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All sourcesNASA NTRSDOE OSTI
NASA NTRS1977

A distributed processing high data rate multiport wind-tunnel pressure measurement system

A multiport pressure measurement system has been developed for the high data rates and the in situ calibration of electronically scanned pressure (ESP) sensors. The system employs a stand-alone microcomputer, connected to a host computer, for data acquisition and preprocessing. The host computer provides several operational modes. Before each run the in situ calibration of each sensor is automatically performed. Using up to a maximum of 14 data acquisition and control units (DACU's), the system may be expanded from 16 to 10,752 pressure ports. Each DACU can make 20,000 measurements per second, average data, and perform statistical analyses before transferring data to the central unit. The system may be introduced into existing facilities and requires little user orientation.

Juanarena, D.↗
NASA NTRS1990

Remote sensing of Earth terrain

Remote sensing of earth terrain is examined. The layered random medium model is used to investigate the fully polarimetric scattering of electromagnetic waves from vegetation. The model is used to interpret the measured data for vegetation fields such as rice, wheat, or soybean over water or soil. Accurate calibration of polarimetric radar systems is essential for the polarimetric remote sensing of earth terrain. A polarimetric calibration algorithm using three arbitrary in-scene reflectors is developed. In the interpretation of active and passive microwave remote sensing data from the earth terrain, the random medium model was shown to be quite successful. A multivariate K-distribution is proposed to model the statistics of fully polarimetric radar returns from earth terrain. In the terrain cover classification using the synthetic aperture radar (SAR) images, the applications of the K-distribution model will provide better performance than the conventional Gaussian classifiers. The layered random medium model is used to study the polarimetric response of sea ice. Supervised and unsupervised classification procedures are also developed and applied to synthetic aperture radar polarimetric images in order to identify their various earth terrain components for more than two classes. These classification procedures were applied to San Francisco Bay and Traverse City SAR images.

Kong, Jin AU↗
NASA NTRS2001

Stochastic Modeling and Generation of Partially Polarized or Partially Coherent Electromagnetic Waves

Many new Earth remote-sensing instruments are embracing both the advantages and added complexity that result from interferometric or fully polarimetric operation. To increase instrument understanding and functionality a model of the signals these instruments measure is presented. A stochastic model is used as it recognizes the non-deterministic nature of any real-world measurements while also providing a tractable mathematical framework. A stationary, Gaussian-distributed model structure is proposed. Temporal and spectral correlation measures provide a statistical description of the physical properties of coherence and polarization-state. From this relationship the model is mathematically defined. The model is shown to be unique for any set of physical parameters. A method of realizing the model (necessary for applications such as synthetic calibration-signal generation) is given and computer simulation results are presented. The signals are constructed using the output of a multi-input multi-output linear filter system, driven with white noise.

Davis, Brynmor↗
NASA NTRS2001

Atmospheric attenuation calibrations of surface weather observations

A correlation between near-IR atmospheric attenuation measurements made by the Atmospheric Visibility Monitor (AVM) at the Table Mountain Facility and airport surface weather observations at Edwards Air Force Base has been performed. High correlations (over 0.93) exist between the simultaneous Edwards observed sky cover and the average AVM measured attenuations over the course of the 10 months analyzed. The statistical relationship between the data-sets allows the determination of coarse attenuation statistics from the surface observations, suggesting that such statistics may be extrapolated from any surface weather observation site, Furthermore, a superior technique for converting AVM images to attenuation values by way of MODTRAN predictions has been demonstrated.

laser propogation↗
NASA NTRS1983

An analysis of new techniqes for radiometric correction of LANDSAT-4 Thematic Mapper images

The utility of methods for generating TM RLUTS which can improve the quality of the resultant images was investigated. The TM-CCT-ADDS tape was changed to account for a different collection window for the calibration data. Several scenes of Terrebonne Bay, Louisiana and the Grand Bahamas were analyzed to evaluate the radiometric corrections operationally applied to the image data and to investigate several techniques for reducing striping in the images. Printer plots for the TM shutter data were produced and detector statistics were compiled and plotted. These statistics included various combinations of the average shutter counts for each scan before and after DC restore for forward and reverse scans. Results show that striping is caused by the detectors becoming saturated when they view a bright cloud and depress the DC restore level.

