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At least 91 records · Page 5

Radiometric Calibration Techniques for Signal-of-Opportunity Reflectometers

Bi-static reflection measurements utilizing global navigation satellite service (GNSS) or other signals of opportunity (SoOp) can be used to sense ocean and terrestrial surface properties. End-to-end calibration of GNSS-R has been performed using well-characterized reflection surface (e.g., water), direct path antenna, and receiver gain characterization. We propose an augmented approach using on-board receiver electronics for radiometric calibration of SoOp reflectometers utilizing direct and reflected signal receiving antennas. The method calibrates receiver and correlator gains and offsets utilizing a reference switch and common noise source. On-board electronic calibration sources, such as reference switches, noise diodes and loop-back circuits, have shown great utility in stabilizing total power and correlation microwave radiometer and scatterometer receiver electronics in L-band spaceborne instruments. Application to SoOp instruments is likely to bring several benefits. For example, application to provide short and long time scale calibration stability of the direct path channel, especially in low signal-to-noise ratio configurations, is directly analogous to the microwave radiometer problem. The direct path channel is analogous to the loopback path in a scatterometer to provide a reference of the transmitted power, although the receiver is independent from the reflected path channel. Thus, a common noise source can be used to measure the gain ratio of the two paths. Using these techniques long-term (days to weeks) calibration stability of spaceborne L-band scatterometer and radiometer has been achieved better than 0.1. Similar long-term stability would likely be needed for a spaceborne reflectometer mission to measure terrestrial properties such as soil moisture.

calibrating

Orthogonal subspaces for correlation masking

A digital correlation mask that induces orthogonality among a prescribed set of reference imagery is described. In this particular implementation, the resulting correlation is undersampled and shift-variant, though if it is applied to optical correlators, those limitations are removed. A method of introducing orthogonality among the weights among the training set from which filter values are obtained is derived, so that the correlation value from a given filter is representative of the unique nature of the reference object as compared against the other objects in the training class.

Juday, Richard D.

Remote Sensing of Cloud Top Height from SEVIRI: Analysis of Eleven Current Retrieval Algorithms

The role of clouds remains the largest uncertainty in climate projections. They influence solar and thermal radiative transfer and the earth's water cycle. Therefore, there is an urgent need for accurate cloud observations to validate climate models and to monitor climate change. Passive satellite imagers measuring radiation at visible to thermal infrared (IR) wavelengths provide a wealth of information on cloud properties. Among others, the cloud top height (CTH) - a crucial parameter to estimate the thermal cloud radiative forcing - can be retrieved. In this paper we investigate the skill of ten current retrieval algorithms to estimate the CTH using observations from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) onboard Meteosat Second Generation (MSG). In the first part we compare ten SEVIRI cloud top pressure (CTP) data sets with each other. The SEVIRI algorithms catch the latitudinal variation of the CTP in a similar way. The agreement is better in the extratropics than in the tropics. In the tropics multi-layer clouds and thin cirrus layers complicate the CTP retrieval, whereas a good agreement among the algorithms is found for trade wind cumulus, marine stratocumulus and the optically thick cores of the deep convective system. In the second part of the paper the SEVIRI retrievals are compared to CTH observations from the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP) and Cloud Profiling Radar (CPR) instruments. It is important to note that the different measurement techniques cause differences in the retrieved CTH data. SEVIRI measures a radiatively effective CTH, while the CTH of the active instruments is derived from the return time of the emitted radar or lidar signal. Therefore, some systematic differences are expected. On average the CTHs detected by the SEVIRI algorithms are 1.0 to 2.5 kilometers lower than CALIOP observations, and the correlation coefficients between the SEVIRI and the CALIOP data sets range between 0.77 and 0.90. The average CTHs derived by the SEVIRI algorithms are closer to the CPR measurements than to CALIOP measurements. The biases between SEVIRI and CPR retrievals range from −0.8 kilometers to 0.6 kilometers. The correlation coefficients of CPR and SEVIRI observations vary between 0.82 and 0.89. To discuss the origin of the CTH deviation, we investigate three cloud categories: optically thin and thick single layer as well as multi-layer clouds. For optically thick clouds the correlation coefficients between the SEVIRI and the reference data sets are usually above 0.95. For optically thin single layer clouds the correlation coefficients are still above 0.92. For this cloud category the SEVIRI algorithms yield CTHs that are lower than CALIOP and similar to CPR observations. Most challenging are the multi-layer clouds, where the correlation coefficients are for most algorithms between 0.6 and 0.8. Finally, we evaluate the performance of the SEVIRI retrievals for boundary layer clouds. While the CTH retrieval for this cloud type is relatively accurate, there are still considerable differences between the algorithms. These are related to the uncertainties and limited vertical resolution of the assumed temperature profiles in combination with the presence of temperature inversions, which lead to ambiguities in the CTH retrieval. Alternative approaches for the CTH retrieval of low clouds are discussed.

