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At least 739 records · Page 41

Algorithm for Detection of Ground and Canopy Cover in Micropulse Photon-Counting Lidar Altimeter Data in Preparation for the ICESat-2 Mission

NASA's Ice, Cloud and Land Elevation Satellite-II (ICESat-2) mission is a decadal survey mission (2016 launch). The mission objectives are to measure land ice elevation, sea ice freeboard, and changes in these variables, as well as to collect measurements over vegetation to facilitate canopy height determination. Two innovative components will characterize the ICESat-2 lidar: 1) collection of elevation data by a multibeam system and 2) application of micropulse lidar (photon-counting) technology. A photon-counting altimeter yields clouds of discrete points, resulting from returns of individual photons, and hence new data analysis techniques are required for elevation determination and association of the returned points to reflectors of interest. The objective of this paper is to derive an algorithm that allows detection of ground under dense canopy and identification of ground and canopy levels in simulated ICESat-2 data, based on airborne observations with a Sigma Space micropulse lidar. The mathematical algorithm uses spatial statistical and discrete mathematical concepts, including radial basis functions, density measures, geometrical anisotropy, eigenvectors, and geostatistical classification parameters and hyperparameters. Validation shows that ground and canopy elevation, and hence canopy height, can be expected to be observable with high accuracy by ICESat-2 for all expected beam energies considered for instrument design (93.01%-99.57% correctly selected points for a beam with expected return of 0.93 mean signals per shot (msp), and 72.85%-98.68% for 0.48 msp). The algorithm derived here is generally applicable for elevation determination from photoncounting lidar altimeter data collected over forested areas, land ice, sea ice, and land surfaces, as well as for cloud detection.

Algorithms↗

On recursive least-squares filtering algorithms and implementations

In many real-time signal processing applications, fast and numerically stable algorithms for solving least-squares problems are necessary and important. In particular, under non-stationary conditions, these algorithms must be able to adapt themselves to reflect the changes in the system and take appropriate adjustments to achieve optimum performances. Among existing algorithms, the QR-decomposition (QRD)-based recursive least-squares (RLS) methods have been shown to be useful and effective for adaptive signal processing. In order to increase the speed of processing and achieve high throughput rate, many algorithms are being vectorized and/or pipelined to facilitate high degrees of parallelism. A time-recursive formulation of RLS filtering employing block QRD will be considered first. Several methods, including a new non-continuous windowing scheme based on selectively rejecting contaminated data, were investigated for adaptive processing. Based on systolic triarrays, many other forms of systolic arrays are shown to be capable of implementing different algorithms. Various updating and downdating systolic algorithms and architectures for RLS filtering are examined and compared in details, which include Householder reflector, Gram-Schmidt procedure, and Givens rotation. A unified approach encompassing existing square-root-free algorithms is also proposed. For the sinusoidal spectrum estimation problem, a judicious method of separating the noise from the signal is of great interest. Various truncated QR methods are proposed for this purpose and compared to the truncated SVD method. Computer simulations provided for detailed comparisons show the effectiveness of these methods. This thesis deals with fundamental issues of numerical stability, computational efficiency, adaptivity, and VLSI implementation for the RLS filtering problems. In all, various new and modified algorithms and architectures are proposed and analyzed; the significance of any of the new method depends crucially on specific application.

Hsieh, Shih-Fu↗

Probabilistic computer model of optimal runway turnoffs

Landing delays are currently a problem at major air carrier airports and many forecasters agree that airport congestion will get worse by the end of the century. It is anticipated that some types of delays can be reduced by an efficient optimal runway exist system allowing increased approach volumes necessary at congested airports. A computerized Probabilistic Runway Turnoff Model which locates exits and defines path geometry for a selected maximum occupancy time appropriate for each TERPS aircraft category is defined. The model includes an algorithm for lateral ride comfort limits.

Schoen, M. L.↗

Marine stratocumulus cloud fields off the coast of southern California observed using Landsat imagery. I - Structural characteristics

The structural characteristics of stratocumulus cloud fields off the coast of southern California are investigated using Landsat Multispectral Scanner imagery. Twelve scenes in this area are examined along with three other stratocumulus scenes near San Francisco, over central Oregon, and in the Gulf of Mexico. Results from this initial study of stratocumulus clouds indicate that cloud-background threshold selection techniques based upon edge detection gradient assumptions are not appropriate for cloud segmentation and classification algorithms, cloud size distributions obey a power law, and cell horizontal aspect ratio increases with cell diameter. It was also found that stratocumulus clouds are bifractal in nature with fractal dimension of d of about 1.2 for cells with diameter D smaller than 0.5 km and d of about 1.5 for cells with D greater than 0.5 km; stratocumulus cloud fields appear to be homogeneous over regions of about 100 km x 100 km, a much smaller region than the 2.5-deg x 2.5-deg boxes to be used in the ISCCP regional averaging algorithms; and that structural properties of stratocumulus clouds observed off the coast of southern California are similar to those observed for stratocumulus clouds at three other locations.

