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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS2008

Characterization of MODIS VIS/NIR Spectral Band Detector-to-Detector Difference

MODIS has 36 spectral bands with wavelengths in the visible (VIS), near-infrared (NIR), shortwave infrared (SWTR), mid-wave infrared (MWIR), and long-wave infrared (LWIR). It makes observations at three nadir spatial resolutions: 0,25km for bands 1-2 with 40 detectors per band, 0.5km for bands 3-7 with 20 detectors per band, and 1km for bands 8-36 with 10 detectors per band. The VIS, NIR, and S\VIR spectral bands are the reflective solar bands (RSB), which are calibrated on-orbit by a solar diffuser (SD). In addition, MODIS lunar observations are used to track the RSB calibration stability. In this study, we examine detector-to-detector calibration difference for the VIStNIR spectral bands using the SD and lunar observations. The results will be compared with an independent analysis with additional information, such as polarization correction, derived from standard ocean color data products. The current MODIS RSB calibration approach only carries a band-averaged RVS (response versus scan angle) correction. The results from this study suggest that a detector-based RVS correction should be used to improve the L1B data quality, especially for several VIS bands in Terra MODIS due to large changes of the scan mirror's optical properties in recent years.

Xiong, X.↗
NASA NTRS2011

Sensitivity of C-Band Polarimetric Radar-Based Drop Size Distribution Measurements to Maximum Diameter Assumptions

The estimation of rain drop size distribution (DSD) parameters from polarimetric radar observations is accomplished by first establishing a relationship between differential reflectivity (Z(sub dr)) and the central tendency of the rain DSD such as the median volume diameter (D0). Since Z(sub dr) does not provide a direct measurement of DSD central tendency, the relationship is typically derived empirically from rain drop and radar scattering models (e.g., D0 = F[Z (sub dr)] ). Past studies have explored the general sensitivity of these models to temperature, radar wavelength, the drop shape vs. size relation, and DSD variability. Much progress has been made in recent years in measuring the drop shape and DSD variability using surface-based disdrometers, such as the 2D Video disdrometer (2DVD), and documenting their impact on polarimetric radar techniques. In addition to measuring drop shape, another advantage of the 2DVD over earlier impact type disdrometers is its ability to resolve drop diameters in excess of 5 mm. Despite this improvement, the sampling limitations of a disdrometer, including the 2DVD, make it very difficult to adequately measure the maximum drop diameter (D(sub max)) present in a typical radar resolution volume. As a result, D(sub max) must still be assumed in the drop and radar models from which D0 = F[Z(sub dr)] is derived. Since scattering resonance at C-band wavelengths begins to occur in drop diameters larger than about 5 mm, modeled C-band radar parameters, particularly Z(sub dr), can be sensitive to D(sub max) assumptions. In past C-band radar studies, a variety of D(sub max) assumptions have been made, including the actual disdrometer estimate of D(sub max) during a typical sampling period (e.g., 1-3 minutes), D(sub max) = C (where C is constant at values from 5 to 8 mm), and D(sub max) = M*D0 (where the constant multiple, M, is fixed at values ranging from 2.5 to 3.5). The overall objective of this NASA Global Precipitation Measurement Mission (GPM/PMM Science Team)-funded study is to document the sensitivity of DSD measurements, including estimates of D0, from C-band Z(sub dr) and reflectivity to this range of D(sub max) assumptions. For this study, GPM Ground Validation 2DVD's were operated under the scanning domain of the UAHuntsville ARMOR C-band dual-polarimetric radar. Approximately 7500 minutes of DSD data were collected and processed to create gamma size distribution parameters using a truncated method of moments approach. After creating the gamma parameter datasets the DSD's were then used as input to a T-matrix model for computation of polarimetric radar moments at C-band. All necessary model parameterizations, such as temperature, drop shape, and drop fall mode, were fixed at typically accepted values while the D(sub max) assumption was allowed to vary in sensitivity tests. By hypothesizing a DSD model with D(sub max) (fit) from which the empirical fit to D0 = F[Z(sub dr)] was derived via non-linear least squares regression and a separate reference DSD model with D(sub max) (truth), bias and standard error in D0 retrievals were estimated in the presence of Z(sub dr) measurement error and hypothesized mismatch in D(sub max) assumptions. Although the normalized standard error for D0 = F[Z(sub dr)r] can increase slightly (as much as from 11% to 16% for all 7500 DSDs) when the D(sub max) (fit) does not match D(sub max) (truth), the primary impact of uncertainty in D(sub max) is a potential increase in normalized bias error in D0 (from 0% to as much as 10% over all 7500 DSDs, depending on the extent of the mismatch between D(sub max) (fit) and D(sub max) (truth)). For DSDs characterized by large Z(sub dr) (Z(sub dr) > 1.5 to 2.0 dB), the normalized bias error for D0 estimation at C-band is sometimes unacceptably large (> 10%), again depending on the extent of the hypothesized D(sub max) mismatch. Modeled errors in D0 retrievals from Z(sub dr) at C-band are demonstrated in detail and comparedo similar modeled retrieval errors at S-band and X-band where the sensitivity to D(sub max) is expected to be less. The impact of D(sub max) assumptions to the retrieval of other DSD parameters such as Nw, the liquid water content normalized intercept parameter, are also explored. Likely implications for DSD retrievals using C-band polarimetric radar for GPM are assessed by considering current community knowledge regarding D(sub max) and quantifying the statistical distribution of Z(sub dr) from ARMOR over a large variety of meteorological conditions. Based on these results and the prevalence of C-band polarimetric radars worldwide, a call for more emphasis on constraining our observational estimate of D(sub max) within a typical radar resolution volume is made

