Development of multi time-step tomographic reconstruction with RAVEN

Yoshito Ono, Masayuki Akiyama, Shin Oya, Olivier Ladière

Research output: Contribution to conferencePaperpeer-review


In this paper, we present a tomographic reconstruction method to reduce a tomographic error, multi time-step reconstruction, for a wide-field adaptive optics (WFAO). Based on the frozen flow assumption, we can compute the time evolution of measurements from wave-front sensors (WFS) at previous time-steps with using wind information. Our idea is to reduce the tomographic error by using the measurements at both the current and previous time-steps simultaneously. We also develop a method to estimate wind speed and direction at each altitude from temporal correlations of phase distortion pattern reconstructed by a classical tomography. We evaluate the performance of the method by a laboratory experiment with the RAVEN, a multi-object adaptive optics (MOAO) technical and science demonstrator. In the laboratory experiment, our wind estimation method can estimate wind speeds and directions of multiple layers. By the multi time-step reconstruction method, the ensquared energy in a 140 mas box increases about 3-5% compared with a classical tomographic reconstruction.

Original languageEnglish
Publication statusPublished - 2015
Event4th Adaptive Optics for Extremely Large Telescopes, AO4ELT 2015 - Lake Arrowhead, United States
Duration: 2015 Oct 262015 Oct 30


Other4th Adaptive Optics for Extremely Large Telescopes, AO4ELT 2015
Country/TerritoryUnited States
CityLake Arrowhead

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Instrumentation
  • Electronic, Optical and Magnetic Materials
  • Space and Planetary Science
  • Astronomy and Astrophysics
  • Mechanical Engineering


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