Yunjin Kim

The Nuclear Spectroscopic Telescope Array (NuSTAR) High-Energy X-Ray Mission

The Nuclear Spectroscopic Telescope Array (NuSTAR) is a National Aeronautics and Space Administration (NASA) Small Explorer mission that carried the first focusing hard X-ray (6-79 keV) telescope into orbit. It was launched on a Pegasus rocket into a low-inclination Earth orbit on June 13, 2012, from Reagan Test Site, Kwajalein Atoll. NuSTAR will carry out a two-year primary science mission. The NuSTAR observatory is composed of the X-ray instrument and the spacecraft. The NuSTAR spacecraft is three-axis stabilized with a single articulating solar array based on Orbital Sciences Corporations LEOStar-2 design. The NuSTAR science instrument consists of two co-aligned grazing incidence optics focusing on to two shielded solid state CdZnTe pixel detectors. The instrument was launched in a compact, stowed configuration, and after launch, a 10-meter mast was deployed to achieve a focal length of 10.15 m. The NuSTAR instrument provides sub-arcminute imaging with excellent spectral resolution over a 12-arcminute field of view. The NuSTAR observatory will be operated out of the Mission Operations Center (MOC) at UC Berkeley. Most science targets will be viewed for a week or more. The science data will be transferred from the UC Berkeley MOC to a Science Operations Center (SOC) located at the California Institute of Technology (Caltech). In this paper, we will describe the mission architecture, the technical challenges during the development phase, and the post-launch activities.

The hydrosphere State (hydros) Satellite mission: an Earth system pathfinder for global mapping of soil moisture and land freeze/thaw

The Hydrosphere State Mission (Hydros) is a pathfinder mission in the National Aeronautics and Space Administration (NASA) Earth System Science Pathfinder Program (ESSP). The objective of the mission is to provide exploratory global measurements of the earths soil moisture at 10-km resolution with two- to three-days revisit and land-surface freeze/thaw conditions at 3-km resolution with one- to two-days revisit. The mission builds on the heritage of ground-based and airborne passive and active low-frequency microwave measurements that have demonstrated and validated the effectiveness of the measurements and associated algorithms for estimating the amount and phase (frozen or thawed) of surface soil moisture. The mission data will enable advances in weather and climate prediction and in mapping processes that link the water, energy, and carbon cycles. The Hydros instrument is a combined radar and radiometer system operating at 1.26 GHz (with VV, HH, and HV polarizations) and 1.41 GHz (with H, V, and U polarizations), respectively. The radar and the radiometer share the aperture of a 6-m antenna with a look-angle of 39/spl deg/ with respect to nadir. The lightweight deployable mesh antenna is rotated at 14.6 rpm to provide a constant look-angle scan across a swath width of 1000 km. The wide swath provides global coverage that meet the revisit requirements. The radiometer measurements allow retrieval of soil moisture in diverse (nonforested) landscapes with a resolution of 40 km. The radar measurements allow the retrieval of soil moisture at relatively high resolution (3 km). The mission includes combined radar/radiometer data products that will use the synergy of the two sensors to deliver enhanced-quality 10-km resolution soil moisture estimates. In this paper, the science requirements and their traceability to the instrument design are outlined. A review of the underlying measurement physics and key instrument performance parameters are also presented.

Model-Based Decomposition of Polarimetric SAR Covariance Matrices Constrained for Nonnegative Eigenvalues

Model-based decomposition of polarimetric radar covariance matrices holds the promise that specific scattering mechanisms can be isolated for further quantitative analysis. In this paper, we show that current algorithms suffer from a fatal flaw in that some of the scattering components result in negative powers. We propose a simple modification that ensures that all covariance matrices in the decomposition will have nonnegative eigenvalues. We further combine our nonnegative eigenvalue decomposition with eigenvector decomposition to remove additional assumptions that have to be made before the current algorithms can be used to estimate all the scattering components. Our results are illustrated using Airborne Synthetic Aperture Radar data and show that current algorithms typically overestimate the canopy scattering contribution by 10%-20%.

Adaptive Model-Based Decomposition of Polarimetric SAR Covariance Matrices

Previous model-based decomposition techniques are applicable to a limited range of vegetation types because of their specific assumptions about the volume scattering component. Furthermore, most of these techniques use the same model, or just a few models, to characterize the volume scattering component in the decomposition for all pixels in an image. In this paper, we extend the model-based decomposition idea by creating an adaptive model-based decomposition technique, allowing us to estimate both the mean orientation angle and a degree of randomness for the canopy scattering for each pixel in an image. No scattering reflection symmetry assumption is required to determine the volume contribution. We examined the usefulness of the proposed decomposition technique by decomposing the covariance matrix using the National Aeronautics and Space Administration/Jet Propulsion Laboratory Airborne Synthetic Aperture Radar data at the C-, L-, and P-bands. The randomness and mean orientation angle maps generated using our adaptive decomposition significantly improve the physical interpretation of the scattering observed at the three different frequencies.

A Time-Series Approach to Estimate Soil Moisture Using Polarimetric Radar Data

Electromagnetic scattering from a rough surface is a function of both surface roughness and dielectric constant of the scattering surface. Therefore, in order to estimate soil moisture of a bare surface accurately from radar measurements, the effects of surface roughness must be compensated for properly. Several algorithms have been developed to estimate soil moisture from a polarimetric radar image, all with limited ranges of applicability. No theoretical algorithm has been reported to retrieve volumetric soil moisture of a vegetated surface. In this paper, we examine a different approach to estimate soil moisture that exploits the fact that the backscattering cross section from a natural object changes over short timescales mainly due to variations in soil moisture. We develop a model function that expresses copolarized backscattering cross sections (sigmahh and sigmavv) in terms of volumetric soil moisture using L-band experimental data for both bare and vegetated surfaces. In order to estimate soil moisture, two unknowns in the model function must be determined. We propose a viable approach to determine these two unknowns using combined radiometer and radar data. This time-series approach also provides a framework to utilize a priori knowledge on soil moisture to improve the retrieval accuracy of volumetric soil moisture. We demonstrate that this time-series algorithm is a simple and robust way to estimate soil moisture for both bare and vegetated surfaces.