Carey, Lawrence D.↗
NASA NTRS2023

Towards Soil Moisture Profile Estimation in the Root Zone Using L- and P-Band Radiometer Observations: A Coherent Modelling Approach

Precision irrigation management and crop water stress assessment rely on accurate estimation of root zone soil moisture. However, only the top 5cm soil moisture can be estimated using the two current passive microwave satellite missions, Soil Moisture and Ocean Salinity (SMOS) and Soil Moisture Active Passive (SMAP), which operate at L-band (wavelength of ~21cm). Since the contributing depth of the soil to brightness temperature increases with observation wavelength, it is expected that a P-band (wavelength of ~40cm) radiometer could potentially provide soil moisture information from deeper layers of the soil profile. Moreover, by combining both L- and P- bands, it is hypothesized that the soil moisture profile can be estimated even beyond their individual observation depths. The aim of this study was to demonstrate the potential of combined L-band and P-band radiometer observations to estimate the soil moisture profile under flat bare soil using a stratified coherent forward model. Brightness temperature observations at L-band and P-band from a tower based experimental site across a dry (April 2019) and a wet (March 2020) period, covering different soil moisture profile shapes, were used in this study. Results from an initial synthetic study showed that the performance of a combined L-band and P-band approach was better than the performance of using either band individually, with an average depth over which reliable soil moisture profile information could be estimated (i.e. with a target root mean square error (RMSE) of less than 0.04 m3/m3) being 20cm for linear and 15cm for second-order polynomial functions. Other functions were also tested but found to have a poorer performance. Applying the method to the tower-based brightness temperature achieved an average estimation depth of 28cm (20cm) and 5cm (5cm) during the dry and wet periods respectively when using a second-order polynomial (linear) function. These findings highlight the opportunity of a satellite mission with L-band and P-band observations to accurately estimate the soil moisture profile to as deep as 30cm globally.

