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This report provides the results of two independent evaluations, an absolute and a relative assessment, of the geopositional accuracy of the Earth Satellite (EarthSat) Corporation's GeoCover orthorectified Landsat Enhanced Thematic Mapper Plus (ETM+) imagery. This imagery was purchased through NASA's Earth Science Enterprise (ESE) Scientific Data Purchase (SDP) program.
This paper documents a study that drove the development of a mathematical expression in the minimum operational performance standards (MOPS) of detect-and-avoid (DAA) systems for unmanned aircraft systems (UAS). This equation describes the conditions under which vertical maneuver guidance could be provided during recovery of well clear separation with a non-cooperative VFR aircraft in addition to horizontal maneuver guidance. Although suppressing vertical maneuver guidance in these situations increased the minimum horizontal separation from 500 to 800 feet, the maximum severity of loss of well clear increased in about 35 of the encounters compared to when a vertical maneuver was preferred and allowed. Additionally, analysis of individual cases led to the identification of a class of encounter where vertical rate error had a large effect on horizontal maneuvers due to the difficulty of making the correct left-right turn decision: crossing conflict with intruder changing altitude. These results supported allowing vertical maneuvers when UAS vertical performance exceeds the relative vertical position and velocity accuracy of the DAA tracker given the current velocity of the UAS and the relative vertical position and velocity estimated by the DAA tracker. Looking ahead, these results indicate a need to improve guidance algorithms by utilizing maneuver stability and near mid-air collision risk when determining maneuver guidance to regain well clear separation.
This study involved the evaluation of the characteristics of multispectral scanner data relative to forest cover type mapping, using NASA's NS-001 multispectral scanner to simulate the proposed Thematic Mapper (TM). The objectives were to determine: (1) the optimum number of wavebands to utilize in computer classifications of TM data; (2) which channel combinations provide the highest expected classification accuracy; and (3) the relative merit of each channel in the context of the cover classes examined. Transformed divergence was used as a measure of statistical distance between spectral class densities associated with each of twelve cover classes. The maximum overall mean pair-wise transformed divergence was used as the basis for evaluating all possible waveband combinations available for use in computer-assisted forest cover classifications.
The paper studies with finite difference nonlinear circulation models the uncertainties in interesting flow properties, such as western boundary current transport, potential and kinetic energy, owing to the uncertainty in the driving surface boundary condition. The procedure is based upon nonlinear optimization methods. The same calculations permit quantitative study of the importance of new information as a function of type, region of measurement and accuracy, providing a method to study various observing strategies. Uncertainty in a model parameter, the bottom friction coefficient, is studied in conjunction with uncertain measurements. The model is free to adjust the bottom friction coefficient such that an objective function is minimized while fitting a set of data to within prescribed bounds. The relative importance of the accuracy of the knowledge about the friction coefficient with respect to various kinds of observations is then quantified, and the possible range of the friction coefficients is calculated.
The relatively large antenna subarrays (tens of meters) to be used in the Solar Power Satellite, and the desire to accurately quantify antenna performance, dictate the requirement for specialized measurement techniques. The error contributors associated with both far-field and near-field antenna measurement concepts were quantified. As a result, instrumentation configurations with measurement accuracy potential were identified. In every case, advances in the state of the art of associated electronics were found to be required. Relative cost trade-offs between a candidate far-field elevated antenna range and near-field facility were also performed.
High dispersion long wave redundant (LWR) spectra are analyzed for the differential velocity between hot and cool components of heretofore single lined spectroscopic binaries with late type giant or supergiant primaries. Cross correlation of a composite spectrum against early and late type standard stars yields relative velocities with an accuracy of 0.2 to 0.3 kms. When the orbit of the primay is known, the differential measurement from IUE gives the mass ratio of the system. Low dispersion short wave prime (SWP) and LWR flux spectra are used together with ground-based photometry to disentangle the composite energy distributions of the binaries. Temperatures of both components, their relative luminosities, and the reddening of the system are obtained. Assuming the hot secondaries to be main sequence stars, their probable luminosities and masses may be obtained from their temperatures. Then absolute magnitudes and masses may be obtained for the evolved primaries with more confidence than with existing techniques.