Welch, R. M.↗

Performance seeking control excitation mode

Flight testing of the performance seeking control (PSC) excitation mode was successfully completed at NASA Dryden on the F-15 highly integrated digital electronic control (HIDEC) aircraft. Although the excitation mode was not one of the original objectives of the PSC program, it was rapidly prototyped and implemented into the architecture of the PSC algorithm, allowing valuable and timely research data to be gathered. The primary flight test objective was to investigate the feasibility of a future measurement-based performance optimization algorithm. This future algorithm, called AdAPT, which stands for adaptive aircraft performance technology, generates and applies excitation inputs to selected control effectors. Fourier transformations are used to convert measured response and control effector data into frequency domain models which are mapped into state space models using multiterm frequency matching. Formal optimization principles are applied to produce an integrated, performance optimal effector suite. The key technical challenge of the measurement-based approach is the identification of the gradient of the performance index to the selected control effector. This concern was addressed by the excitation mode flight test. The AdAPT feasibility study utilized the PSC excitation mode to apply separate sinusoidal excitation trims to the controls - one aircraft, inlet first ramp (cowl), and one engine, throat area. Aircraft control and response data were recorded using on-board instrumentation and analyzed post-flight. Sensor noise characteristics, axial acceleration performance gradients, and repeatability were determined. Results were compared to pilot comments to assess the ride quality. Flight test results indicate that performance gradients were identified at all flight conditions, sensor noise levels were acceptable at the frequencies of interest, and excitations were generally not sensed by the pilot.

Schkolnik, Gerard↗

The Impact of Atmospheric InfraRed Sounder (AIRS) Profiles on Short-term Weather Forecasts

The Atmospheric Infrared Sounder (AIRS), together with the Advanced Microwave Sounding Unit (AMSU), represents one of the most advanced spacebased atmospheric sounding systems. The combined AlRS/AMSU system provides radiance measurements used to retrieve temperature profiles with an accuracy of 1 K over 1 km layers under both clear and partly cloudy conditions, while the accuracy of the derived humidity profiles is 15% in 2 km layers. Critical to the successful use of AIRS profiles for weather and climate studies is the use of profile quality indicators and error estimates provided with each profile Aside form monitoring changes in Earth's climate, one of the objectives of AIRS is to provide sounding information of sufficient accuracy such that the assimilation of the new observations, especially in data sparse region, will lead to an improvement in weather forecasts. The purpose of this paper is to describe a procedure to optimally assimilate highresolution AIRS profile data in a regional analysis/forecast model. The paper will focus on the impact of AIRS profiles on a rapidly developing east coast storm and will also discuss preliminary results for a 30-day forecast period, simulating a quasi-operation environment. Temperature and moisture profiles were obtained from the prototype version 5.0 EOS science team retrieval algorithm which includes explicit error information for each profile. The error profile information was used to select the highest quality temperature and moisture data for every profile location and pressure level for assimilation into the ARPS Data Analysis System (ADAS). The AIRS-enhanced analyses were used as initial fields for the Weather Research and Forecast (WRF) system used by the SPORT project for regional weather forecast studies. The ADASWRF system will be run on CONUS domain with an emphasis on the east coast. The preliminary assessment of the impact of the AIRS profiles will focus on quality control issues associated with AIRS, intelligent use of the quality indicators, and forecast verification.

Chou, Shih-Hung↗

Methodology for Prototyping Increased Levels of Automation for Spacecraft Rendezvous Functions

The Crew Exploration Vehicle necessitates higher levels of automation than previous NASA vehicles, due to program requirements for automation, including Automated Rendezvous and Docking. Studies of spacecraft development often point to the locus of decision-making authority between humans and computers (i.e. automation) as a prime driver for cost, safety, and mission success. Therefore, a critical component in the Crew Exploration Vehicle development is the determination of the correct level of automation. To identify the appropriate levels of automation and autonomy to design into a human space flight vehicle, NASA has created the Function-specific Level of Autonomy and Automation Tool. This paper develops a methodology for prototyping increased levels of automation for spacecraft rendezvous functions. This methodology is used to evaluate the accuracy of the Function-specific Level of Autonomy and Automation Tool specified levels of automation, via prototyping. Spacecraft rendezvous planning tasks are selected and then prototyped in Matlab using Fuzzy Logic techniques and existing Space Shuttle rendezvous trajectory algorithms.