Foad Brakhasi↗
NASA NTRS2023

Evaluation of EPIC Oxygen Bands Stability With Radiative Transfer Simulations Over the South Pole

The Earth Polychromatic Imaging Camera (EPIC) onboard the Deep Space Climate Observatory (DSCOVR) satellite orbiting the Sun at the Lagrange-1 point was launched without onboard calibration systems. Vicarious calibration is conducted for 8 of the 10 UV/VIS/NIR channels using other low earth orbiting satellite instruments, while its two O 2 bands (688 nm and 764nm) rely on indirect moon-view calibrations because the same narrow-band O 2 bands are not readily available from other in-flight instruments. This study compares EPIC measurements from the four O 2 bands aiming at examining sensor stability over a uniquely suited location, i.e., the permanently snow-covered South Pole. The study utilizes radiative transfer model simulations with in-situ atmospheric soundings taken at South Pole during months of December and January from 2015 to 2022. The absolute discrepancy between the model simulations and observations is less than 1.0% for the two reference bands, but 5.75% and 15.63% for the 688nm, and 764 nm absorption bands, respectively. The simulated A-band and B-band ratios are 16.09% and 4.74% higher than that from the observations. Various sensitivities are conducted to estimate possible contributions to the discrepancies from input atmospheric profiles, spectral surface albedos and surface BRDF. While none of the input uncertainties is likely to account for the large discrepancies in the oxygen absorption bands, a small shift in the instrument response function could be the main reason for these biases. On the other hand, the model simulations are able to capture systematic variations with observed angular measurements and explain the multi-year trends found in observed O 2 band ratios due to satellite orbit shifting. When model simulated contributions from the angle variations are deducted from the observed O 2 band ratios, the residual O 2 band ratios are found to be stable since 2015.

EPIC↗
DOE OSTI2021

Opening band gaps of low-dimensional materials at the meta-GGA level of density functional approximations

The quasiparticle band structure can be properly described by Hedin's GW approximation (GW), at a high computational cost. For band gaps, semilocal density functionals up to the generalized gradient approximation (GGA) level cannot compete with the accuracy of hybrid-based approximations or GW. Meta-GGA density functionals with a strong dependence on the kinetic energy density ingredient can potentially give wider band gaps compared with GGAs. The recent TASK meta-GGA density functional from Aschebrock and Kümmel [ Phys. Rev. Research 1 , 033082 (2019) ], is constructed with an enhanced nonlocality in the generalized Kohn-Sham scheme and therefore harbors great opportunities for band gap prediction. Although this approximation was found to yield excellent band gaps of bulk solids, this accuracy cannot be straightforwardly transferred to low-dimensional materials. Additionally, the reduced screening of these materials results in larger band gaps compared with their bulk counterparts, as an additional barrier to overcome. In this paper we demonstrate how the alteration of this functional affects the band gaps of monolayers and nanoribbons and present accurate band gaps competing with the revised Heyd-Scuseria-Ernzerhof (HSE06) approximation. In order to achieve this goal, we have modified the TASK functional (a) by changing the tight upper bound for one- or two-electron systems ( h X 0 ) from 1.174 to 1.29 and (b) by changing the limit of the interpolation function f X ( α → ∞ ) of the TASK functional that interpolates the exchange enhancement factor F X ( s , α ) from α = 0 to 1. The resulting modified TASK (mTASK) was tested for various materials from three dimensions to two dimensions to one dimension (nanoribbons) and was compared with the results of the higher-level hybrid functional HSE06 or with the G 0 W 0 approximation within many-body perturbation theory. We find that mTASK systematically improves the band gaps and band structures of two-dimensional (2D) and 1D systems, without significantly affecting the accuracy of the original TASK for the bulk 3D materials, when compared with the Perdew-Burke-Ernzerhof (PBE) GGA and the strongly constrained and appropriately normed (SCAN) meta-GGA. We further demonstrate the applicability of mTASK by assessing the band structures of transition metal dichalcogenide nanoribbons with respect to various bending curvatures.

