989 research outputs found
Calibration Challenges for Future Radio Telescopes
Instruments for radio astronomical observations have come a long way. While
the first telescopes were based on very large dishes and 2-antenna
interferometers, current instruments consist of dozens of steerable dishes,
whereas future instruments will be even larger distributed sensor arrays with a
hierarchy of phased array elements. For such arrays to provide meaningful
output (images), accurate calibration is of critical importance. Calibration
must solve for the unknown antenna gains and phases, as well as the unknown
atmospheric and ionospheric disturbances. Future telescopes will have a large
number of elements and a large field of view. In this case the parameters are
strongly direction dependent, resulting in a large number of unknown parameters
even if appropriately constrained physical or phenomenological descriptions are
used. This makes calibration a daunting parameter estimation task, that is
reviewed from a signal processing perspective in this article.Comment: 12 pages, 7 figures, 20 subfigures The title quoted in the meta-data
is the title after release / final editing
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Antibioticagebruik in de veehouderij wordt door de buitenwereld kritisch gevolgd
Retrieval of canopy component temperatures through Bayesian inversion of directional thermal measurements
Evapotranspiration is usually estimated in remote sensing from single temperature value representing both soil and vegetation. This surface temperature is an aggregate over multiple canopy components. The temperature of the individual components can differ significantly, introducing errors in the evapotranspiration estimations. The temperature aggregate has a high level of directionality. An inversion method is presented in this paper to retrieve four canopy component temperatures from directional brightness temperatures. The Bayesian method uses both a priori information and sensor characteristics to solve the ill-posed inversion problem. The method is tested using two case studies: 1) a sensitivity analysis, using a large forward simulated dataset, and 2) in a reality study, using two datasets of two field campaigns. The results of the sensitivity analysis show that the Bayesian approach is able to retrieve the four component temperatures from directional brightness temperatures with good success rates using multi-directional sensors (SrspectraËś0.3, SrgonioËś0.3, and SrAATSRËś0.5), and no improvement using mono-angular sensors (SrËś1). The results of the experimental study show that the approach gives good results for high LAI values (RMSEgrass=0.50 K, RMSEwheat=0.29 K, RMSEsugar beet=0.75 K, RMSEbarley=0.67 K); but for low LAI values the results were unsatisfactory (RMSEyoung maize=2.85 K). This discrepancy was found to originate from the presence of the metallic construction of the setup. As these disturbances, were only present for two crops and were not present in the sensitivity analysis, which had a low LAI, it is concluded that using masked thermal images will eliminate this discrepanc
Optimum vegetation characteristics, assimilation, and transpiration during a dry season. 2. Model evaluation
BRDFs acquired by directional radiative measurements during EAGLE and AGRISAR
Radiation is the driving force for all processes and interactions between earth surface and atmosphere. The amount of
measured radiation reflected by vegetation depends on its structure, the viewing angle and the solar angle. This angular
dependence is usually expressed in the Bi-directional Reflectance Distribution Function (BRDF). This BRDF is not
only different for different types of vegetation, but also different for different stages of the growth. The BRDF therefore
has to be measured at ground level before any satellite imagery can be used the calculate surface-atmosphere
interaction. The objective of this research is to acquire the BRDFs for agricultural crop types.
A goniometric system is used to acquire the BRDFs. This is a mechanical device capable of a complete hemispherical
rotation. The radiative directional measurements are performed with different sensors that can be attached to this
system. The BRDFs are calculated from the measured radiation.
In the periods 10 June - 18 June 2006 and 2 July - 10 July 2006 directional radiative measurements were performed at
three sites: Speulderbos site, in the Netherlands, the Cabauw site, in the Netherlands, and an agricultural test site in
Goermin, Germany. The measurements were performed over eight different crops: forest, grass, pine tree, corn, wheat,
sugar beat and barley. The sensors covered the spectrum from the optical to the thermal domain. The measured radiance
is used to calculate the BRDFs or directional thermal signature.
This contribution describes the measurements and calculation of the BRDFs of forest, grassland, young corn, mature
corn, wheat, sugar beat and barley during the EAGLE2006 and AGRISAR 2006 fieldcampaigns. Optical BRDF have
been acquired for all crops except barley. Thermal angular signatures are acquired for all the crop
Demonstration of an ultra-short polarization converter in InGaAsP/InP membrane
An ultra-short (<10 µm length) polarization converter is demonstrated in an indium phosphide based membrane. Measurements show very high polarization conversion efficiency (97 %) with low excess losses (~ 1 dB)
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