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NASA NTRS1990

Cloud altitude determination from infrared spectral radiances

The CO2 slicing method is generally recognized as the most accurate means of inferring cloud altitude from passive infrared radiance observations. The method is applicable to semi-transparent and broken clouds. During the cirrus FIRE and COHMEX field experiments, CO2 channel radiance data suitable for cloud altitude specification were achieved from moderate spectral resolution satellite sounders (NOAA-TOVS and GOES-VAS) and from a High spectral resolution Interferometer Spectrometer (HIS) flown on the NASA U2/ER2 aircraft. Also aboard the ER2 was a down-looking active lidar unit capable of providing cloud top pressure verifications with high accuracy. A third instrument, the Multispectral Atmospheric Mapping Sensor (MAMS) provided 50 meter resolution infrared window data which is used wtih radiosonde data to verify the heights of middle and low level clouds. Comparisons of lidar and MAMS/radiosonde ground truth cloud heights are made with those determined from: high resolution (0.5/cm) HIS spectra, HIS spectra degraded to the moderate resolution (15/cm) of the VAS/TOVS instruments, and spectrally averaged HIS radiances for individual pairs of VAS spectral channels. The results show that the best results are achieved from high resolution spectra; the RMS difference with the ground truth is 23 mb. The RMS differences between the infrared radiance determination and ground truth increase by 35 percent when the spectral resolution is degraded to the moderate spectral resolution of the VAS/TOVS instruments and by 52 to 183 percent, depending upon channel combinations, when only two spectral channels at VAS/TOVS spectral resolution are used.

Smith, William L.↗

NASA NTRS1991

Radar modeling of a boreal forest

Microwave modeling, ground truth, and SAR data are used to investigate the characteristics of forest stands. A mixed coniferous forest stand has been modeled at P, L, and C bands. Extensive measurements of ground truth and canopy geometry parameters were performed in a 200-m-square hemlock-dominated forest plot. About 10 percent of the trees were sampled to determine a distribution of diameter at breast height (DBH). Hemlock trees in the forest are modeled by characterizing tree trunks, branches, and needles as randomly oriented lossy dielectric cylinders whose area and orientation distributions are prescribed. The distorted Born approximation is used to compute the backscatter at P, L, and C bands. The theoretical results are found to be lower than the calibrated ground-truth data. The experiment and model results agree quite closely, however, when the ratios of VV to HH and HV to HH are compared.

Chauhan, Narinder S.↗

NASA NTRS1991

Explanation-based generalization of partially ordered plans

Most previous work in analytic generalization of plans dealt with totally ordered plans. These methods cannot be directly applied to generalizing partially ordered plans, since they do not capture all interactions among plan operators for all total orders of such plans. We introduce a new method for generalizing partially ordered plans. This method is based on providing explanation-based generalization (EBG) with explanations which systematically capture the interactions among plan operators for all the total orders of a partially-ordered plan. The explanations are based on the Modal Truth Criterion which states the necessary and sufficient conditions for ensuring the truth of a proposition at any point in a plan, for a class of partially ordered plans. The generalizations obtained by this method guarantee successful and interaction-free execution of any total order of the generalized plan. In addition, the systematic derivation of the generalization algorithms from the Modal Truth Criterion obviates the need for carrying out a separate formal proof of correctness of the EBG algorithms.

Kambhampati, Subbarao↗

NASA NTRS2002

Earth Observing-1 Advanced Land Imager Flight Performance Assessment: Absolute Radiometry and Stability During the First Year

The absolute radiometry of the Advanced Land Imager during the first year on orbit (November 21,2000 - November 21, 2001) is presented. Results derived from solar, lunar, ground truth, and internal reference lamp measurements are presented. An 18% drop in the radiometric response of the Band 1p data since preflight calibration at Lincoln Laboratory is observed using all techniques. This decrease cannot be accounted for by preflight calibration errors, stray light, or contamination of the focal plane. A slight drooping of the VNIR response toward the blue and a 5-12% increase in the Band 5 response is also apparent in all the data. Radiometric response correction factors have been calculated and preflight calibration coefficients have been updated in order to provide +/- 5% agreement between the measured solar, lunar, and ground truth data and the expected values. The radiometric stability of the ALI during the first year of operation is also presented for each spectral band. Internal reference lamp data indicate the focal plane has been stable to within 1% for bands 1p, 1, 2, 5p, 5, 7, pan and 3% for Bands 3,4, 4p since launch. Solar, lunar, and ground truth measurements indicate the optical train and solar diffuser of the instrument has been stable to within 1% since initial measurements on orbit in late December 2000.