36 MATERIALS SCIENCE↗
NASA NTRS2016

VIIRS Reflective Solar Band Radiometric and Stability Evaluation Using Deep Convective Clouds

This work takes advantage of the stable distribution of deep convective cloud (DCC) reflectance measurements to assess the calibration stability and detector difference in Visible Infrared Imaging Radiometer Suite (VIIRS) reflective bands. VIIRS Sensor Data Records (SDRs) from February 2012 to June 2015 are utilized to analyze the long-term trending, detector difference, and half angle mirror (HAM) side difference. VIIRS has two thermal emissive bands with coverage crossing 11 microns for DCC pixel identification. The comparison of the results of these two processing bands is one of the indicators of analysis reliability. The long-term stability analysis shows downward trends (up to approximately 0.4 per year) for the visible and near-infrared bands and upward trends (up to 0.5per year) for the short- and mid-wave infrared bands. The detector difference for each band is calculated as the difference relative to the average reflectance overall detectors. Except for the slightly greater than 1 difference in the two bands at 1610 nm, the detector difference is less than1 for other solar reflective bands. The detector differences show increasing trends for some short-wave bands with center wavelengths from 400 to 600 nm and remain unchanged for the bands with longer center wavelengths. The HAM side difference is insignificant and stable. Those short-wave bands from 400 to 600 nm also have relatively larger HAM side difference, up to 0.25.Comparing the striped images from SDR and the smooth images after the correction validates the analyses of detector difference and HAM side difference. These analyses are very helpful for VIIRS calibration improvement and thus enhance product quality

VIIRS↗
NASA NTRS2019

On-Orbit Tracking of Sub-Sample Gain Differences in SNPP and NOAA-20 VIIRS Imagery Bands

The VIIRS instruments on board the SNPP and NOAA-20 (N20) satellites have 14 reflective solar bands covering a spectral range from 412 nm to 2250 nm. Three of these are imaging bands (I bands) with a nadir spatial resolution of 375 m and 11 are moderate resolution bands (M bands) with a resolution of 750 m. The higher resolution in the I bands is achieved by a combination of more detectors, with the I bands having twice as many detectors of half the size for every M band detector, and a higher data rate, with the I bands having two sub-samples for every sample of M band data. To ensure calibration accuracy, any systematic difference in the response of the two sub-samples needs to be monitored and corrected in the calibrated products. In this paper, we use the solar diffuser calibrations to monitor the gain differences between the two sub-samples of the I bands both as a function of time and signal level. We find gain differences of about 0.1% for I1, 0.3% for I2, and <0.1% for I3 that are mostly constant over the range of signal values available in the SD calibration. These values are mostly consistent throughout the mission for both instruments. The results are remarkably similar for the two VIIRS instruments, including a slightly out-of-family behavior seen in a few detectors. We discuss possible causes for the difference and the impact on the aggregated Earth view images.

On-orbit↗
NASA NTRS2021

MODIS Reflective Solar Bands Calibration Improvements for Collection 7

Calibration of Terra and Aqua MODIS reflective solar bands (RSB) has evolved significantly since the launch of the first MODIS instrument on the Terra satellite more than 21 years ago. In NASA’s current Collection 6 and 6.1 Level 1B products (C6/C6.1 L1B), the RSB calibration algorithm continues to rely primarily on the onboard solar diffuser to calibrate the instrument gain. Lunar observations are used to track on-orbit changes in the response versus scan angle (RVS), and data from pseudo-invariant desert sites are used to apply adjustments to the gain and RVS calibration for select bands. The resulting reflectance products have in general shown a very stable performance. In recent years, some performance degradation has been noted for a few bands and algorithm changes have been tested to further improve the calibration accuracy for the upcoming Collection 7 (C7) L1B reprocess. In this paper, we present the MODIS RSB calibration improvements that will be included in C7. Major improvements include: applying polarization correction to the desert data before using it to generateRVS for Terra bands 8, 9, 3, and 10; using ocean scene data and an interband calibration approach to correct for long-term drift of Terra bands 11 and 12; applying an updated crosstalk correction to Terra SWIR bands over the entire mission; and using data from deep convective clouds in Terra SWIR band calibration, including the addition of time-dependent RVS for bands 5 and 26. All other minor calibration changes are also covered. Overall, the reflectance differences at nadir between C6.1 and C7 are within a few percent, though the differences increase in some cases at large scan angles. The Terra visible (3, 8-12) and SWIR bands (5-7, 26) have the most significant improvements. For all other Terra bands and all Aqua bands, the C7-C6.1 differences are mostly within 1%