Kogut, J.↗
NASA NTRS1994

The Accuracy of Parameter Estimation in System Identification of Noisy Aircraft Load Measurement

This thesis focuses on the subject of the accuracy of parameter estimation and system identification techniques. Motivated by a complicated load measurement from NASA Dryden Flight Research Center, advanced system identification techniques are needed. The objective of this problem is to accurately predict the load experienced by the aircraft wing structure during flight determined from a set of calibrated load and gage response relationship. We can then model the problem as a black box input-output system identification from which the system parameter has to be estimated. Traditional LS (Least Square) techniques and the issues of noisy data and model accuracy are addressed. A statistical bound reflecting the change in residual is derived in order to understand the effects of the perturbations on the data. Due to the intrinsic nature of the LS problem, LS solution faces the dilemma of the trade off between model accuracy and noise sensitivity. A method of conflicting performance indices is presented, thus allowing us to improve the noise sensitivity while at the same time configuring the degredation of the model accuracy. SVD techniques for data reduction are studied and the equivalence of the Correspondence Analysis (CA) and Total Least Squares Criteria are proved. We also looked at nonlinear LS problems with NASA F-111 data set as an example. Conventional methods are neither easily applicable nor suitable for the specific load problem since the exact model of the system is unknown. Neural Network (NN) does not require prior information on the model of the system. This robustness motivated us to apply the NN techniques on our load problem. Simulation results for the NN methods used in both the single load and the 'warning signal' problems are both useful and encouraging. The performance of the NN (for single load estimate) is better than the LS approach, whereas no conventional approach was tried for the 'warning signals' problems. The NN design methodology is also presented. The use of SVD, CA and Collinearity Index methods are used to reduce the number of neurons in a layer.

Kong, Jeffrey↗
NASA NTRS1994

Using optical-microwave synergy for estimating surface energy fluxes over semi-arid rangeland

First results of the Walnut Gulch '92 (Arizona, U.S.) experiment concerning the combined use of radar backscattering (ERS-1) and thermal infrared (LANDSAT TM (Thematic Mapper)) data to estimate surface sensible heat flux are reported. The first step investigates the potential use of ERS-1 SAR (Synthetic Aperture Radar) images for surface soil moisture monitoring of the watershed using five calibrated images acquired during the year 1992 (dry to wet conditions). Results show that despite the typical low level of biomass of semi arid rangeland, an attenuation of the soil backscatter (up to 2 dB) can occur during the rainy season mainly due to the vegetation characteristics. A statistical relationship is then used to retrieve the volumetric surface soil moisture from ERS-1 backscattering (sensitivity of 0.23 dB/% moisture) with a resulting root mean square error of 1.3% of soil moisture. In a second step a semi empirical approach based on energy balance relates soil temperatures to this estimated surface soil moisture. Vegetation temperature is then deduced from soil temperatures and LANDSAT TM composite temperature in order to estimate sensible heat flux according to a two layer type model providing an RMSE of 29 W/sq m.

Troufleau, D.↗
NASA NTRS2008

Five-Year Wilkinson Microwave Anisotropy Probe (WMAP)Observations: Beam Maps and Window Functions

Cosmology and other scientific results from the WMAP mission require an accurate knowledge of the beam patterns in flight. While the degree of beam knowledge for the WMAP one-year and three-year results was unprecedented for a CMB experiment, we have significantly improved the beam determination as part of the five-year data release. Physical optics fits are done on both the A and the B sides for the first time. The cutoff scale of the fitted distortions on the primary mirror is reduced by a factor of approximately 2 from previous analyses. These changes enable an improvement in the hybridization of Jupiter data with beam models, which is optimized with respect to error in the main beam solid angle. An increase in main-beam solid angle of approximately 1% is found for the V2 and W1-W4 differencing assemblies. Although the five-year results are statistically consistent with previous ones, the errors in the five-year beam transfer functions are reduced by a factor of approximately 2 as compared to the three-year analysis. We present radiometry of the planet Jupiter as a test of the beam consistency and as a calibration standard; for an individual differencing assembly. errors in the measured disk temperature are approximately 0.5%.

