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Proceedings Paper

Image processing methods for exoplanets detection and characterization in starshade observations
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Paper Abstract

A starshade is a promising instrument for the direct imaging and characterization of exoplanets. However, even with a starshade, exoplanets are difficult to detect because detector noise, starshade defects, and misalignment (dynamics of the starshade system) degrade the signal to noise ratio (SNR) and contrast. No image processing methods have been specialized for images produced by a starshade system (simply referred as starshade images later). In this paper, we present a method, based on the generalized likelihood ratio test (GLRT), to detect and characterize planets from a single starshade image or multiple starshade images. This paper describes the GLRT model and its preliminary results for simulated images with starshade shape error, dynamics, detector noise and starshade rotation considered. The planets are detected with low false alarm rate, and planet positions are accurately estimated, and planet intensities are reasonably estimated. Thus, it demonstrates great potential as an acute and robust detection method for starshade images

Paper Details

Date Published: 16 July 2018
PDF: 13 pages
Proc. SPIE 10698, Space Telescopes and Instrumentation 2018: Optical, Infrared, and Millimeter Wave, 106985K (16 July 2018); doi: 10.1117/12.2312091
Show Author Affiliations
Mengya (Mia) Hu, Princeton Univ. (United States)
Anthony Harness, Princeton Univ. (United States)
N. Jeremy Kasdin, Princeton Univ. (United States)


Published in SPIE Proceedings Vol. 10698:
Space Telescopes and Instrumentation 2018: Optical, Infrared, and Millimeter Wave
Makenzie Lystrup; Howard A. MacEwen; Giovanni G. Fazio; Natalie Batalha; Nicholas Siegler; Edward C. Tong, Editor(s)

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