MODIS↗
DOE OSTI2025

Quantifying the Impact of LSST u -band Survey Strategy on Photometric Redshift Estimation and the Detection of Lyman-break Galaxies

The Vera C. Rubin Observatory will conduct the Legacy Survey of Space and Time (LSST), promising to discover billions of galaxies out to redshift 7, using six photometric bands (ugrizy) spanning the near-ultraviolet to the near-infrared. The exact number of and quality of information about these galaxies will depend on survey depth in these six bands, which in turn depends on the LSST survey strategy, i.e., how often and how long to expose in each band. u-band depth is especially important for photometric redshift (photo-z) estimation and for detection of high-redshift Lyman-break galaxies (LBGs). In this paper, we use a simulated galaxy catalog and an analytic model for the LBG population to study how recent updates and proposed changes to Rubin’s u-band throughput and LSST survey strategy impact photo-z accuracy and LBG detection. We find that proposed variations in u-band strategy have a small impact on photo-z accuracy for z < 1.5 galaxies, but the outlier fraction, scatter, and bias for higher-redshift galaxies vary by up to 50%, depending on the survey strategy considered. The number of u-band dropout LBGs at z ∼ 3 is also highly sensitive to the u-band depth, varying by up to 500%, while the number of griz-band dropouts is only modestly affected. Under the new u-band strategy recommended by the Rubin Survey Cadence Optimization Committee, we predict u-band dropout number densities of 110 deg −2 (3200 deg −2 ) in year 1 (10) of LSST. We discuss the implications of these results for LSST cosmology.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1993

Multiple scattering effects on the Linear Depolarization Ratio (LDR) measured during CaPE by a Ka-band air-borne radar

Air-borne radar measurements of thunderstorms were made as part of the CaPE (Convection and Precipitation/Electrification) experiment in Florida in July 1991. The radar has two channels, X-band (10 GHz) and Ka-band (34.5 GHz), and is capable of measuring cross-polarized returns as well as co-polarized returns. In stratiform rain, the cross-polarized components can be observed only at the bright band region and from the surface reflection. The linear depolarization ratios (LDR's) measured at X-band and Ka-band at the bright band are nearly equal. In convective rain, however, the LDR in Ka-band often exceeds the X-band LDR by several dB, and sometimes by more than 10 dB, reaching LDR values of up to -5 dB over heavy convective rain. For randomly oriented hydrometeors, such high LDR values cannot be explained by single scattering from non-spherical scattering particles alone. Because the LDR by single backscatter depends weakly on the wavelength, the difference between the Ka-band and X-band LDR's suggests that multiple scattering effects prevail in the Ka-band LDR. In order to test this inference, the magnitude of the cross-polarized component created by double scattering was calculated using the parameters of the airborne radar, which for both frequencies has beamwidths of 5.1 degrees and pulse widths of 0.5 microsecond. Uniform rain beyond the range of 3 km is assumed.

Iguchi, Toshio↗
NASA NTRS1993

Multi-band reflector antenna with double-ring element frequency selective subreflector