Hart, Jeremy J.↗

2D/3D Visual Tracker for Rover Mast

A visual-tracker computer program controls an articulated mast on a Mars rover to keep a designated feature (a target) in view while the rover drives toward the target, avoiding obstacles. Several prior visual-tracker programs have been tested on rover platforms; most require very small and well-estimated motion between consecutive image frames a requirement that is not realistic for a rover on rough terrain. The present visual-tracker program is designed to handle large image motions that lead to significant changes in feature geometry and photometry between frames. When a point is selected in one of the images acquired from stereoscopic cameras on the mast, a stereo triangulation algorithm computes a three-dimensional (3D) location for the target. As the rover moves, its body-mounted cameras feed images to a visual-odometry algorithm, which tracks two-dimensional (2D) corner features and computes their old and new 3D locations. The algorithm rejects points, the 3D motions of which are inconsistent with a rigid-world constraint, and then computes the apparent change in the rover pose (i.e., translation and rotation). The mast pan and tilt angles needed to keep the target centered in the field-of-view of the cameras (thereby minimizing the area over which the 2D-tracking algorithm must operate) are computed from the estimated change in the rover pose, the 3D position of the target feature, and a model of kinematics of the mast. If the motion between the consecutive frames is still large (i.e., 3D tracking was unsuccessful), an adaptive view-based matching technique is applied to the new image. This technique uses correlation-based template matching, in which a feature template is scaled by the ratio between the depth in the original template and the depth of pixels in the new image. This is repeated over the entire search window and the best correlation results indicate the appropriate match. The program could be a core for building application programs for systems that require coordination of vision and robotic motion.

Bajracharya, Max↗

Investigation of scene identification algorithms for radiation budget measurements

The computation of Earth radiation budget from satellite measurements requires the identification of the scene in order to select spectral factors and bidirectional models. A scene identification procedure is developed for AVHRR SW and LW data by using two radiative transfer models. These AVHRR GAC pixels are then attached to corresponding ERBE pixels and the results are sorted into scene identification probability matrices. These scene intercomparisons show that there generally is a higher tendency for underestimation of cloudiness over ocean at high cloud amounts, e.g., mostly cloudy instead of overcast, partly cloudy instead of mostly cloudy, for the ERBE relative to the AVHRR results. Reasons for this are explained. Preliminary estimates of the errors of exitances due to scene misidentification demonstrates the high dependency on the probability matrices. While the longwave error can generally be neglected the shortwave deviations have reached maximum values of more than 12% of the respective exitances.

Diekmann, F. J.↗

Investigation of scene identification algorithms for radiation budget measurements

The computation of earth radiation budget from satellite measurements requires the identification of the scene in order to select spectral factors and bidirectional models. A scene identification procedure is developed for AVHRR SW and LW data by using two radiative transfer models. These AVHRR GAC pixels are then attached to corresponding ERBE pixels and the results are sorted into scene identification probability matrices. These scene intercomparisons show that there generally is a higher tendency for underestimation of cloudiness over ocean at high cloud amounts, e.g., mostly cloudy instead of overcast, partly cloudy instead of mostly cloudy, for the ERBE relative to the AVHRR results. Reasons for this are explained. Preliminary estimates of the errors of exitances due to scene misidentification demonstrates the high dependency on the probability matrices. While the longwave error can generally be neglected the shortwave deviations have reached maximum values of more than 12 percent of the respective exitances.

Diekmann, F. J.↗

Investigation for improving Global Positioning System (GPS) orbits using a discrete sequential estimator and stochastic models of selected physical processes