Mendenhall, J. A.↗

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 NTRS2013

Orion Exploration Flight Test-1 Contingency Drogue Deploy Velocity Trigger

As a backup to the GPS-aided Kalman filter and the Barometric altimeter, an "adjusted" velocity trigger is used during entry to trigger the chain of events that leads to drogue chute deploy for the Orion Multi-Purpose Crew Vehicle (MPCV) Exploration Flight Test-1 (EFT-1). Even though this scenario is multiple failures deep, the Orion Guidance, Navigation, and Control (GN&C) software makes use of a clever technique that was taken from the Mars Science Laboratory (MSL) program, which recently successfully landing the Curiosity rover on Mars. MSL used this technique to jettison the heat shield at the proper time during descent. Originally, Orion use the un-adjusted navigated velocity, but the removal of the Star Tracker to save costs for EFT-1, increased attitude errors which increased inertial propagation errors to the point where the un-adjusted velocity caused altitude dispersions at drogue deploy to be too large. Thus, to reduce dispersions, the velocity vector is projected onto a "reference" vector that represents the nominal "truth" vector at the desired point in the trajectory. Because the navigation errors are largely perpendicular to the truth vector, this projection significantly reduces dispersions in the velocity magnitude. This paper will detail the evolution of this trigger method for the Orion project and cover the various methods tested to determine the reference "truth" vector; and at what point in the trajectory it should be computed.

Gay, Robert S.↗

NASA NTRS2016

Avoiding Stair-Step Artifacts in Image Registration for GOES-R Navigation and Registration Assessment

In developing software for independent verification and validation (IVV) of the Image Navigation and Registration (INR) capability for the Geostationary Operational Environmental Satellite R Series (GOES-R) Advanced Baseline Imager (ABI), we have encountered an image registration artifact which limits the accuracy of image offset estimation at the subpixel scale using image correlation. Where the two images to be registered have the same pixel size, subpixel image registration preferentially selects registration values where the image pixel boundaries are close to lined up. Because of the shape of a curve plotting input displacement to estimated offset, we call this a stair-step artifact. When one image is at a higher resolution than the other, the stair-step artifact is minimized by correlating at the higher resolution. For validating ABI image navigation, GOES-R images are correlated with Landsat-based ground truth maps. To create the ground truth map, the Landsat image is first transformed to the perspective seen from the GOES-R satellite, and then is scaled to an appropriate pixel size. Minimizing processing time motivates choosing the map pixels to be the same size as the GOES-R pixels. At this pixel size image processing of the shift estimate is efficient, but the stair-step artifact is present. If the map pixel is very small, stair-step is not a problem, but image correlation is computation-intensive. This paper describes simulation-based selection of the scale for truth maps for registering GOES-R ABI images.

stair-step artifact↗

NASA NTRS2016

Avoiding Stair-Step Artifacts in Image Registration for GOES-R Navigation and Registration Assessment

image registration↗

NASA NTRS2017

Evaluation of the Simple Safe Site Selection (S4) Hazard Detection Algorithm Using Helicopter Field Test Data

Small scale terrain hazards, such as rocks, slopes, and craters, can pose significant risk to landing spacecraft and rover or payload deployment. Onboard Hazard Detection and Avoidance (HDA) systems scan and analyze the landing area for these hazards in real time during descent, and divert the spacecraft to the safest touchdown site. The computationally efficient Simple Safe Site Selection (S4) algorithm combined with a flash LIDAR is an HDA system geared towards small robotic spacecraft. Rather than creating and analyzing a digital elevation map (DEM) from potentially many overlapping range images, S4 operates directly on a single flash LIDAR image. Extending prior work that has analyzed S4 performance for Mars landing using extensive simulations, this paper evaluates S4 performance using actual flash LIDAR images of an artificial hazard field acquired during a 2014 helicopter field test in Death Valley, CA. In particular, we describe LIDAR characterization and calibration, creation of ground truth elevation and safety maps, creation of ground truth sensor poses, actual S4 algorithm processing, and performance analysis. The results show that the safety cost images produced by S4 are remarkably close to the ground truth safety map (computed offline by an HDA algorithm developed under the Autonomous Landing and Hazard Avoidance (ALHAT) project) at significantly reduced computational cost, confirming S4 as a viable candidate algorithm for onboard spacecraft HDA.

Luna, Michael E.↗

NASA NTRSDate not supplied

QuantifyML: How good is my machine learning model?