Hill, R.S.↗
NASA NTRS2007

Recent Short Term Global Aerosol Trends over Land and Ocean Dominated by Biomass Burning

NASA's MODIS instrument on board the Terra satellite is one of the premier tools to assess aerosol over land and ocean because of its high quality calibration and consistency. We analyze Terra-MODIS's seven year record of aerosol optical depth (AOD) observations to determine whether global aerosol has increased or decreased during this period. This record shows that AOD has decreased over land and increased over ocean. Only the ocean trend is statistically significant and corresponds to an increase in AOD of 0.009, or a 15% increase from background conditions. The strongest increasing trends occur over regions and seasons noted for strong biomass burning. This suggests that biomass burning aerosol dominates the increasing trend over oceans and mitigates the otherwise mostly negative trend over the continents.

Remer, Lorraine A.↗
NASA NTRS2004

Evaluation of a Multi-Parameter Sensor for Automated, Continuous Cell Culture Monitoring in Bioreactors

Compact and automated sensors are desired for assessing the health of cell cultures in biotechnology experiments in microgravity. Measurement of cell culture medium allows for the optirn.jzation of culture conditions on orbit to maximize cell growth and minimize unnecessary exchange of medium. While several discrete sensors exist to measure culture health, a multi-parameter sensor would simplify the experimental apparatus. One such sensor, the Paratrend 7, consists of three optical fibers for measuring pH, dissolved oxygen (p02), dissolved carbon dioxide (pC02) , and a thermocouple to measure temperature. The sensor bundle was designed for intra-arterial placement in clinical patients, and potentially can be used in NASA's Space Shuttle and International Space Station biotechnology program bioreactors. Methods: A Paratrend 7 sensor was placed at the outlet of a rotating-wall perfused vessel bioreactor system inoculated with BHK-21 (baby hamster kidney) cells. Cell culture medium (GTSF-2, composed of 40% minimum essential medium, 60% L-15 Leibovitz medium) was manually measured using a bench top blood gas analyzer (BGA, Ciba-Corning). Results: A Paratrend 7 sensor was used over a long-term (>120 day) cell culture experiment. The sensor was able to track changes in cell medium pH, p02, and pC02 due to the consumption of nutrients by the BHK-21. When compared to manually obtained BGA measurements, the sensor had good agreement for pH, p02, and pC02 with bias [and precision] of 0.02 [0.15], 1 mm Hg [18 mm Hg], and -4.0 mm Hg [8.0 mm Hg] respectively. The Paratrend oxygen sensor was recalibrated (offset) periodically due to drift. The bias for the raw (no offset or recalibration) oxygen measurements was 42 mm Hg [38 mm Hg]. The measured response (rise) time of the sensor was 20 +/- 4s for pH, 81 +/- 53s for pC02, 51 +/- 20s for p02. For long-term cell culture measurements, these response times are more than adequate. Based on these findings , the Paratrend sensor could offer automated, continuous monitoring of cell cultures with a temporal resolution of 1 minute, which is not attainable by sampling via handheld blood analyzer (i-STAT). Conclusion: The resulting bias and precision found in these cell culture-based studies is comparable to Paratrend sensor clinical results. Although the large error in p02 measurements (+/-18 mm Hg) may be acceptable for clinical applications, where Paratrend values are periodically adjusted to a BGA measurement, the O2 sensor in this bundle may not be reliable enough for the single-calibration requirement of sensors used in NASA's bioreactors. The pH and pC02 sensors in the bundle are reliable and stable over the measurement period, and can be used without recalibration to measure cell cultures in rn.jcrogravity biotechnology experiments. Future work will test additional Paratrend sensors to provide statistical assessment of sensor performance.

Pappas, D.↗
NASA NTRS2014

OMMYDCLD: a New A-train Cloud Product that Co-locates OMI and MODIS Cloud and Radiance Parameters onto the OMI Footprint