Use of luminescent paints for the measurement of global pressures on wind tunnel model surfaces requires a full understanding of the inherent accuracy of the technique. Theoretical emission of the paint luminophor follows the well known Stern-Volmer relation. Inherent in this relation are fundamental limits to achievable sensitivity and accuracy. Equations for relative error in pressure as a function of relative signal intensity (emittance), relative error in pressure as a function of pressure, and the relationship between sensitivity and pressure are derived and represented graphically.
Root Mean Square Errors (RMSE) in the soil moisture anomaly time series obtained from the Advanced Scatterometer (ASCAT) and the Advanced Microwave Scanning Radiometer (AMSR-E; using the Land Parameter Retrieval Model) are estimated over a continental scale domain centered on North America, using two methods: triple colocation (RMSETC ) and error propagation through the soil moisture retrieval models (RMSEEP ). In the absence of an established consensus for the climatology of soil moisture over large domains, presenting a RMSE in soil moisture units requires that it be specified relative to a selected reference data set. To avoid the complications that arise from the use of a reference, the RMSE is presented as a fraction of the time series standard deviation (fRMSE). For both sensors, the fRMSETC and fRMSEEP show similar spatial patterns of relatively highlow errors, and the mean fRMSE for each land cover class is consistent with expectations. Triple colocation is also shown to be surprisingly robust to representativity differences between the soil moisture data sets used, and it is believed to accurately estimate the fRMSE in the remotely sensed soil moisture anomaly time series. Comparing the ASCAT and AMSR-E fRMSETC shows that both data sets have very similar accuracy across a range of land cover classes, although the AMSR-E accuracy is more directly related to vegetation cover. In general, both data sets have good skill up to moderate vegetation conditions.
NASA's long-range plan for the study of solar-terrestrial relations includes a Solar Probe Mission in which a spacecraft is put into an eccentric orbit with perihelion near 4 solar radii (0.02 AU). The scientific experiments which might be done with such a mission are discussed. Topics include the distribution of mass within the Sun, solar angular momentum, the fine structure of the solar surface and corona, the acceleration of the solar wind and energetic particles, and the evolution of interplanetary dust. The mission could also contribute to high-accuracy tests of general relativity and the search for cosmic gravitational radiation.
This report summarizes a review of the literature regarding propeller noise prediction methods. The review is divided into six sections: (1) early methods; (2) more recent methods based on earlier theory; (3) more recent methods based on the Acoustic Analogy; (4) more recent methods based on Computational Acoustics; (5) empirical methods; and (6) broadband methods. The report concludes that there are a large number of noise prediction procedures available which vary markedly in complexity. Deficiencies in accuracy of methods in many cases may be related, not to the methods themselves, but the accuracy and detail of the aerodynamic inputs used to calculate noise. The steps recommended in the report to provide accurate and easy to use prediction methods are: (1) identify reliable test data; (2) define and conduct test programs to fill gaps in the existing data base; (3) identify the most promising prediction methods; (4) evaluate promising prediction methods relative to the data base; (5) identify and correct the weaknesses in the prediction methods, including lack of user friendliness, and include features now available only in research codes; (6) confirm the accuracy of improved prediction methods to the data base; and (7) make the methods widely available and provide training in their use.
Some of the disadvantages relating to altitude stability and proximity to the ocean are described for radio oceanography studies using aircraft. The random oscillatory motion introduced by the autopilot in maintaining aircraft altitude requires a more sophisticated range tracker for a radar altimeter than would be required in a satellite application. One-dimensional simulations of the sea surface (long-crested waves) are performed using both the JONSWAP spectrum and the Pierson-Moskowitz spectrum. The results of the simulation indicate that care must be taken in trying to experimentally verify instrument measurement accuracy. Because of the relatively few wavelengths examined from an aircraft due to proximity to the ocean and low velocity compared to a satellite, the random variation in the sea surface parameters being measured can far exceed an instrument's ability to measure them.
