Planet Detection Algorithms for the Terrestrial Planet Finder-C

Astronomy and Astrophysics – Astronomy

Scientific paper

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Scientific paper

Critical to mission planning for the terrestrial planet finder coronagraph (TPF-C) is the ability to estimate integration times for planet detection. This detection is complicated by the presence of background noise due to local and exo-zodiacal dust, by residual speckle due optical errors, and by the dependence of the PSF shape on the specific coronagraph. In this paper we examine in detail the use of PSF fitting (matched filtering) for planet detection, derive probabilistic bounds for the signal-to-noise ratio by balancing missed detection and false alarm rates, and demonstrate that this is close to the optimal linear detection technique. We then compare to a Bayesian detection approach and show that for very low background the Bayesian method offers integration time improvements, but rapidly approaches the PSF fitting result for reasonable levels of background noise. We confirm via monte-carlo simulations. This work was supported under a grant from the Jet Propulsion Laboratory and by a fellowship from the Institut National de Recherche en Informatique et Automatique (INRIA).

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