This paper presents an approach, QuantifyML, which employs model counting to assess the learnability and robustness of machine learning models. Typically the efficacy of machine learning models is determined by computing their accuracy statistically on test data sets. However, this may be misleading, if the test data is not representative of the problem that is being studied. Further, two different models may have the same accuracy on a given data set, measured statistically, but may be very different in their behavior on unseen data. Also, models with high accuracy could have poor adversarial robustness. In QuantifyML, our goal is to precisely quantify the extent to which machine learning models have learned and generalized from the given data. In QuantifyML, a trained model is translated into a C program, which is fed to the CBMC model checking tool to produce a formula in Conjunctive Normal Form (CNF), which in turn is analyzed with state-of-the-art model counters to efficiently obtain precise counts w.r.t different outputs. QuantifyML enables i) evaluating the learnability of models by comparing the counts for the outputs to ground truth, expressed as logical predicates (if available), ii) comparing the performance of different models that may be built with different machine learning algorithms (e.g., decision-trees vs. neural networks), and iii) quantifying the robustness of trained models around given inputs. Our evaluation demonstrates these applications of QuantifyML on decision trees and neural networks trained to learn relational properties of graphs, for which we know the ground truth, and to perform image classification, for which we do not have the ground truth, but we can quantify local robustness.

Deep Neural Networks↗

NASA NTRSDate not supplied

Ground to Air Testing of a Fused Optical-Radar Aircraft Detection and Tracking System

Onboard detection and tracking capability are integral to the sensing component in collision avoidance systems needed to safely operate autonomous urban air taxis and small Unmanned Aircraft Systems. Ground-based validation of detection and tracking systems is an important milestone towards the end goal of real-time collision avoidance using onboard sensors and algorithms. In this work, we evaluate three Extended Kalman Filter(EKF)based fusion trackers with radar and vision detection inputs, and compare them with baseline trackers for each sensor type. Performance is assessed using field collected data of ground to air test flights with the sensors co-located on a stable platform with an instrumented multirotor acting as the intruder performing a waypoint pattern at a distance of1.1km to 0.3km to simulate a head-on collision geometry. Fusing an image-based morphological detector with a radar detector using an EKF covered 74% of the ground truth position updates logged by the flight controller on the multirotor within 50 meters after accounting for alignment offsets while covering 15% more ground truth updates relative to radar only. Removing timestamps when the intruder aircraft is occluded by trees and only considering timestamps where the radar has an update, the EKF image-based morphological detector combined with the radar detector covered 90% of the of the ground truth position updates within 50metersand 97% within 100 meters.

Chester V Dolph↗

NASA NTRSDate not supplied

A PPE Use Case on Configuration Management Approach for MBSE

Systems engineers worldwide have been working to implement Model-based Systems Engineering (MBSE) environments, tools, and methodologies. MBSE is a formalized application of modeling to support systems engineering, including requirements, design, analysis, verification, and validation activities over the project’s lifecycle[1]; MBSE captures the system data into a digital environment. Significant benefits of MBSE includes a reduction in the time in performing systems engineering activities and an improvement higher fidelity data production. As more Systems Engineers are using MBSE, the models it produces are becoming the source of truth for Systems Engineering artifacts. As we move towards using these models as the source of truth, a more rigorous Configuration Management (CM) infrastructure is needed. Many of the MBSE tools provide CM options but utilizing them efficiently and effectively can be challenging. More rigorous methods and tools are needed to assist with keeping track of changes in the model, making sure inadvertent changes to baseline data did not occur, visibility of changes in the different model versions, and the impacts of changes to the models. System engineers and configuration management personnel from the Power and Propulsion Element (PPE) project at NASA Glenn Research Center have been working to develop a modeling construct that allows models to be the source of truth and maintain a configuration managed baseline. This paper presents a process that leverages the existing CM tools and describes how PPE used this process to manage changes more rigorously. It will describe the process behind building the model architecture that utilizes the MBSE tool capabilities and the configuration management process. It will contain some of the advantages and disadvantages of the architecture that the PPE project had settled upon utilizing, as well as some enhanced capabilities that the PPE MBSE team has developed.

MBSE↗

NASA NTRS1972

Spectral reflectance measurements of plant soil combinations

Field and laboratory observations of plant and soil reflectance spectra were made to develop an understanding of the reflectance of solar energy by plants and soils. A related objective is the isolation of factors contributing to the image formed by multispectral scanners and return beam vidicons carried by ERTS or film-filter combinations used in the field or on aircraft. A set of objective criteria are to be developed for identifying plant and soil types and their changing condition through the seasons for application of space imagery to resource management. This is because the global scale of earth observations satellites requires objective rather than subjective techniques, particularly where ground truth is either not available or too costly to acquire. As the acquiring of ground truth for training sets may be impractical in many cases, attempts have been made to identify objectively standard responses which could be used for image interpretation.