GEODYNII is a conventional batch least-squares differential corrector computer program with deterministic models of the physical environment. Conventional algorithms were used to process differenced phase and pseudorange data to determine eight-day Global Positioning system (GPS) orbits with several meter accuracy. However, random physical processes drive the errors whose magnitudes prevent improving the GPS orbit accuracy. To improve the orbit accuracy, these random processes should be modeled stochastically. The conventional batch least-squares algorithm cannot accommodate stochastic models, only a stochastic estimation algorithm is suitable, such as a sequential filter/smoother. Also, GEODYNII cannot currently model the correlation among data values. Differenced pseudorange, and especially differenced phase, are precise data types that can be used to improve the GPS orbit precision. To overcome these limitations and improve the accuracy of GPS orbits computed using GEODYNII, we proposed to develop a sequential stochastic filter/smoother processor by using GEODYNII as a type of trajectory preprocessor. Our proposed processor is now completed. It contains a correlated double difference range processing capability, first order Gauss Markov models for the solar radiation pressure scale coefficient and y-bias acceleration, and a random walk model for the tropospheric refraction correction. The development approach was to interface the standard GEODYNII output files (measurement partials and variationals) with software modules containing the stochastic estimator, the stochastic models, and a double differenced phase range processing routine. Thus, no modifications to the original GEODYNII software were required. A schematic of the development is shown. The observational data are edited in the preprocessor and the data are passed to GEODYNII as one of its standard data types. A reference orbit is determined using GEODYNII as a batch least-squares processor and the GEODYNII measurement partial (FTN90) and variational (FTN80, V-matrix) files are generated. These two files along with a control statement file and a satellite identification and mass file are passed to the filter/smoother to estimate time-varying parameter states at each epoch, improved satellite initial elements, and improved estimates of constant parameters.

Goad, Clyde C.↗

GIFTS SM EDU Level 1B Algorithms

The Geosynchronous Imaging Fourier Transform Spectrometer (GIFTS) SensorModule (SM) Engineering Demonstration Unit (EDU) is a high resolution spectral imager designed to measure infrared (IR) radiances using a Fourier transform spectrometer (FTS). The GIFTS instrument employs three focal plane arrays (FPAs), which gather measurements across the long-wave IR (LWIR), short/mid-wave IR (SMWIR), and visible spectral bands. The raw interferogram measurements are radiometrically and spectrally calibrated to produce radiance spectra, which are further processed to obtain atmospheric profiles via retrieval algorithms. This paper describes the GIFTS SM EDU Level 1B algorithms involved in the calibration. The GIFTS Level 1B calibration procedures can be subdivided into four blocks. In the first block, the measured raw interferograms are first corrected for the detector nonlinearity distortion, followed by the complex filtering and decimation procedure. In the second block, a phase correction algorithm is applied to the filtered and decimated complex interferograms. The resulting imaginary part of the spectrum contains only the noise component of the uncorrected spectrum. Additional random noise reduction can be accomplished by applying a spectral smoothing routine to the phase-corrected spectrum. The phase correction and spectral smoothing operations are performed on a set of interferogram scans for both ambient and hot blackbody references. To continue with the calibration, we compute the spectral responsivity based on the previous results, from which, the calibrated ambient blackbody (ABB), hot blackbody (HBB), and scene spectra can be obtained. We now can estimate the noise equivalent spectral radiance (NESR) from the calibrated ABB and HBB spectra. The correction schemes that compensate for the fore-optics offsets and off-axis effects are also implemented. In the third block, we developed an efficient method of generating pixel performance assessments. In addition, a random pixel selection scheme is designed based on the pixel performance evaluation. Finally, in the fourth block, the single pixel algorithms are applied to the entire FPA.

Tian, Jialin↗

Enabling Disabled Persons to Gain Access to Digital Media

A report describes the first phase in an effort to enhance the NaviGaze software to enable profoundly disabled persons to operate computers. (Running on a Windows-based computer equipped with a video camera aimed at the user s head, the original NaviGaze software processes the user's head movements and eye blinks into cursor movements and mouse clicks to enable hands-free control of the computer.) To accommodate large variations in movement capabilities among disabled individuals, one of the enhancements was the addition of a graphical user interface for selection of parameters that affect the way the software interacts with the computer and tracks the user s movements. Tracking algorithms were improved to reduce sensitivity to rotations and reduce the likelihood of tracking the wrong features. Visual feedback to the user was improved to provide an indication of the state of the computer system. It was found that users can quickly learn to use the enhanced software, performing single clicks, double clicks, and drags within minutes of first use. Available programs that could increase the usability of NaviGaze were identified. One of these enables entry of text by using NaviGaze as a mouse to select keys on a virtual keyboard.

Beach, Glenn↗

An efficient algorithm for generating random number pairs drawn from a bivariate normal distribution

An efficient algorithm for generating random number pairs from a bivariate normal distribution was developed. Any desired value of the two means, two standard deviations, and correlation coefficient can be selected. Theoretically the technique is exact and in practice its accuracy is limited only by the quality of the uniform distribution random number generator, inaccuracies in computer function evaluation, and arithmetic. A FORTRAN routine was written to check the algorithm and good accuracy was obtained. Some small errors in the correlation coefficient were observed to vary in a surprisingly regular manner. A simple model was developed which explained the qualities aspects of the errors.

