4,053 research outputs found
SPICES: Spectro-Polarimetric Imaging and Characterization of Exoplanetary Systems
SPICES (Spectro-Polarimetric Imaging and Characterization of Exoplanetary
Systems) is a five-year M-class mission proposed to ESA Cosmic Vision. Its
purpose is to image and characterize long-period extrasolar planets and
circumstellar disks in the visible (450 - 900 nm) at a spectral resolution of
about 40 using both spectroscopy and polarimetry. By 2020/22, present and
near-term instruments will have found several tens of planets that SPICES will
be able to observe and study in detail. Equipped with a 1.5 m telescope, SPICES
can preferentially access exoplanets located at several AUs (0.5-10 AU) from
nearby stars (25 pc) with masses ranging from a few Jupiter masses to Super
Earths (2 Earth radii, 10 M) as well as circumstellar
disks as faint as a few times the zodiacal light in the Solar System
SPHERE: the exoplanet imager for the Very Large Telescope
Observations of circumstellar environments to look for the direct signal of
exoplanets and the scattered light from disks has significant instrumental
implications. In the past 15 years, major developments in adaptive optics,
coronagraphy, optical manufacturing, wavefront sensing and data processing,
together with a consistent global system analysis have enabled a new generation
of high-contrast imagers and spectrographs on large ground-based telescopes
with much better performance. One of the most productive is the
Spectro-Polarimetic High contrast imager for Exoplanets REsearch (SPHERE)
designed and built for the ESO Very Large Telescope (VLT) in Chile. SPHERE
includes an extreme adaptive optics system, a highly stable common path
interface, several types of coronagraphs and three science instruments. Two of
them, the Integral Field Spectrograph (IFS) and the Infra-Red Dual-band Imager
and Spectrograph (IRDIS), are designed to efficiently cover the near-infrared
(NIR) range in a single observation for efficient young planet search. The
third one, ZIMPOL, is designed for visible (VIR) polarimetric observation to
look for the reflected light of exoplanets and the light scattered by debris
disks. This suite of three science instruments enables to study circumstellar
environments at unprecedented angular resolution both in the visible and the
near-infrared. In this work, we present the complete instrument and its on-sky
performance after 4 years of operations at the VLT.Comment: Final version accepted for publication in A&
The Lyot Project Direct Imaging Survey of Substellar Companions: Statistical Analysis and Information from Nondetections
The Lyot project used an optimized Lyot coronagraph with Extreme Adaptive
Optics at the 3.63m Advanced Electro-Optical System telescope (AEOS) to observe
86 stars from 2004 to 2007. In this paper we give an overview of the survey
results and a statistical analysis of the observed nondetections around 58 of
our targets to place constraints on the population of substellar companions to
nearby stars. The observations did not detect any companion in the substellar
regime. Since null results can be as important as detections, we analyzed each
observation to determine the characteristics of the companions that can be
ruled out. For this purpose we use a Monte Carlo approach to produce artificial
companions, and determine their detectability by comparison with the
sensitivity curve for each star. All the non-detection results are combined
using a Bayesian approach and we provide upper limits on the population of
giant exoplanets and brown dwarfs for this sample of stars. Our nondetections
confirm the rarity of brown dwarfs around solar-like stars and we constrain the
frequency of massive substellar companions (M>40Mjup) at orbital separation
between and 10 and 50 AU to be <20%.Comment: 32 pages, 11 figures, 2 tables. Published in the Astrophysical
Journa
Coherency Matrix Decomposition-Based Polarimetric Persistent Scatterer Interferometry
© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.The rationale of polarimetric optimization techniques is to enhance the phase quality of the interferograms by combining adequately the different polarization channels available to produce an improved one. Different approaches have been proposed for polarimetric persistent scatterer interferometry (PolPSI). They range from the simple and computationally efficient BEST, where, for each pixel, the polarimetric channel with the best response in terms of phase quality is selected, to those with high-computational burden like the equal scattering mechanism (ESM) and the suboptimum scattering mechanism (SOM). BEST is fast and simple, but it does not fully exploit the potentials of polarimetry. On the other side, ESM explores all the space of solutions and finds the optimal one but with a very high-computational burden. A new PolPSI algorithm, named coherency matrix decomposition-based PolPSI (CMD-PolPSI), is proposed to achieve a compromise between phase optimization and computational cost. Its core idea is utilizing the polarimetric synthetic aperture radar (PolSAR) coherency matrix decomposition to determine the optimal polarization channel for each pixel. Three different PolSAR image sets of both full- (Barcelona) and dual-polarization (Murcia and Mexico City) are used to evaluate the performance of CMD-PolPSI. The results show that CMD-PolPSI presents better optimization results than the BEST method by using either or temporal mean coherence as phase quality metrics. Compared with the ESM algorithm, CMD-PolPSI is 255 times faster but its performance is not optimal. The influence of the number of available polarization channels and pixel's resolutions on the CMD-PolPSI performance is also discussed.Peer ReviewedPostprint (author's final draft
On the use of the l(2)-norm for texture analysis of polarimetric SAR data
In this paper, the use of the l2-norm, or Span, of the scattering vectors is suggested for texture analysis of polarimetric synthetic aperture radar (SAR) data, with the benefits that we need neither an analysis of the polarimetric channels separately nor a filtering of the data to analyze the statistics. Based on the product model, the distribution of the l2-norm is studied. Closed expressions of the probability density functions under the assumptions of several texture distributions are provided. To utilize the statistical properties of the l2-norm, quantities including normalized moments and log-cumulants are derived, along with corresponding estimators and estimation variances. Results on both simulated and real SAR data show that the use of statistics based on the l2-norm brings advantages in several aspects with respect to the normalized intensity moments and matrix variate log-cumulants.Peer ReviewedPostprint (published version
Velocity Dealiased Spectral Estimators of Range Migrating Targets using a Single Low-PRF Wideband Waveform
Wideband radars are promising systems that may provide numerous advantages, like simultaneous detection of slow and fast moving targets, high range-velocity resolution classification, and electronic countermeasures. Unfortunately, classical processing algorithms are challenged by the range-migration phenomenon that occurs then for fast moving targets. We
propose a new approach where the range migration is used rather as an asset to retrieve information about target velocitiesand, subsequently, to obtain a velocity dealiased mode. More specifically three new complex spectral estimators are devised in case of a single low-PRF (pulse repetition frequency) wideband waveform. The new estimation schemes enable one to decrease the
level of sidelobes that arise at ambiguous velocities and, thus, to enhance the discrimination capability of the radar. Synthetic data and experimental data are used to assess the performance of the proposed estimators
Bayesian statistical analysis of ground-clutter for the relative calibration of dual polarization weather radars
A new data processing methodology, based on the statistical analysis of ground-clutter echoes and aimed at investigating the stability of the weather radar relative calibration, is presented. A Bayesian classification scheme has been used to identify meteorological and/or ground-clutter echoes. The outcome is evaluated on a training dataset using statistical score indexes through the comparison with a deterministic clutter map. After discriminating the ground clutter areas, we have focused on the spatial analysis of robust and stable returns by using an automated region-merging algorithm. The temporal series of the ground-clutter statistical parameters, extracted from the spatial analysis and expressed in terms of percentile and mean values, have been used to estimate the relative clutter calibration and its uncertainty for both co-polar and differential reflectivity. The proposed methodology has been applied to a dataset collected by a C-band weather radar in southern Italy
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