Wavefront correction with Kalman filtering for the WFIRST-AFTA coronagraph instrument

Abstract

The only way to characterize most exoplanets spectrally is via direct imaging. For example, the Coronagraph Instrument (CGI) on the proposed Wide-Field Infrared Survey Telescope-Astrophysics Focused Telescope Assets (WFIRST-AFTA) mission plans to image and characterize several cool gas giants around nearby stars. The integration time on these faint exoplanets will be many hours to days. A crucial assumption for mission planning is that the time required to dig a dark hole (a region of high star-to-planet contrast) with deformable mirrors is small compared to science integration time. The science camera must be used as the wavefront sensor to avoid non-common path aberrations, but this approach can be quite time intensive. Several estimation images are required to build an estimate of the starlight electric field before it can be partially corrected, and this process is repeated iteratively until high contrast is reached. Here we present simulated results of batch process and recursive wavefront estimation schemes. In particular, we test a Kalman filter and an iterative extended Kalman filter (IEKF) to reduce the total exposure time and improve the robustness of wavefront correction for the WFIRST-AFTA CGI. An IEKF or other nonlinear filter also allows recursive, real-time estimation of sources incoherent with the star, such as exoplanets and disks, and may therefore reduce detection uncertainty.