The Nuclear Spectroscopic Telescope Array (NuSTAR)

The Nuclear Spectroscopic Telescope Array (NuSTAR) is a NASA Small Explorer mission that will carry the first focusing hard X-ray (6 - 80 keV) telescope to orbit. NuSTAR will offer a factor 50 - 100 sensitivity improvement compared to previous collimated or coded mask imagers that have operated in this energy band. In addition, NuSTAR provides sub-arcminute imaging with good spectral resolution over a 12-arcminute eld of view. After launch, NuSTAR will carry out a two-year primary science mission that focuses on four key programs: studying the evolution of massive black holes through surveys carried out in fields with excellent multiwavelength coverage, understanding the population of compact objects and the nature of the massive black hole in the center of the Milky Way, constraining the explosion dynamics and nucleosynthesis in supernovae, and probing the nature of particle acceleration in relativistic jets in active galactic nuclei. A number of additional observations will be included in the primary mission, and a guest observer program will be proposed for an extended mission to expand the range of scientic targets. The payload consists of two co-aligned depth-graded multilayer coated grazing incidence optics focused onto a solid state CdZnTe pixel detectors. To be launched in early 2012 on a Pegasus rocket into a low-inclination Earth orbit, NuSTAR largely avoids SAA passage, and will therefore have low and stable detector backgrounds. The telescope achieves a 10.14-meter focal length through on-orbit deployment of an extendable mast. An aspect and alignment metrology system enable reconstruction of the absolute aspect and variations in the telescope alignment resulting from mast exure during ground data processing. Data will be publicly available at GSFCs High Energy Archive Research Center (HEASARC) following validation at the science operations center located at Caltech.

A General Characterization for Polarimetric Scattering From Vegetation Canopies

Current polarimetric model-based decomposition techniques are limited to specific types of vegetation because of their assumptions about the volume scattering component. In this paper, we propose a generalized probability density function based on the nth power of a cosine-squared function. This distribution is completely characterized by two parameters; a mean orientation angle and the power of the cosine-squared function. We show that the underlying randomness of the distribution is only a function of the power of the cosine-squared function. We then derive the average covariance matrix for various different elementary scatterers showing that the result has a very simple analytical form suitable for use in model-based decomposition schemes.

Ionospheric effects on synthetic aperture radar at 100 MHz to 2 GHz

Recently, there has been increasing interest in the use of spaceborne synthetic aperture radar (SAR) for measuring forest biomass. However, it is noted that conventional SAR using C-band or higher frequencies cannot penetrate into foliage, and therefore the biomass measurements require longer wavelengths, typically P-band (500 MHz). It is also known that the ionosphere is highly dispersive, causing group delay and broadening of pulses. The variance of the refractive index fluctuations due to turbulence is approximately proportional toƒ−4. In addition, the Faraday rotation due to the geomagnetic field in the ionosphere becomes significant. This paper presents an analysis with numerical examples of the following effects in the frequency range from 100 MHz to 2 GHz in order to show the frequency dependence and the effects of total electron content (TEC) of the ionosphere. First, the ionospheric turbulence can reduce the coherent length below the equivalent aperture size, and the azimuthal resolution becomes greater than D/2 where D is the antenna aperture size. Second, the ionospheric dispersion causes a shift of the imagery due to the group velocity. Third, the dispersion also creates broadening of the pulse. In addition, multiple scattering due to ionospheric turbulence gives rise to pulse broadening. Fourth, we consider the Faraday rotation effect and show that the ellipticity change is negligible, but the orientation angle changes significantly at P-band. Numerical examples are shown using typical ionospheric parameters, turbulence spectrum, and TEC values.

Periodic chiral structures

The electromagnetic properties of a structure that is both chiral and periodic are investigated using coupled-mode equations. The chirality is characterized by the constitutive relations D= epsilon E+i xi /sub c/B and H=i xi /sub c/E+B/ mu , where xi /sub c/ is the chiral admittance. The periodicity is described by a sinusoidal perturbation of the permittivity, permeability, and chiral admittance. The coupled-mode equations are derived from physical considerations and used to examine bandgap structure and reflected and transmitted fields. Chirality is observed predominantly in transmission, whereas periodicity is present in both reflection and transmission. >

The effect of small-wave modulation on the electromagnetic bias

The effect of the modulation of small ocean waves by large waves on the physical mechanism of the electromagnetic (EM) bias is examined by conducting a numerical scattering experiment which does not assume the applicability of geometric optics. The modulation effect of the large waves on the small waves is modeled using the principle of conservation of wave action and includes the modulation of gravity-capillary waves. The frequency dependence and magnitude of the EM bias is examined for a simplified ocean spectral model as a function of wind speed. These calculations allow us to assess the validity of previous assumptions made in the theory of the EM bias, with respect to both scattering and hydrodynamic effects. We find that the geometric optics approximation is inadequate for predictions of the EM bias at typical radar altimeter frequencies, while the improved scattering calculations provide a frequency dependence of the EM bias which is in qualitative agreement with observation. We also find that, for typical wind speeds, the EM bias contribution due to small-wave modulation is of the same order as that due to modulation by the nonlinearities of the large-scale waves.