The Guidance, Navigation, and Control Center (GNCC) at Goddard Space Flight Center (GSFC) has successfully developed high-accuracy autonomous satellite navigation systems using the National Aeronautics and Space Administration's (NASA's) space and ground communications systems and the Global Positioning System (GPS). In addition, an autonomous navigation system that uses celestial object sensor measurements is currently under development and has been successfully tested using real Sun and Earth horizon measurements.The GNCC has developed advanced spacecraft systems that provide autonomous navigation and control of formation flyers in near-Earth, high-Earth, and libration point orbits. To support this effort, the GNCC is assessing the relative navigation accuracy achievable for proposed formations using GPS, intersatellite crosslink, ground-to-satellite Doppler, and celestial object sensor measurements. This paper evaluates the performance of these relative navigation approaches for three proposed missions with two or more vehicles maintaining relatively tight formations. High-fidelity simulations were performed to quantify the absolute and relative navigation accuracy as a function of navigation algorithm and measurement type. Realistically-simulated measurements were processed using the extended Kalman filter implemented in the GPS Enhanced Inboard Navigation System (GEONS) flight software developed by GSFC GNCC. Solutions obtained by simultaneously estimating all satellites in the formation were compared with the results obtained using a simpler approach based on differencing independently estimated state vectors.
During the 1998 Convection and Moisture Experiment (CAMEX-3), the first hurricane wind field measurements with Doppler lidar were achieved. Wind fields were mapped within the eye, along the eyewall, in the central dense overcast, and in the marine boundary layer encompassing the inflow region. Spatial coverage was determined primarily by cloud distribution and opacity. Within optically-thin cirrus slant range of 20- 25 km was achieved, whereas no propagation was obtained during penetration of dense cloud. Measurements were obtained with the Multi-center Airborne Coherent Atmospheric Wind Sensor (MACAWS) on the NASA DC-8 research aircraft. MACAWS was developed and operated cooperatively by the atmospheric lidar remote sensing groups of NOAA Environmental Technology Laboratory, NASA Marshall Space Flight Center, and Jet Propulsion Laboratory. A pseudo-dual Doppler technique ("co-planar scanning") is used to map the horizontal component of the wind at several vertical levels. Pulses from the laser are directed out the left side of the aircraft in the desired directions using computer-controlled rotating prisms. Upon exiting the aircraft, the beam is completely eyesafe. Aircraft attitude and speed are taken into account during real-time signal processing, resulting in determination of the ground-relative wind to an accuracy of about 1 m/s magnitude and about 10 deg direction. Beam pointing angle errors are about 0.1 deg, equivalent to about 17 m at 10 km. Horizontal resolution is about 1 km (along-track) for typical signal processor and scanner settings; vertical resolution varies with range. Results from CAMEX-3 suggest that scanning Doppler wind lidar can complement airborne Doppler radar by providing wind field measurements in regions that are devoid of hydrometeors. At present MACAWS observations are being assimilated into experimental forecast models and satellite Doppler wind lidar simulations to evaluate the relative impact.
The navigational accuracy of an oceangoing vessel using conventional GPS p-code data is examined. The GPS signal is transmitted over two carrier frequencies in the L-band at 1575.42 and 1227.6 MHz. Achievable navigational uncertainties of differenced positional estimates are presented as a function of the parameters of the problem, with particular attention given to the effect of sea-state, user equivalent range error, uncompensated antenna motion, varying delay intervals, and reduced data rate examined in the unaided mode. The unmodeled errors resulting from satellite ephemeris uncertainties are shown to be negligible for the GPS-NDS (Navigation Development) satellites. Requirements are met in relatively calm seas, but accuracy degradation by a factor of at least 2 must be anticipated in heavier sea states. The aided mode of operation is examined, and it is shown that requirements can be met by using an inertial measurement unit (IMU) to aid the GPS receiver operation. Since the use of an IMU would mean higher costs, direct Doppler from the GPS satellites is presented as a viable alternative.