Clouds cover approximately 60% of the earth's surface. When obscuring the satellite's field of view (FOV), clouds complicate the retrieval of ozone, trace gases and aerosols from data collected by earth observing satellites. Cloud properties associated with optical thickness, cloud pressure, water phase, drop size distribution (DSD), cloud fraction, vertical and areal extent can also change significantly over short spatio-temporal scales. The radiative transfer models used to retrieve column estimates of atmospheric constituents typically do not account for all these properties and their variations. The OMI science team is preparing to release a new data product, OMMYDCLD, which combines the cloud information from sensors on board two earth observing satellites in the NASA A-Train: Aura/OMI and Aqua/MODIS. OMMYDCLD co-locates high resolution cloud and radiance information from MODIS onto the much larger OMI pixel and combines it with parameters derived from the two other OMI cloud products: OMCLDRR and OMCLDO2. The product includes histograms for MODIS scientific data sets (SDS) provided at 1 km resolution. The statistics of key data fields - such as effective particle radius, cloud optical thickness and cloud water path - are further separated into liquid and ice categories using the optical and IR phase information. OMMYDCLD offers users of OMI data cloud information that will be useful for carrying out OMI calibration work, multi-year studies of cloud vertical structure and in the identification and classification of multi-layer clouds.

OMMYDCLD↗
NASA NTRS1986

Flight evaluation of a precision landing task for a powered-lift STOL aircraft

A flight research experiment was conducted with the NASA-Ames Research Center's Quiet Short-Haul Research Aircraft to determine the factors which influence the touchdown distribution for a powered-lift STOL aircraft. The pilots were given two tasks for each of a series of precision approaches flown using a microwave landing system (MLS) in simulated instrument meteorological conditions. They flew the aircraft, with forward vision obscured by a screen, to a 100-ft decision height using a flightpath-oriented, color electronic display and one of four levels of control augmentation. Approaches were flown along a nominal 6 deg glidepath, as well as to calibrated offsets at the decision height to establish a variety of initial conditions for the landing task. The screen was removed at the decision height and the pilot was briefed to land in a 200 foot touchdown zone of the STOLport with a sink rate less than 5 ft/sec. Statistical performance envelopes and pilot ratings are used to describe the results of this experiment. The data generated are expected to be useful for establishing STOL aircraft operating requirements and STOL MLS approach criteria.

Watson, D. M.↗
NASA NTRS1990

Nimbus 7 SMMR precipitation observations calibrated against surface radar during TAMEX

This paper compares recent (Petty and Katsaros, 1990) satellite passive microwave observations of tropical cloud clusters over the South China Sea, using the 37-GHz channels of the Nimbus-7 SMMR, to the surface digital radar observations of oceanic precipitation during the Taiwan Area Mesoscale Experiment (TAMEX) conducted in May and June, 1987 (Kuo and Chen, 1990). The data confirm the existence of useful statistical relationships between surface rainfall parameters and satellite microwave observations. It is suggested that the approach applied in this study can be expanded to include other microwave frequencies (for example, the 19- and 85-GHz channels of the SSM/I)

Petty, Grant W.↗
NASA NTRS2002

Comparison of Two Methods for Estimating the Sampling-Related Uncertainty of Satellite Rainfall Averages Based on a Large Radar Data Set

The uncertainty of rainfall estimated from averages of discrete samples collected by a satellite is assessed using a multi-year radar data set covering a large portion of the United States. The sampling-related uncertainty of rainfall estimates is evaluated for all combinations of 100 km, 200 km, and 500 km space domains, 1 day, 5 day, and 30 day rainfall accumulations, and regular sampling time intervals of 1 h, 3 h, 6 h, 8 h, and 12 h. These extensive analyses are combined to characterize the sampling uncertainty as a function of space and time domain, sampling frequency, and rainfall characteristics by means of a simple scaling law. Moreover, it is shown that both parametric and non-parametric statistical techniques of estimating the sampling uncertainty produce comparable results. Sampling uncertainty estimates, however, do depend on the choice of technique for obtaining them. They can also vary considerably from case to case, reflecting the great variability of natural rainfall, and should therefore be expressed in probabilistic terms. Rainfall calibration errors are shown to affect comparison of results obtained by studies based on data from different climate regions and/or observation platforms.

