Design and Performance Analysis of Adaptive Optical Telescopes Using Laser Guide Stars

Chester S. Gardner, Byron M. Welsh, Laird A. Thompson

Research output: Contribution to journalArticlepeer-review


Atmospheric turbulence severely limits the resolution of ground-based astronomical telescopes. In good seeing conditions at the best observatory sites, resolution at visible wavelengths is typically limited to ~ 1 s of arc. During the past 15 years adaptive optical systems using electrically deformable mirrors have been developed to compensate for turbulence effects. Unfortunately, these systems require bright reference sources adjacent to the object of interest and can be used only to observe the brightest stars. Artificial guide stars suitable for controlling an adaptive imaging system can be created in the upper atmosphere by using a laser to excite either Rayleigh backscattering in the stratosphere or resonance backscattering in the mesospheric sodium layer. The design requirements of a laser-guided adaptive telescope, as well as the expected imaging performance, are discussed in detail in this paper. We show that a 2-m ground-based laser-guided telescope can achieve imaging performance levels at visible wavelengths nearly matching the theoretical imaging performance of the Hubble Space Telescope (HST)- The required lasers can be either bought off the shelf or built with today's technology. The laser power requirement for the Rayleigh guide star approach is on the order of 82 W for zenith viewing when the atmospheric seeing cell diameter is 20 cm. For the same conditions the laser power requirement for the Na guide star approach is on the order of 14 W. Both systems will achieve near diffraction limited imaging with a Strehl ratio of 0.67 and an angular resolution of approximately 0.07 arc-sec for an observation wavelength of 0.5 μn.

Original languageEnglish (US)
Pages (from-to)1721-1743
Number of pages23
JournalProceedings of the IEEE
Issue number11
StatePublished - Nov 1990

ASJC Scopus subject areas

  • General Computer Science
  • Electrical and Electronic Engineering


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