Inaccurate prediction of aircraft trajectory by ground-based decision support tools (DST) is a major concern in air traffic management (ATM). Aircraft trajectory prediction tools rely on a simplified point-mass aircraft performance model (APM) to make their predictions. Even though the performance coefficients and weight of an aircraft are a vital part of the APM’s predictions and accuracy, these coefficients are proprietary in nature and therefore, unavailable to DSTs. Current ATM research focuses on improving the estimate of some APM parameters by freezing all other coefficients. This simplified approach introduces unwanted sources of bias and negatively impacts the accuracy of the performance model. In this paper, we apply machine learning (ML) techniques for the simultaneous prediction of three key APM parameters (two drag coefficients and the initial aircraft weight). To accomplish this, we employ an ordinary differential equation (ODE) fitting approach to generate optimized APM parameter labels customized to each individual flight record. Subsequently, we train ML models to capture the relationship between the historical data and the optimized APM parameters. Two different ML model solutions are applied and APM coefficients are predicted for unseen flights. The results indicate that the ML models are able to capture the relationship between APM parameters and flight-related features with good accuracy.
This paper evaluates several navigation approaches for the first phase of the Magnetospheric Multiscale (MMS) mission, which consists of a tetrahedral formation of four satellites in highly eccentric Earth orbits of approximately 1.2 by 12 Earth radii at an inclination of 10 degrees. The inter-satellite separation is approximately 10 kilometers near apogees. Navigation approaches were studied using ground station m g e =d two-way Doppler measurements, Global Positioning System (GPS) pseudorange measurements, crosslink range measurements among the members flying in formation, and various combinations of these measurement types. An absolute position accuracy of 10 kilometers or better can be achieved with most of the approaches studied and a relative position accuracy of 100 meters or better can be achieved at apogee in some cases. Among the various approaches studied, the approaches that use a combination of GPS and crosslink measurements were found to be more reliable in terms of absolute and relative navigation accuracies and operational flexibility.
Commercial companies such as Maxar, PlanetScope, and BlackSky have launched many satellites with revisit times ranging from two hours to one day and have built large archives of high resolution (1-3 m) Earth observing data. The high temporal resolution and global coverage of these satellites makes commercial satellite images ideal for scientists studying rapidly changing processes such as flooding and fires. A key step in assessing changes in these images is co-registration of various images to each other. High geolocation accuracy (at most 0.5 pixels of offset) allows for easy co-registration of images across different times and sensors. Here, we assess the latest PlanetScope imagery and evaluate it for geolocation accuracy. For our assessment, we compare the target image to a reference image with known geolocation accuracy (WorldView imagery) and determine the offset between these images by shifting them to maximize their Pearson Cross-Correlation (PCC) value. Offsets required to maximize the PCC give the geolocation accuracy of the target image relative to the reference image. Previously, our global assessment of Planet data revealed large variability in geolocation accuracy from one continent to another. The measured root mean squared errors (RMSEs) range from 5.4 m in North America to 14.9 m in Africa. We have updated this previous assessment to include both their newest SuperDove series as well as a more robust assessment of the temporal stability of PlanetScope's geolocation accuracy.
We present here a query processing method that produces approximate answers to queries posed in standard relational algebra. This method is monotone in the sense that the accuracy of the approximate result improves with the amount of time spent producing the result. This strategy enables us to trade the time to produce the result for the accuracy of the result. An approximate relational model that characterizes appromimate relations and a partial order for comparing them is developed. Relational operators which operate on and return approximate relations are defined.