Lau, William K. M.↗
NASA NTRSDate not supplied

Estimating Bidirectional Reflectance and Monitoring Stability of SNPP-VIIRS Reflective Solar Bands Using A Deep Neural Network

The NASA Clouds and the Earth's Radiant Energy System project provides the scientific community with observed top-of-atmosphere shortwave and longwave fluxes for climate monitoring and climate model validation. To provide consistent VIIRS cloud retrievals, the CERES Imager and Geostationary Calibration Group (IGCG) must understand and quantify the stability of the VIIRS instruments. To achieve this, the IGCG utilizes tropical deep convective clouds (DCCs) as invariant targets. Proper seasonal characterization of the DCC bidirectional reflectance distribution function (BRDF) is key to the success of DCC-based calibration methods, particularly for shortwave infrared (SWIR) bands. This article proposes the use of a deep neural network (DNN) to characterize VIIRS solar reflective band BRDF reflectance, with which individual channel trends are isolated by manipulating the DNN time input. Initial results show that the DNN method can extract statistically significant SNPP-VIIRS band trends, using only SNPP-VIIRS inputs, that are correlative to and match the magnitude of significant trends determined using methods that rely on an external angular distribution model. It may be possible to apply this approach to actively monitor the stability of new instruments without the need for predetermined seasonal BRDF corrections.

Benjamin Scarino↗
NASA NTRS1993

Digital test signal generation: An accurate SNR calibration approach for the DSN

In support of the on-going automation of the Deep Space Network (DSN) a new method of generating analog test signals with accurate signal-to-noise ratio (SNR) is described. High accuracy is obtained by simultaneous generation of digital noise and signal spectra at the desired bandwidth (base-band or bandpass). The digital synthesis provides a test signal embedded in noise with the statistical properties of a stationary random process. Accuracy is dependent on test integration time and limited only by the system quantization noise (0.02 dB). The monitor and control as well as signal-processing programs reside in a personal computer (PC). Commands are transmitted to properly configure the specially designed high-speed digital hardware. The prototype can generate either two data channels modulated or not on a subcarrier, or one QPSK channel, or a residual carrier with one biphase data channel. The analog spectrum generated is on the DC to 10 MHz frequency range. These spectra may be up-converted to any desired frequency without loss on the characteristics of the SNR provided. Test results are presented.

Gutierrez-Luaces, Benito O.↗
NASA NTRS2017

Comparison of Passive Microwave-Derived Early Melt Onset Records on Arctic Sea Ice

Two long records of melt onset (MO) on Arctic sea ice from passive microwave brightness temperatures (Tbs) obtained by a series of satellite-borne instruments are compared. The Passive Microwave (PMW) method and Advanced Horizontal Range Algorithm (AHRA) detect the increase in emissivity that occurs when liquid water develops around snow grains at the onset of early melting on sea ice. The timing of MO on Arctic sea ice influences the amount of solar radiation absorbed by the ice-ocean system throughout the melt season by reducing surface albedos in the early spring. This work presents a thorough comparison of these two methods for the time series of MO dates from 1979through 2012. The methods are first compared using the published data as a baseline comparison of the publically available data products. A second comparison is performed on adjusted MO dates we produced to remove known differences in inter-sensor calibration of Tbs and masking techniques used to develop the original MO date products. These adjustments result in a more consistent set of input Tbs for the algorithms. Tests of significance indicate that the trends in the time series of annual mean MO dates for the PMW and AHRA are statistically different for the majority of the Arctic Ocean including the Laptev, E. Siberian, Chukchi, Beaufort, and central Arctic regions with mean differences as large as 38.3 days in the Barents Sea. Trend agreement improves for our more consistent MO dates for nearly all regions. Mean differences remain large, primarily due to differing sensitivity of in-algorithm thresholds and larger uncertainties in thin-ice regions.

sea ice↗
NASA NTRS1979

Applied regional monitoring of the vernal advancement and retrogradation (green wave effect) of natural vegetation in the Great Plains corridor

The author has identified the following significant results. Rangelands in southwest Texas were used to establish threshold values and limitations on measuring herbaceous biomass under typical arid and semi-arid range conditions. Previous regression relationships established between ND6 and green biomass for two different ecosystems were similar. The west Texas data set for brush-free sites was too small to be statistically conclusive. It appears that a line with a third (and steeper) slope would be best for the west Texas data, and that line would intersect the other two. Results show that similar relationships exist between ND6 and green biomass under low brush canopy cover conditions, but local variations require a calibration to determine the best fit for an ecosystem. The brush canopy has a detrimental effect on the ND6 vs. herbaceous green biomass relationship.

Harlan, J. C.↗