Hamann, U.

Gas correlation lidar for methane detection

A new type of DIAL system for the detection of methane in the atmosphere is being developed. The main feature of this lidar is the use of a gas correlation technique to obtain the reference signal by means of a single laser pulse, instead of two shots at different wavelengths. This fact is useful to make measurements on fast moving platforms. To meet the infrared absorption band of methane an optical parametric oscillator (OPO) was used with a LiNbO3 crystal as active element, and a tuning range between 1.5 divided by 4 microns. As known, the major problem to overcome in parametric oscillators are the pump beam quality and the difficulty in reducing the linewidth. The first requirement is met by using, as a pump, a Nd-YAG laser based on a new type of resonator cavity, named SFUR (Self Filtering Unstable Resonator). The laser emits, with high efficiency, near diffraction limited pulsed beams of about 250 mJ of energy, 20 ns of duration at 10 pps of frequency repetition rate. On the other hand, the gas correlation technique allows the operation with a bandwidth as large as 1/cm, which is obtainable using only a diffraction grating as a dispersive element in the OPO cavity.

Galletti, E.

Influence of free-stream disturbances on boundary-layer transition

Considerable experimental evidence exists which shows that free stream disturbances (the ratio of root-mean-square pressure fluctuations to mean values) in conventional wind tunnels increase with increasing Mach number at low supersonic to moderate hypersonic speeds. In addition to local conditions, the free stream disturbance level influences transition behavior on simple test models. Based on this observation, existing noise transition data obtained in the same test facility were correlated for a large number of reference sharp cones and flat plates and are shown to collapse along a single curve. This result is a significant improvement over previous attempts to correlate noise transition data.

Harvey, W. D.

Accurate Magnetometer/Gyroscope Attitudes Using a Filter with Correlated Sensor Noise

Magnetometers and gyroscopes have been shown to provide very accurate attitudes for a variety of spacecraft. These results have been obtained, however, using a batch-least-squares algorithm and long periods of data. For use in onboard applications, attitudes are best determined using sequential estimators such as the Kalman filter. When a filter is used to determine attitudes using magnetometer and gyroscope data for input, the resulting accuracy is limited by both the sensor accuracies and errors inherent in the Earth magnetic field model. The Kalman filter accounts for the random component by modeling the magnetometer and gyroscope errors as white noise processes. However, even when these tuning parameters are physically realistic, the rate biases (included in the state vector) have been found to show systematic oscillations. These are attributed to the field model errors. If the gyroscope noise is sufficiently small, the tuned filter 'memory' will be long compared to the orbital period. In this case, the variations in the rate bias induced by field model errors are substantially reduced. Mistuning the filter to have a short memory time leads to strongly oscillating rate biases and increased attitude errors. To reduce the effect of the magnetic field model errors, these errors are estimated within the filter and used to correct the reference model. An exponentially-correlated noise model is used to represent the filter estimate of the systematic error. Results from several test cases using in-flight data from the Compton Gamma Ray Observatory are presented. These tests emphasize magnetometer errors, but the method is generally applicable to any sensor subject to a combination of random and systematic noise.

Sedlak, J.

