Navigation Performance Trades and Analysis for the Lunar GNSS Receiver Experiment (LuGRE)
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GRUAN, the GCOS Reference Upper Air Network, is an international reference observing network of sites measuring essential climate variables above Earth's surface, designed to fill an important gap in the current global observing system. GRUAN’s objectives are to (1) provide long-term, high-quality climate records, (2) constrain and calibrate data from more spatially comprehensive global observing systems (including satellites and current radiosonde networks), and (3) fully characterize the properties of the atmospheric column.
GRUAN, the Global Climate Observing System (GCOS) Reference Upper Air Network, is an international reference observing network of sites measuring essential climate variables above Earth's surface, designed to fill an important gap in the current global observing system. GRUAN’s objectives are to (1) provide long-term, high-quality climate records, (2) constrain and calibrate data from more spatially comprehensive global observing systems (including satellites and current radiosonde networks), and (3) fully characterize the properties of the atmospheric column.
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One of the world's two global navigation systems, the Global Positioning System (GPS), is already fully operational (April 1994) and the other, the Global Navigation Satellite System (GLONASS) will become operational by the end of 1995 or early 1996. Each will offer, independently of the other, precise location and time transfer continuously anywhere in the world and indeed in space itself. Many potential users, in particular the civil aviation community, are keenly interested in a joint GPS/GLONASS operation since it would offer substantial advantages in defining and maintaining the integrity of the navigation aid. Results are presented on the characterization of GPS/GLONASS time comparison using a 20-channel dual receiver developed and constructed at the University of Leeds, UK.
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The presentation outline includes University Corporation for Atmospheric Research (UCAR) and Jet Propulsion Laboratory (JPL) product comparisons, assimilating ground-based global positioning satellites (GPS) and COSMIC into JPL/University of Southern California (USC) Global Assimilative Ionospheric Model (GAIM), and JPL/USC GAIM validation. The discussion of comparisons examines Abel profiles and calibrated TEC. The JPL/USC GAIM validation uses Arecibo ISR, Jason-2 VTEC, and Abel profiles.
In February-March 2009 NASA JPL conducted an airborne field campaign using the Passive Active L-band System (PALS) and the Ku-band Polarimetric Scatterometer (PolSCAT) collecting measurements of brightness temperature and near surface wind speeds. Flights were conducted over a region of expected high-speed winds in the Atlantic Ocean, for the purposes of algorithm development for salinity retrievals. Wind speeds encountered were in the range of 5 to 25 m/s during the two weeks deployment. The NASA-Langley GPS delay-mapping receiver (DMR) was also flown to collect GPS signals reflected from the ocean surface and generate post-correlation power vs. delay measurements. This data was used to estimate ocean surface roughness and a strong correlation with brightness temperature was found. Initial results suggest that reflected GPS signals, using small low-power instruments, will provide an additional source of data for correcting brightness temperature measurements for the purpose of sea surface salinity retrievals.
The increased availability of radio occultation (RO) data offers the ability to detect and study turbulence in the Earth's atmosphere. An analysis of how RO data can be used to determine the strength and location of turbulent regions is presented. This includes the derivation of a model for the power spectrum of the log-amplitude and phase fluctuations of the permittivity (or index of refraction) field. The bulk of the paper is then concerned with the estimation of the model parameters. Parameter estimators are introduced and some of their statistical properties are studied. These estimators are then applied to simulated log-amplitude RO signals. This includes the analysis of global statistics derived from a large number of realizations, as well as case studies that illustrate various specific aspects of the problem. Improvements to the basic estimation methods are discussed, and their beneficial properties are illustrated. The estimation techniques are then applied to real occultation data. Only two cases are presented, but they illustrate some of the salient features inherent in real data.
Outline of presentation: Why do we use the rate of TEC index (ROTI) instead of the standard s4 and sigma-phi indices? What are the differences between S4, sigma-phi and ROTI? Examples of ROTI measurements and Development status and plan.