Remote phasing of the Multiple-Mirror Telescope with far-field optimization

Naresh C. Mehta; Clinton W. Allen

doi:10.1117/12.284224

18 September 1997 Remote phasing of the Multiple-Mirror Telescope with far-field optimization

Naresh C. Mehta, Clinton W. Allen

Proceedings Volume 3112, Telescope Control Systems II; (1997) https://doi.org/10.1117/12.284224
Event: Optical Science, Engineering and Instrumentation '97, 1997, San Diego, CA, United States

Abstract

In order to achieve diffraction-limited performance in a distributed aperture optical system such as the multiple mirror telescope, the elements must be optically phased to form a single aperture which can be a difficult task. In this paper, we report a novel, iterative adaptive control method, called far-field optimization, which employs the simplex algorithm to configure the elements of a distributed aperture telescope to optical alignment. Far-field optimization does not require the knowledge of the adaptive mirror surfaces, thus eliminating the need for a wavefront sensor, but uses a simple measure of the point-spread function (image-plane intensity). We present results of computer simulations to demonstrate the utility of far-field optimization to remotely align the six-element multiple mirror telescope in a few seconds, even in the presence of drifting atmospheric turbulence.

Citation Download Citation

Naresh C. Mehta and Clinton W. Allen "Remote phasing of the Multiple-Mirror Telescope with far-field optimization", Proc. SPIE 3112, Telescope Control Systems II, (18 September 1997); https://doi.org/10.1117/12.284224

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available