The Experts below are selected from a list of 135078 Experts worldwide ranked by ideXlab platform
Eric Pottier - One of the best experts on this subject based on the ideXlab platform.
-
Matching-pursuit-based analysis of moving objects in polarimetric SAR images
IEEE Geoscience and Remote Sensing Letters, 2008Co-Authors: Paul Leducq, Laurent Ferro-Famil, Eric PottierAbstract:This letter deals with the analysis of moving and nonstationary objects in already focused synthetic aperture radar (SAR) images. A method based on the matching pursuit (MP) algorithm is proposed to decompose the SAR signal into a set of atoms. A model of a moving object response with frequency- and angle-dependent reflectivity is introduced to design the MP atoms. Each selected atom is associated to a scatterer of the scene and is Parameterized by relevant Physical descriptors, leading to a multidimensional model of the object. The efficiency of this technique is demonstrated in terms of SAR response refocusing and Physical Parameter map derivation, using a polarimetric SAR image of a moving object lying in a natural background.
-
Physical Parameter extraction over urban areas using L-band POLSAR data and interferometric baseline diversity
International Geoscience and Remote Sensing Symposium (IGARSS), 2007Co-Authors: Stefan Sauer, Laurent Ferro-Famil, Andreas Reigber, Eric PottierAbstract:Estimating the number of backscattering sources is an important issue in analyzing multibaseline interferometric SAR data. This paper extends model order selection algorithms to process polarimetric multibaseline InSAR observations. These methods are applied to urban environments using fully polarimetric dual-baseline InSAR data of Dresden city acquired by DLR's E-SAR system. Experimental results for single polarization and polarimetric set-ups are presented and discussed.
Yan Mei Chen - One of the best experts on this subject based on the ideXlab platform.
-
evolution of the most massive galaxies to z 0 6 i a new method for Physical Parameter estimation
Monthly Notices of the Royal Astronomical Society, 2012Co-Authors: Yan Mei Chen, Guinevere Kauffmann, Christy Tremonti, Simon White, Timothy M Heckman, Katarina Kovac, Kevin Bundy, John Chisholm, Claudia MarastonAbstract:We use principal component analysis (PCA) to estimate stellar masses, mean stellar ages, star formation histories (SFHs), dust extinctions and stellar velocity dispersions for a set of ∼290 000 galaxies with stellar masses greater than 1011 M⊙ and redshifts in the range 0.4 < z < 0.7 from the Baryon Oscillation Spectroscopic Survey (BOSS). We find that the fraction of galaxies with active star formation first declines with increasing stellar mass, but then flattens above a stellar mass of 1011.5 M⊙ at z∼ 0.6. This is in striking contrast to z∼ 0.1, where the fraction of galaxies with active star formation declines monotonically with stellar mass. At stellar masses of 1012 M⊙, therefore, the evolution in the fraction of star-forming galaxies from z∼ 0.6 to the present day reaches a factor of ∼10. When we stack the spectra of the most massive, star-forming galaxies at z∼ 0.6, we find that half of their [O iii] emission is produced by active galactic nuclei. The black holes in these galaxies are accreting on average at ∼0.01 the Eddington rate. To obtain these results, we use the stellar population synthesis models of Bruzual & Charlot to generate a library of model spectra with a broad range of SFHs, metallicities, dust extinctions and stellar velocity dispersions. The PCA is run on this library to identify its principal components over the rest-frame wavelength range 3700–5500 A. We demonstrate that linear combinations of these components can recover information equivalent to traditional spectral indices such as the 4000-A break strength and HδA, with greatly improved signal-to-noise ratio (S/N). In addition, the method is able to recover Physical Parameters such as stellar mass-to-light ratio, mean stellar age, velocity dispersion and dust extinction from the relatively low S/N BOSS spectra. We examine in detail the sensitivity of our stellar mass estimates to the input Parameters in our model library, showing that almost all changes result in systematic differences in logM* of 0.1 dex or less. The biggest differences are obtained when using different population synthesis models – stellar masses derived using Maraston et al. models are systematically smaller by up to 0.12 dex at young ages.
-
evolution of the most massive galaxies to z 0 6 i a new method for Physical Parameter estimation
arXiv: Astrophysics of Galaxies, 2011Co-Authors: Yan Mei Chen, Guinevere Kauffmann, Christy Tremonti, Simon White, Timothy M Heckman, Katarina Kovac, Kevin Bundy, John Chisholm, Claudia Maraston, Donald P SchneiderAbstract:We use principal component analysis (PCA) to estimate stellar masses, mean stellar ages, star formation histories (SFHs), dust extinctions and stellar velocity dispersions for ~290,000 galaxies with stellar masses greater than $10^{11}Msun and redshifts in the range 0.4
Nemai Chandra Karmakar - One of the best experts on this subject based on the ideXlab platform.