Computer-aided analysis of Landsat data for surveying Texas coastal zone environments

The feasibility of using machine-aided processing of Landsat data to inventory environmental units was studied by analyzing geometrically corrected and spatially registered Landsat data collected over the Matagorda Bay area of the Texas coastal estuarine system. A clustering algorithm (nonsupervised processor) was used to divide the data into groups of sample points of similar spectral characteristics, and correlation of spectral classes with reference data on a point-to-point basis showed the coastal features exhibit unique spectral variations. Use of a maximum likelihood algorithm permitted discrimination of 13 terrestrial and aquatic environments.

Kristof, S. J.

Correlation spectrometer having high resolution and multiplexing capability

A correlation spectrometer permanently incorporates a reference cell and an electro-optical phase modulator (EOPM) in the light path between a sample cell and a detector. The effect of the EOPM is such that its frequency modulates all of the monochromatic component of the incoherent radiation passing through it. The EOPM is adjusted so that when it is ON all of the energy in the monochromatic components is thrown into sidebands differing from the original frequencies by integral multiples of the modulation frequency with the total amount of energy absorbed from the original radiation remaining constant. When there is no coincidence between the constituents in the two cells, the detector's output is the same when the EOPM is ON and when it is OFF. However, when there is coincidence the detector's output changes when the EOPM is switched between its two states. The change in the detector's output is related to the quantity of the constituents in the sample cell.

Margolis, J. S.

On the electron affinity of Be2

Calculations of the electron affinity (EA) of Be2 using a large Slater-type orbital basis set and extensive correlation based upon a CASSCF reference are reported. The adiabatic EAs are estimated to be 0.44 eV for the 2Sigma sub g(+) state and 0.56 eV for the 2Pi sub u state. The extra electron attaches into an empty bonding orbital, causing a shortening of the bond length and an increase in omega(e). The D(e) of the 2Pi sub u state of Be2 is six times as large as the D(e) of Be2.

Bauschlicher, C. W., Jr.

Positive ions of the first- and second-row transition metal hydrides

Theoretical dissociation energies for the first- and second-row transition metal hydride positive ions are critically compared against recent experimental values obtained from ion beam reactive scattering methods. Theoretical spectroscopic parameters and dipole moments are presented for the ground and several low-lying excited states. The calculations employ large Gaussian basis sets and account for electron correlation using the single-reference single- and double-excitation configuration interaction and coupled-pair-functional methods. The Darwin and mass-velocity contributions to the relativistic energy are included in the all-electron calculations on the first-row systems using first-order perturbation theory, and in the second-row systems using the Hay and Wadt relativistic effective core potentials. The theoretical D(0) values for the second-row transition metal hydride positive ions should provide a critical measure of the experimental values, which are not as refined as many of those in the first transition row.

Pettersson, Lars G. M.

Optical Recognition And Tracking Of Objects

Separate objects moving independently tracked simultaneously. System uses coherent optical techniques to obtain correlation between each object and reference image. Moving objects monitored by charge-coupled-device television camera, output fed to liquid-crystal television (LCTV) display. Acting as spatial light modulator, LCTV impresses images of moving objects on collimated laser beam. Beam spatially low-pass filtered to remove high-spatial-frequency television grid pattern.

Chao, Tien-Hsin

The role of computerized modeling and simulation in the development of life support system technologies

Computerized modeling and simulation (CMAS) is a tool that can greatly reduce both the time and cost of technology development. CMAS refers to computer methods for correlating, storing, and retrieving property data for chemical species and for solving the phenomenological equations of physical/chemical processes. Furthermore, process conditions based on properties of materials, mass, and energy balances; equipment sizing based on rate processes; and the governing equations for unit operations can be determined using CMAS. CMAS systems can be used to evaluate an LSS process with minimal requirements for laboratory experimentation. A CMAS model is presented for a vapor compression distillation system(VCD) for reclaiming water from urine.

Modell, Michael

Real-time edge-enhanced optical correlator

Edge enhancement of an input image by four-wave mixing a first write beam with a second write beam in a photorefractive crystal, GaAs, was achieved for VanderLugt optical correlation with an edge enhanced reference image by optimizing the power ratio of a second write beam to the first write beam (70:1) and optimizing the power ratio of a read beam, which carries the reference image to the first write beam (100:701). Liquid crystal TV panels are employed as spatial light modulators to change the input and reference images in real time.