Macleod, N. H.↗

NASA NTRS1972

Discriminant analyses of Bendix scanner data

Flights over Weslaco, Texas are discussed, using the 9-channel Bendix scanner, providing calibrated data in the 380 to 1000 nm wavelength interval. These flights were at 2000 ft. These data gave seasonal coverage from the time signals, representing mainly the soil background. The ground truth data are provided; signature processing studies relating scanner data to ground truth were also carried out.

Richardson, A. J.↗

NASA NTRS1972

Investigation of techniques for correcting ERTS data for solar and atmospheric effects

The author has identified the following significant results. The design and fabrication of five radiant power measuring instruments (RPMI) for ERTS ground truth have been completed. These instruments will be deployed in concert with ERTS overflights to obtain radiometric measurements needed to determine solar and atmospheric parameters that effect ERTS radiance measurements. With these parameters, the accuracy and capability of various procedures for transforming ERTS data into absolute target reflectance signatures will be evaluated. The RPMI is a rugged, hand-carried instrument accurately calibrated to measure both downwelling and reflected radiance within each ERTS multispectral scanner band. A foldover handle permits a quick change from wide angle global or sky irradiance measurements to narrow angle radiance measurements from sky and ground targets. These measurements yield ground truth site reflectance and permit calculation of additional parameters such as beam transmittance between spacecraft and ground, and path radiance (path reflectance).

Rogers, R. H.↗

NASA NTRS1973

A study to explore the use of orbital remote sensing to determine native arid plant distribution

The author has identified the following significant results. A theory has been developed of a method for determining the reflectivities of natural areas from ERTS-1 data. This method requires the following measurements: (1) ground truth reflectivity data from two different calibration areas; (2) radiance data from ERTS-1 MSS imagery for the same two calibration areas; and (3) radiance data from ERTS-1 MSS imagery for the area(s) in which reflectivity is to be determined. The method takes into account sun angle effects and atmospheric effects on the radiance seen by the space sensor. If certain assumptions are made, the ground truth data collection need not be simultaneous with the ERTS-1 overflight. The method allows the calculation of a conversion factor for converting ERTS-1 MSS radiance measurements of a given overflight to reflectivity values. This conversion factor can be used to determine the reflectivity of any area in the general vicinity of the calibration areas which has a relatively similar overlying atmosphere. This method, or some modification of it, may be useful in ERTS investigations which require the determination of spectral signatures of areas from spacecraft data.

Mcginnies, W. G.↗

NASA NTRS1973

Analysis of usefulness of ERTS-1 MSS data in detecting and measuring coastal marshes

The author has identified the following significant results. The usefulness of ERTS-1 data in detecting and measuring coastal marshes has been analyzed. The data chosen for study was taken over the Houston Area Test Site on August 29, 1972. A study site was selected which contained marshes of varying size. Using a computerized clustering algorithm which groups areas of spectral homogeneity, it was possible to distinguish twenty-five classes or features. To determine the total acreage of the marshes, the pure picture elements were counted. Using a technique developed by the team, the boundary picture elements were also counted. Ground truth was provided from rectified, enlarged, and scaled high altitude aircraft photography acquired during the same time frame. Comparison of the ground truth coverage depicted by the aircraft photography to the clustering acreage displayed from the ERTS-1 data showed a percentage of accuracy ranging from 89% to 99% for determining areal extent of coastal marshes.

Erb, R. B.↗

NASA NTRS1973

Study to demonstrate the feasibility of and determine the optimum method of remote haze monitoring by satellite

The author has identified the following significant results. Ground truth data has been obtained in order to determine the amount of haze present at the time of ERTS-1 passes over the Los Angeles area. October 21, 1972 was the haziest day, that was essentially cloud free, to date. At the time of the next pass, November 8, 1972 this area was quite clear. Changes in terrain features are minimized because these were consecutive passes. Digital tapes of the ERTS-1 data from these two days are being analyzed to determine the effects of haze on the data, in order to determine the optimum method for monitoring haze from a satellite. Preliminary results indicate that a slight reduction in contrast and some distortion of spectral signatures are caused by heavy haze. This effect is thought to be sufficient to determine the presence of moderate haze without the benefit of ground truth data. It is significant to note that there is very little degradation of ERTS-1 data caused be a rather heavy haze. For many purposes the data obtained on a hazy day are just as useful as that obtained on a clear day.

Rogers, E. H.↗