-
The Realization of Chipless RFID Resonator for Multiple Physical Parameter Sensing
IEEE Internet of Things Journal, 2019Co-Authors: Tharindu Athauda, Nemai Chandra KarmakarAbstract:We present the design of asymmetric circular split ring resonator as a chipless radio frequency identification (RFID) sensor tag design that can be deployed to measure multiple Physical Parameters wirelessly in ultrawideband frequencies. Secondarily, the proposed tag design can extend to be used as a chipless RFID tag with actual data encoded for product identification purposes. The proposed resonator design consists of four complementary split circular rings. Each gap between the rings acts as a capacitive sensor which is optimized to have a resonance with a high-quality factor. Each resonance can be considered as a sensor to deploy smart materials that are sensitive to different environmental Physical Parameters, which can be operated in wireless conditions. The fabricated chipless RFID sensor provides a higher ${Q}$ factor, aligned with the optimized simulation model. Chipless RFID sensors are comparatively low-cost, but they provide enormous design flexibility in diversified applications. The proposed design holds a great promise for sensing multiple Physical Parameters in a remote setting.
Kun Huang Chen - One of the best experts on this subject based on the ideXlab platform.
-
Measuring Physical Parameters with surface plasmon resonance heterodyne interferometry
Optik, 2009Co-Authors: Kun Huang Chen, Jing-heng ChenAbstract:If the incident angle of a light beam on the boundary surface between the thin metal film of a surface plasmon resonance (SPR) apparatus and a test medium is equal to or very near the resonant angle, then the phase difference between the p- and s-polarizations of the reflected light is related to the associated Physical Parameter. The phase difference can be measured accurately with heterodyne interferometry. If the relationship between the phase difference and the associated Physical Parameter is specified, then the associated Physical Parameter can be estimated from the phase difference data. This method has the benefits of both common-path interferometry and heterodyne interferometry, such as simple structure, high stability, high resolution, easy operation, and rapid real-time measurement.
-
Surface plasmon resonance heterodyne interferometry for measuring Physical Parameters
Optical Metrology in Production Engineering, 2004Co-Authors: Der-chin Su, Jing-heng Chen, Kun Huang ChenAbstract:A light beam is incident on the boundary surface between the thin metal film of a surface-plasmon-resonance (SPR) apparatus and the test medium. If the incident angle is equal or very near to the resonant angle, then the phase difference between p- and s- polarizations of the reflected light is related to the associated Physical Parameter. The phase difference can be measured accurately by the heterodyne interferometry. If the relation between the phase difference and the associated Physical Parameter is specified, the associated Physical Parameter can be estimated with the data of the phase difference. This method has the advantages of both common-path interferometry and heterodyne interferometry.
Claudia Maraston - One of the best experts on this subject based on the ideXlab platform.
-
evolution of the most massive galaxies to z 0 6 i a new method for Physical Parameter estimation
Monthly Notices of the Royal Astronomical Society, 2012Co-Authors: Yan Mei Chen, Guinevere Kauffmann, Christy Tremonti, Simon White, Timothy M Heckman, Katarina Kovac, Kevin Bundy, John Chisholm, Claudia MarastonAbstract:We use principal component analysis (PCA) to estimate stellar masses, mean stellar ages, star formation histories (SFHs), dust extinctions and stellar velocity dispersions for a set of ∼290 000 galaxies with stellar masses greater than 1011 M⊙ and redshifts in the range 0.4 < z < 0.7 from the Baryon Oscillation Spectroscopic Survey (BOSS). We find that the fraction of galaxies with active star formation first declines with increasing stellar mass, but then flattens above a stellar mass of 1011.5 M⊙ at z∼ 0.6. This is in striking contrast to z∼ 0.1, where the fraction of galaxies with active star formation declines monotonically with stellar mass. At stellar masses of 1012 M⊙, therefore, the evolution in the fraction of star-forming galaxies from z∼ 0.6 to the present day reaches a factor of ∼10. When we stack the spectra of the most massive, star-forming galaxies at z∼ 0.6, we find that half of their [O iii] emission is produced by active galactic nuclei. The black holes in these galaxies are accreting on average at ∼0.01 the Eddington rate. To obtain these results, we use the stellar population synthesis models of Bruzual & Charlot to generate a library of model spectra with a broad range of SFHs, metallicities, dust extinctions and stellar velocity dispersions. The PCA is run on this library to identify its principal components over the rest-frame wavelength range 3700–5500 A. We demonstrate that linear combinations of these components can recover information equivalent to traditional spectral indices such as the 4000-A break strength and HδA, with greatly improved signal-to-noise ratio (S/N). In addition, the method is able to recover Physical Parameters such as stellar mass-to-light ratio, mean stellar age, velocity dispersion and dust extinction from the relatively low S/N BOSS spectra. We examine in detail the sensitivity of our stellar mass estimates to the input Parameters in our model library, showing that almost all changes result in systematic differences in logM* of 0.1 dex or less. The biggest differences are obtained when using different population synthesis models – stellar masses derived using Maraston et al. models are systematically smaller by up to 0.12 dex at young ages.
-
evolution of the most massive galaxies to z 0 6 i a new method for Physical Parameter estimation
arXiv: Astrophysics of Galaxies, 2011Co-Authors: Yan Mei Chen, Guinevere Kauffmann, Christy Tremonti, Simon White, Timothy M Heckman, Katarina Kovac, Kevin Bundy, John Chisholm, Claudia Maraston, Donald P SchneiderAbstract:We use principal component analysis (PCA) to estimate stellar masses, mean stellar ages, star formation histories (SFHs), dust extinctions and stellar velocity dispersions for ~290,000 galaxies with stellar masses greater than $10^{11}Msun and redshifts in the range 0.4
