Multi-Channel Planet Detection Algorithm for Angular Differential Imaging

Mugnier, Laurent M.; Sauvage, Jean-François; Fusco, Thierry; Rousset, G.

doi:10.1364/aopt.2007.atua4

Cited by 6 publications

(2 citation statements)

References 3 publications

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“…• first, subtract two by two the angular images to remove the star signal (the speckles) and produce angular differential data; second, estimate the planet [20,21] only from this new angular differential data series.…”

Section: Principle Of the Proposed Methodsmentioning

confidence: 99%

Optimal method for exoplanet detection by angular differential imaging

Mugnier¹,

Cornia²,

Sauvage³

et al. 2009

J. Opt. Soc. Am. A

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We propose a novel method for the efficient direct detection of exoplanets from the ground using angular differential imaging. The method combines images appropriately, then uses the combined images jointly in a maximum-likelihood framework to estimate the position and intensity of potential planets orbiting the observed star. It takes into account the mixture of photon and detector noises and a positivity constraint on the planet's intensity. A reasonable detection criterion is also proposed based on the computation of the noise propagation from the images to the estimated intensity of the potential planet. The implementation of this method is tested on simulated data that take into account static aberrations before and after the coronagraph, residual turbulence after adaptive optics correction, and noise.

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Section: Principle Of the Proposed Methodsmentioning

confidence: 99%

Optimal method for exoplanet detection by angular differential imaging

Mugnier¹,

Cornia²,

Sauvage³

et al. 2009

J. Opt. Soc. Am. A

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show abstract

“…The diffraction pattern of the static aberration of the instrument being similar to the unresolved exoplanet profile, detection algorithm proposed in the literature tries to discriminate the planet from the background by the detection of its motion. Previous work tries to suppress and stabilize the background using differential processing of successive images [2,3].…”

Section: Introductionmentioning

confidence: 99%

Detection and performance analysis for a moving point source in speckle noise, application to exoplanet detection by direct imaging

Smith

Ferrari

Carbillet

2008

2008 IEEE International Conference on Acoustics, Speech and Signal Processing

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With the current development of astronomical instruments able to detect the direct light of exoplanets, such as the Very Large Telescope instrument SPHERE, statistical tools need to be developed in order to make precise detection and estimation assessments. We propose a detection algorithm that delivers an estimation of the position and the intensity of the potentially detected exoplanet. Because of the numerical constraints on the signal processing task, the detectorestimator is based on a simplified Gaussian model where we use a field-rotation effect as the main discriminating criterium between the planet and the speckles. However, for a given threshold on the statistics test, the Probability of False Alarm (PFA) and the Probability of Detection (PD) need to be accurate. For that purpose we use a more realistic model and the saddlepoint approximation to compute the PFA and PD. The performance of the approximation is evaluated on a 1D data model.

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