Frequency selective subreflectors (FSS) are often employed in the reflector antenna system of a communication satellite or a deep space exploration vehicle for multi-frequency operations. In the past, FSS's have been designed for diplexing two frequency bands. For example, the Voyager FSS was designed to diplex S and X bands and the TDRSS FSS was designed to diplex S and Ku bands. Recently, NASA's CASSINI project requires an FSS to multiplex four frequency (S/X/Ku/Ka) bands. Theoretical analysis and experimental verifications are presented for a multi-band flat pannel FSS with double-ring elements. Both the exact formulation and the thin-ring approximation are described for analyzing and designing this multi-ring patch element FSS. It is found that the thin-ring approximation fails to predict the electrically wide ring element FSS's performance. A single screen double-ring element FSS is demonstrated for the tri-band system that reflects the X-band signal while transmitting through the S- and Ku-band signals. In addition, a double screen FSS with non-similar double-ring elements is presented for the Cassini's four-band system which reflects the X- and Ka-band signals while passing the S- and Ku-band signals. To accurately predict the FSS effects on a dual reflector antenna's radiation pattern, the FSS subreflector's transmitted/reflected field variation as functions of the polarization and incident angles with respect to the local coordinates was taken into account. An FSS transmission/reflection coefficient table is computed for TE and TM polarizations at various incident angles based on the planar FSS model. Next, the hybrid Geometric Optics (GO) and Physical Optics (PO) technique is implemented with linearly interpolating the FSS table to efficiently determine the FSS effects in a dual reflector antenna.

Wu, Te-Kao↗
NASA NTRS1995

Intensity and Self-Broadening Measurements of the 01(exp 1)21-00(exp 0)01 CO2 Perpendicular Band at 5315/cm

The near-infrared thermal emission windows in the spectrum of the night-side of Venus have stimulated new determinations of the intensities of weak CO2 bands which are prominent absorption features in Venus spectra. Parameters for many unmeasured bands have been recomputed for the HITRAN compilation using direct numerical diagonalization (DND) [Wattson and Rothman, J.Q.S.R.T. 48, 763 (1992)]. To assess these HITRAN values, we have been measuring several of these bands on spectra which were obtained using the Kitt Peak McMath FTS and 6-meter White cell. Last year we presented preliminary intensity measurements of the 01(exp 1)21-00(exp 0)01 perpendicular band and 4 associated hot bands, Five additional McMath FTS spectra have now been obtained covering the region 3800 to 8400/cm. This permits us to finalize our intensity measurements, and to make an assessment of their uncertainties. We anticipate that these measured values will help improve further DND calculations of many weak unmeasureable bands. In addition, self-broadening parameters were determined for some lines of the 01(exp 1)21-00(exp 0)01 perpendicular band on spectra obtained with 65 and 80 torr of CO2. Because of the large spectral range, these measurements could be compared directly to self-broadening parameters of corresponding parallel. band lines measured on the same spectra. This procedure eliminates several possible sources of systematic errors that are important when attempting to determine whether or not corresponding rotational lines in different overtone-combination bands have significant differences. Our measurements thus far have found self-broadening parameters for the 01(exp 1)21-00(exp 0)01 perpendicular band to be slightly larger than similar measurements for the 30(exp 0)14-00(exp 0)01 parallel band at 6076/cm.

Giver, Lawrence P.↗
NASA NTRS2012

Terra MODIS Band 27 Electronic Crosstalk Effect and Its Removal

The MODerate-resolution Imaging Spectroradiometer (MODIS) is one of the primary instruments in the NASA Earth Observing System (EOS). The first MODIS instrument was launched in December, 1999 on-board the Terra spacecraft. MODIS has 36 bands, covering a wavelength range from 0.4 micron to 14.4 micron. MODIS band 27 (6.72 micron) is a water vapor band, which is designed to be insensitive to Earth surface features. In recent Earth View (EV) images of Terra band 27, surface feature contamination is clearly seen and striping has become very pronounced. In this paper, it is shown that band 27 is impacted by electronic crosstalk from bands 28-30. An algorithm using a linear approximation is developed to correct the crosstalk effect. The crosstalk coefficients are derived from Terra MODIS lunar observations. They show that the crosstalk is strongly detector dependent and the crosstalk pattern has changed dramatically since launch. The crosstalk contributions are positive to the instrument response of band 27 early in the mission but became negative and much larger in magnitude at later stages of the mission for most detectors of the band. The algorithm is applied to both Black Body (BB) calibration and MODIS L1B products. With the crosstalk effect removed, the calibration coefficients of Terra MODIS band 27 derived from the BB show that the detector differences become smaller. With the algorithm applied to MODIS L1B products, the Earth surface features are significantly removed and the striping is substantially reduced in the images of the band. The approach developed in this report for removal of the electronic crosstalk effect can be applied to other MODIS bands if similar crosstalk behaviors occur.

