Recursive starlight and bias estimation for high-contrast imaging with an extended Kalman filter

A. J. Eldorado Riggs; N. Jeremy Kasdin; Tyler D. Groff

doi:10.1117/1.JATIS.2.1.011017

5 February 2016 Recursive starlight and bias estimation for high-contrast imaging with an extended Kalman filter

A. J. Eldorado Riggs, N. Jeremy Kasdin, Tyler D. Groff

Journal of Astronomical Telescopes, Instruments, and Systems, Vol. 2, Issue 1, 011017 (February 2016). https://doi.org/10.1117/1.JATIS.2.1.011017

Abstract

For imaging faint exoplanets and disks, a coronagraph-equipped observatory needs focal plane wavefront correction to recover high contrast. The most efficient correction methods iteratively estimate the stellar electric field and suppress it with active optics. The estimation requires several images from the science camera per iteration. To maximize the science yield, it is desirable both to have fast wavefront correction and to utilize all the correction images for science target detection. Exoplanets and disks are incoherent with their stars, so a nonlinear estimator is required to estimate both the incoherent intensity and the stellar electric field. Such techniques assume a high level of stability found only on space-based observatories and possibly ground-based telescopes with extreme adaptive optics. In this paper, we implement a nonlinear estimator, the iterated extended Kalman filter (IEKF), to enable fast wavefront correction and a recursive, nearly-optimal estimate of the incoherent light. In Princeton’s High Contrast Imaging Laboratory, we demonstrate that the IEKF allows wavefront correction at least as fast as with a Kalman filter and provides the most accurate detection of a faint companion. The nonlinear IEKF formalism allows us to pursue other strategies such as parameter estimation to improve wavefront correction.

CC BY: © The Authors. Published by SPIE under a Creative Commons Attribution 4.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

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A. J. Eldorado Riggs, N. Jeremy Kasdin, and Tyler D. Groff "Recursive starlight and bias estimation for high-contrast imaging with an extended Kalman filter," Journal of Astronomical Telescopes, Instruments, and Systems 2(1), 011017 (5 February 2016). https://doi.org/10.1117/1.JATIS.2.1.011017

Published: 5 February 2016

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