Recursive Starlight and Bias Estimation for High-Contrast Imaging with an Extended Kalman Filter
A J Eldorado Riggs, N. Jeremy Kasdin, Tyler D. Groff

TL;DR
This paper introduces a recursive nonlinear estimation method using an iterated extended Kalman filter for high-contrast imaging, enabling faster wavefront correction and improved detection of faint exoplanets and disks.
Contribution
The paper implements and demonstrates the effectiveness of the iterated extended Kalman filter for real-time wavefront correction and incoherent light estimation in high-contrast imaging.
Findings
IEKF enables wavefront correction at speeds comparable to linear Kalman filters.
IEKF provides more accurate detection of faint companions.
The method is effective in laboratory settings for high-contrast imaging.
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…
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