Sun, Junqiang↗
NASA NTRS2012

Development of a Q-band Propagation Campaign in the United States

The imminent saturation of commercial Ka-band services has generated increased interest by the SATCOM industry, as well as NASA (via potential commercially provided SATCOM services), to investigate the use of the Q-band (37-42 GHz) for future space-to-earth communications spectrum utilization. It is well understood that the use of higher frequencies (i.e. , Q-band) offers wider bandwidth, higher data rate services, but an understanding of Q-band performance limitations as they pertain to atmospheric propagation, particularly at NASA and commercial sites of interest, is not well characterized. Thus, the first steps towards system performance determination will be the initiation of a propagation campaign to statistically The imminent saturation of commercial Ka-band services has generated increased interest by the SATCOM industry, as well as NASA (via potential commercially provided SATCOM services), to investigate the use of the Q-band (37-42 GHz) for future space-to-earth communications spectrum utilization. It is well understood that the use of higher frequencies (i .e., Q-band) offers wider bandwidth, higher data rate services, but an understanding of Q-band performance limitations as they pertain to atmospheric propagation, particularly at NASA and commercial sites of interest, is not well characterized. Thus, the first steps towards system performance determination will be the initiation of a propagation campaign to statistically quantify long-term degradation parameters due to the atmosphere. As such, NASA Glenn Research Center (GRC), in collaboration with Space Systems/Loral(SS/L), is leading an effort to characterize Q-band link performance at key sites to determine its potential for use in future space communications architectures. The proposed propagation campaign is divided into phases, beginning with passive radiometric observations in the Q-band, and eventually leading to an active beacon experiment. Herein, we describe the schedule, development, and architecture of the first Q-band propagation campaign being conducted in the US and the proposed objectives of the effort.

Nessel, James A.↗
NASA NTRS2013

System and method for progressive band selection for hyperspectral images

Disclosed herein are systems, methods, and non-transitory computer-readable storage media for progressive band selection for hyperspectral images. A system having module configured to control a processor to practice the method calculates a virtual dimensionality of a hyperspectral image having multiple bands to determine a quantity Q of how many bands are needed for a threshold level of information, ranks each band based on a statistical measure, selects Q bands from the multiple bands to generate a subset of bands based on the virtual dimensionality, and generates a reduced image based on the subset of bands. This approach can create reduced datasets of full hyperspectral images tailored for individual applications. The system uses a metric specific to a target application to rank the image bands, and then selects the most useful bands. The number of bands selected can be specified manually or calculated from the hyperspectral image's virtual dimensionality.

Fisher, Kevin↗
NASA NTRS2014

Studying NASA's Transition to Ka-Band Communications for Low Earth Orbit

As the S-band spectrum becomes crowded, future space missions will need to consider moving command and telemetry services to Ka-band. NASA's Space Communications and Navigation (SCaN) Testbed provides a software-defined radio (SDR) platform that is capable of supporting investigation of this service transition. The testbed contains two S-band SDRs and one Ka-band SDR. Over the past year, SCaN Testbed has demonstrated Ka-band communications capabilities with NASAs Tracking and Data Relay Satellite System (TDRSS) using both open- and closed-loop antenna tracking profiles. A number of technical areas need to be addressed for successful transition to Ka-band. The smaller antenna beamwidth at Ka-band increases the criticality of antenna pointing, necessitating closed loop tracking algorithms and new techniques for received power estimation. Additionally, the antenna pointing routines require enhanced knowledge of spacecraft position and attitude for initial acquisition, versus an S-band antenna. Ka-band provides a number of technical advantages for bulk data transfer. Unlike at S-band, a larger bandwidth may be available for space missions, allowing increased data rates. The potential for high rate data transfer can also be extended for direct-to-ground links through use of variable or adaptive coding and modulation. Specific examples of Ka-band research from SCaN Testbeds first year of operation will be cited, such as communications link performance with TDRSS, and the effects of truss flexure on antenna pointing.