Liu, Tsuen-Hsi

Real-Time Optical Correlator Based On GaAs

Apparatus performs correlation between input image and reference image in real time by means of degenerate four-wave mixing in photorefractive crystal, which serves as real-time holographic medium. Gallium arsenide chosen to be photorefractive material in this application because at frame rate and level of illumination used in experiments, offers adequate diffraction efficiency. Frame rates as high as 1,000 s to negative 1st power achievable.

Liu, Tsuen-Hsi

Daily evaluation of 26 precipitation datasets using Stage-IV gauge-radar data for the CONUS

New precipitation (P) datasets are released regularly, following innovations in weather forecasting models, satellite retrieval methods, and multi-source merging techniques. Using the conterminous US as a case study, we evaluated the performance of 26 gridded (sub-)daily P datasets to obtain insight into the merit of these innovations. The evaluation was performed at a daily timescale for the period 2008–2017 using the Kling–Gupta efficiency (KGE), a performance metric combining correlation, bias, and variability. As a reference, we used the high-resolution (4 km) Stage-IV gauge-radar P dataset. Among the three KGE components, the P datasets performed worst overall in terms of correlation (related to event identification). In terms of improving KGE scores for these datasets, improved P totals (affecting the bias score) and improved distribution of P intensity (affecting the variability score) are of secondary importance. Among the 11 gauge-corrected P datasets, the best overall performance was obtained by MSWEP V2.2, underscoring the importance of applying daily gauge corrections and accounting for gauge reporting times. Several uncorrected P datasets outperformed gauge-corrected ones. Among the 15 uncorrected P datasets, the best performance was obtained by the ERA5-HRES fourth-generation reanalysis, reflecting the significant advances in earth system modeling during the last decade. The (re)analyses generally performed better in winter than in summer, while the opposite was the case for the satellite-based datasets. IMERGHH V05 performed substantially better than TMPA-3B42RT V7, attributable to the many improvements implemented in the IMERG satellite P retrieval algorithm. IMERGHH V05 outperformed ERA5-HRES in regions dominated by convective storms, while the opposite was observed in regions of complex terrain. The ERA5-EDA ensemble average exhibited higher correlations than the ERA5-HRES deterministic run, highlighting the value of ensemble modeling. The WRF regional convection-permitting climate model showed considerably more accurate P totals over the mountainous west and performed best among the uncorrected datasets in terms of variability, suggesting there is merit in using high-resolution models to obtain climatological P statistics. Our findings provide some guidance to choose the most suitable P dataset for a particular application.

Hylke E. Beck

A Heuristic Approach to Correlating ERAM Flight Data from Twenty Centers

Among its many other functions, the Federal Aviation Administration’s En Route Automation Modernization (ERAM) provides external systems with real-time air traffic data for flights in enroute airspace in the National Airspace System. It replaced the En Route Host computer and backup system used at 20 FAA Air Route Traffic Control Centers (Centers) nationwide. Among the new features of ERAM, its output data stream of flight plan and track data includes a unique identifier for a flight originating in any one of the 20 ERAM Centers. The unique identifier, called the Global Unique Flight Identifier (GUFI), is persistent across all the Centers that track the flight. However, certain factors make it difficult to correlate data using the GUFI. First, the value of the GUFI is only unique within a time window of seven days. Second, the GUFI is attached only to flight-plan related data messages. Finally, track positions reported by ERAM do not reference the GUFI. In order to correlate historical as well as real time flight-plan and position related ERAM data, an efficient, heuristic approach was developed, and a prototype was developed. The approach showed that the processing speed, through parallel processing, is sufficient to correlate ERAM data in real-time. As described in this paper, when there are multiple track positions reported from multiple Centers within a few seconds, each position is assigned with a weighted score to indicate the quality of the position relative to its last know position. The weighted score can be used to eliminate potentially duplicate track positions. The approach is database-agnostic, and can be implemented in a Big Data system such as an Apache Hadoop system, as well as in traditional database systems.

Correlating ERAM Flight Data