick, D. S. Acton, and A. L. Duncan  »View Author Affiliations


Applied Optics, Vol. 33, Issue 27, pp. 6533-6546 (1994)
http://dx.doi.org/10.1364/AO.33.006533


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Abstract

A phase-diversity wave-front sensor has been developed and tested at the Lockheed Palo Alto Research Labs (LPARL). The sensor consists of two CCD-array focal planes that record the best-focus image of an adaptive imaging system and an image that is defocused. This information is used to generate an object-independent function that is the input to a LPARL-developed neural network algorithm known as the General Regression Neural Network (GRNN). The GRNN algorithm calculates the wave-front errors that are present in the adaptive optics system. A control algorithm uses the calculated values to correct the errors in the optical system. Simulation studies and closed-loop experimental results are presented.

© 1994 Optical Society of America

History
Original Manuscript: September 27, 1993
Revised Manuscript: March 29, 1994
Published: September 20, 1994

Citation
Richard L. Kendrick, D. S. Acton, and A. L. Duncan, "Phase-diversity wave-front sensor for imaging systems," Appl. Opt. 33, 6533-6546 (1994)
http://www.opticsinfobase.org/ao/abstract.cfm?URI=ao-33-27-6533

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