space communications↗
NASA NTRS2014

Studying NASA's Transition to Ka-Band Communications for Low Earth Orbit

As the S-band spectrum becomes crowded, future space missions will need to consider moving command and telemetry services to Ka-band. NASAs Space Communications and Navigation (SCaN) Testbed provides a software-defined radio (SDR) platform that is capable of supporting investigation of this service transition. The testbed contains two S-band SDRs and one Ka-band SDR. Over the past year, SCaN Testbed has demonstrated Ka-band communications capabilities with NASAs Tracking and Data Relay Satellite System (TDRSS) using both open- and closed-loop antenna tracking profiles. A number of technical areas need to be addressed for successful transition to Ka-band. The smaller antenna beamwidth at Ka-band increases the criticality of antenna pointing, necessitating closed loop tracking algorithms and new techniques for received power estimation. Additionally, the antenna pointing routines require enhanced knowledge of spacecraft position and attitude for initial acquisition, versus an S-band antenna. Ka-band provides a number of technical advantages for bulk data transfer. Unlike at S-band, a larger bandwidth may be available for space missions, allowing increased data rates. The potential for high rate data transfer can also be extended for direct-to-ground links through use of variable or adaptive coding and modulation. Specific examples of Ka-band research from SCaN Testbeds first year of operation will be cited, such as communications link performance with TDRSS, and the effects of truss flexure on antenna pointing.

International Space Station↗
NASA NTRS2008

Delay-Throughput Performance of the Deep-Space Ka-band Link

In this paper, performance of a first-in, first-out (FIFO), selective retransmission scheme for the deep-space Ka-band link is presented and compared to the performance of a comparable X-band link. In this analysis, 16 months of water vapor radiometer (WVR) and advanced water vapor radiometer (AWVR) data from the three Deep Space Network (DSN) Communication Complexes (DSCC) were used to emulate weather effects on X-band and Ka-band links from Mars. Mars Reconnaissance Orbiter (MRO) X-band and Ka-band telecommunications parameters were used for spacecraft telecommunications capabilities. One pass per week per complex was selected from MRO's Deep Space Network (DSN) schedule from April 1, 2006 to August 31, 2007 for a total of 207 passes (69 passes per complex) for this analysis. For each pass both X-band and Ka-band links were designed using at most two data rates so that the expected pass capacity would be maximized subject to a minimum availability requirement (MAR). In conjunction with the WVR/AWVR data, elevation profiles of the selected passes and models for the performance of the antennas in the DSN were used to emulate the performance of both links. It was assumed that the retransmission of the data takes place not on the same pass as the original transmission but during subsequent passes. The data collected before a pass was assumed to be a fraction of the expected capacity of the pass as calculated through the link design process. Infinite spacecraft storage was assumed to obtain an upper bound on the spacecraft storage requirement. The independent parameters of this analysis were MAR and the ratio of data collected before a pass to the expected pass capacity. Since the selected passes did not occur at regular intervals, the delay in this analysis was measured in terms of number of passes. The throughput was measured in terms of number of bits received successfully on the ground. The results indicate that reasonable delay performance could be achieved with very high throughput for relatively low MAR values for data collection to expected pass capacity ratio of around 97% for Ka-band. The results indicate that, except for very low average delay requirements, the Ka-band link provides more than twice the throughput of the X-band link for the same amount of power consumed by the spacecraft. In addition, the results indicate that the required storage onboard the spacecraft is not prohibitive and good performance could be achieved by using a buffer size less than three times the maximum amount of data collected before a pass.

Shambayati, Shervin↗