Campbell, C. W.↗

Station Keeping of Small Outboard-Powered Boats

Three station keeping controllers have been developed which work to minimize displacement of a small outboard-powered vessel from a desired location. Each of these three controllers has a common initial layer that uses fixed-gain feedback control to calculate the desired heading of the vessel. A second control layer uses a common fixed-gain feedback controller to calculate the net forward thrust, one of two algorithms for controlling engine angle (Fixed-Gain Proportional-integral-derivative (PID) or PID with Adaptively Augmented Gains), and one of two algorithms for differential throttle control (Fixed-Gain PID and PID with Adaptive Differential Throttle gains), which work together to eliminate heading error. The three selected controllers are evaluated using a numerical simulation of a 33-foot center console vessel with twin outboards that is subject to wave, wind, and current disturbances. Each controller is tested for its ability to maintain position in the presence of three sets of environmental disturbances. These algorithms were tested with current velocity of 1.5 m/s, significant wave height of 0.5 m, and wind speeds of 2, 5, and 10 m/s. These values were chosen to model conditions a small vessel may experience in the Gulf Stream off of Fort Lauderdale. The Fixed-gain PID controller progressively got worse as wind speeds increased, while the controllers using adaptive methodologies showed consistent performance over all weather conditions and decreased heading error by as much as 20%. Thus, enhanced robustness to environmental changes has been gained by using an adaptive algorithm.

Fisher, A. D.↗

A Relevancy Algorithm for Curating Earth Science Data Around Phenomenon

Earth science data are being collected for various science needs and applications, processed using different algorithms at multiple resolutions and coverages, and then archived at different archiving centers for distribution and stewardship causing difficulty in data discovery. Curation, which typically occurs in museums, art galleries, and libraries, is traditionally defined as the process of collecting and organizing information around a common subject matter or a topic of interest. Curating data sets around topics or areas of interest addresses some of the data discovery needs in the field of Earth science, especially for unanticipated users of data. This paper describes a methodology to automate search and selection of data around specific phenomena. Different components of the methodology including the assumptions, the process, and the relevancy ranking algorithm are described. The paper makes two unique contributions to improving data search and discovery capabilities. First, the paper describes a novel methodology developed for automatically curating data around a topic using Earthscience metadata records. Second, the methodology has been implemented as a standalone web service that is utilized to augment search and usability of data in a variety of tools.

earth science phenomena↗

Development of a quantitative basis for selection of spectral features in a vegetation monitoring system

The development of an objective methodology for evaluation of alternative Landsat data preprocessing options, spectral transform features for monitoring vegetation, and feature summarization algorithms is presented. Based on estimates of spectral separability between a target class and its confusion classes, analysis of variance techniques are used to evaluate potential design options for large scale vegetation monitoring systems. Case studies are presented for early season and through the season spring small grains separation and for barley/other spring small grains separation. It is concluded that a basis for efficient, objective selection among alternative feature extraction approaches has been established for the large scale vegetation mapping/inventory problem. Although the approach has been demonstrated for the unitemporal class separability case, extensions to the multitemporal case are under development.

Phinney, D. E.↗

Combined Radar and Radiometer Analysis of Precipitation Profiles for a Parametric Retrieval Algorithm

A methodology to analyze precipitation profiles using the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) and precipitation radar (PR) is proposed. Rainfall profiles are retrieved from PR measurements, defined as the best-fit solution selected from precalculated profiles by cloud-resolving models (CRMs), under explicitly defined assumptions of drop size distribution (DSD) and ice hydrometeor models. The PR path-integrated attenuation (PIA), where available, is further used to adjust DSD in a manner that is similar to the PR operational algorithm. Combined with the TMI-retrieved nonraining geophysical parameters, the three-dimensional structure of the geophysical parameters is obtained across the satellite-observed domains. Microwave brightness temperatures are then computed for a comparison with TMI observations to examine if the radar-retrieved rainfall is consistent in the radiometric measurement space. The inconsistency in microwave brightness temperatures is reduced by iterating the retrieval procedure with updated assumptions of the DSD and ice-density models. The proposed methodology is expected to refine the a priori rain profile database and error models for use by parametric passive microwave algorithms, aimed at the Global Precipitation Measurement (GPM) mission, as well as a future TRMM algorithms.

Masunaga, Hirohiko↗