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Computer Modeling for Generation of Synthetic Radio Reflection-Transmission Tomography (RRTT) Data

Goddard Space Flight Center, Greenbelt, Maryland Numerical algorithms capable of generating synthetic radio tomography data (reflection transmission data) for asteroids, comets, and other near-Earth orbits (NEOs) were developed. Future missions to main asteroid belt objects, NEOs, and other small bodies of the solar system will aim to investigate the surface and subsurface compositions and internal structure of these objects with help of an onboard, low-frequency radio sounder. The resulting numerical model thus developed will be useful in performing trade studies required for designing an optimum radio sounder for the future missions. The forward numerical model will also be important for estimating structural properties of the small objects from the data collected by these future missions.

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Designing Planning Information for Automation into PRL

Lyndon B. Johnson Space Center, Houston, Texas Automation and autonomy are key elements in realizing the vision for space exploration. The NASA Exploration Technology Development Program (ETDP) has been developing several core autonomy capabilities, one of which is called a procedure representation language (PRL). PRL can be automatically translated into code that can be executed by NASA-developed autonomous executives.

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The OCO-2 Level 2 Retrieval Algorithm

Algorithm derives estimates of the column averaged atmospheric CO2. NASA’s Jet Propulsion Laboratory, Pasadena, California The Orbiting Carbon Observatory (OCO) strives for trace gas observations with unprecedented accuracy and precision. This requires a retrieval algorithm with many major improvements over existing retrieval software in the representation of the transfer of solar radiation through the atmosphere and instrument, such as full multiple-scattering calculation for each iteration step and correction for effects of polarization. In addition, the software allows retrieval of space-based and ground-based observations, so that potential algorithmic biases can be minimized for validation experiments. Furthermore, due to the flexible architecture of the software, spectra of existing similar instruments can be analyzed, which facilitates early testing using real space-based observations.

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Ionospheric Slant TEC Analysis Using GNSS-Based Estimation (IonoSTAGE)

At the time of this reporting, IonoSTAGE has been operated successfully under both UNIX and Macintosh operating systems. NASA’s Jet Propulsion Laboratory, Pasadena, California As signals emitted by global navigation satellite systems (GNSS) propagate toward users on or near the surface of the Earth, they experience delay due to the presence of charged particles in the ionosphere. Currently, ionospheric delay is the largest source of GNSS positioning error. To guarantee the safety of airline navigation based upon GNSS signals, satellite-based augmentation systems have been developed to ensure the accuracy, integrity, availability, and continuity of user position estimates derived from GNSS measurements.

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Implementation of a Terrain Radiometric Correction for UAVSAR

A paper discusses a calibration method suited to correct variations of UAVSAR (unmanned aerial vehicle synthetic aperture radar) backscatter with topography. To use radar backscatter to estimate forest biomass on terrain with slopes, it is necessary to remove the effect of topography. The remaining signal should be related to biomass. The hybrid approach uses the radar line of sight to project an oversampled version of the Digital Elevation Model into radar coordinates for summation. Terrain topography has a major impact on the radar backscatter. Slopes facing the radar appear very bright while slopes facing away appear darker.

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Picoradian Staring Astrometry Using a Simple Staring Telescope

A document describes solutions to problems of astrometry at the microarc-second (picoradian) level using a simple staring telescope. The problems include field-dependent beam-walk on the telescope’s mirrors, pixel position irregularity and distortion over time, non-flat intra-pixel quantum efficiency, and systematic errors inherent in the most common image centroiding algorithms (imperfect knowledge of the point spread function).

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Missing Value Imputation in Astronomical Time-Series Data

A document describes a solution to missing flux values in time-domain optical and radio astronomical survey data that form “light curves.” The technique incorporates a priori astronomical knowledge into a missing value imputation technique. It is assumed that missing values in astronomical time series are either Missing At Random (MAR), or missing due to the flux of the source falling below the instrument’s sensitivity threshold, termed Threshold Removed Observations (TRO).

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