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At least 19 records

Remote Sensing of Ocean Color in the Arctic: Algorithm Development and Comparative Validation

The overall goal of this effort is to acquire a large bio-optical database, encompassing most environmental variability in the Arctic, to develop algorithms for phytoplankton biomass and production and other optically active constituents. A large suite of bio-optical and biogeochemical observations have been collected in a variety of high latitude ecosystems at different seasons. The Ocean Research Consortium of the Arctic (ORCA) is a collaborative effort between G.F. Cota of Old Dominion University (ODU), W.G. Harrison and T. Platt of the Bedford Institute of Oceanography (BIO), S. Sathyendranath of Dalhousie University and S. Saitoh of Hokkaido University. ORCA has now conducted 12 cruises and collected over 500 in-water optical profiles plus a variety of ancillary data. Observational suites typically include apparent optical properties (AOPs), inherent optical property (IOPs), and a variety of ancillary observations including sun photometry, biogeochemical profiles, and productivity measurements. All quality-assured data have been submitted to NASA's SeaWIFS Bio-Optical Archive and Storage System (SeaBASS) data archive. Our algorithm development efforts address most of the potential bio-optical data products for the Sea-Viewing Wide Field-of-view Sensor (SeaWiFS), Moderate Resolution Imaging Spectroradiometer (MODIS), and GLI, and provides validation for a specific areas of concern, i.e., high latitudes and coastal waters.

Cota, Glenn F.

Algorithm Development and Validation for Satellite-Derived Distributions of DOC and CDOM in the US Middle Atlantic Bight

In coastal ocean waters, distributions of dissolved organic carbon (DOC) and chromophoric dissolved organic matter (CDOM) vary seasonally and interannually due to multiple source inputs and removal processes. We conducted several oceanographic cruises within the continental margin of the U.S. Middle Atlantic Bight (MAB) to collect field measurements in order to develop algorithms to retrieve CDOM and DOC from NASA's MODIS-Aqua and SeaWiFS satellite sensors. In order to develop empirical algorithms for CDOM and DOC, we correlated the CDOM absorption coefficient (a(sub cdom)) with in situ radiometry (remote sensing reflectance, Rrs, band ratios) and then correlated DOC to Rrs band ratios through the CDOM to DOC relationships. Our validation analyses demonstrate successful retrieval of DOC and CDOM from coastal ocean waters using the MODIS-Aqua and SeaWiFS satellite sensors with mean absolute percent differences from field measurements of < 9 %for DOC, 20% for a(sub cdom)(355)1,6 % for a(sub cdom)(443), and 12% for the CDOM spectral slope. To our knowledge, the algorithms presented here represent the first validated algorithms for satellite retrieval of a(sub cdom) DOC, and CDOM spectral slope in the coastal ocean. The satellite-derived DOC and a(sub cdom) products demonstrate the seasonal net ecosystem production of DOC and photooxidation of CDOM from spring to fall. With accurate satellite retrievals of CDOM and DOC, we will be able to apply satellite observations to investigate interannual and decadal-scale variability in surface CDOM and DOC within continental margins and monitor impacts of climate change and anthropogenic activities on coastal ecosystems.

Mannino, Antonio

Infrared Algorithm Development for Ocean Observations with EOS/MODIS

Efforts continue under this contract to develop algorithms for the computation of sea surface temperature (SST) from MODIS infrared measurements. This effort includes radiative transfer modeling, comparison of in situ and satellite observations, development and evaluation of processing and networking methodologies for algorithm computation and data accession, evaluation of surface validation approaches for IR radiances, development of experimental instrumentation, and participation in MODIS (project) related activities. Activities in this contract period have focused on radiative transfer modeling, evaluation of atmospheric correction methodologies, undertake field campaigns, analysis of field data, and participation in MODIS meetings.

Brown, Otis B.

Infrared algorithm development for ocean observations with EOS/MODIS

Efforts continue under this contract to develop algorithms for the computation of sea surface temperature (SST) from MODIS infrared retrievals. This effort includes radiative transfer modeling, comparison of in situ and satellite observations, development and evaluation of processing and networking methodologies for algorithm computation and data accession, evaluation of surface validation approaches for IR radiances, and participation in MODIS (project) related activities. Efforts in this contract period have focused on radiative transfer modeling and evaluation of atmospheric path radiance efforts on SST estimation, exploration of involvement in ongoing field studies, evaluation of new computer networking strategies, and objective analysis approaches.

Brown, Otis B.

Infrared algorithm development for ocean observations

Efforts continue under this contract to develop algorithms for the computation of sea surface temperature (SST) from MODIS infrared retrievals. This effort includes radiative transfer modeling, comparison of in situ and satellite observations, development and evaluation of processing and networking methodologies for algorithm computation and data accession, evaluation of surface validation approaches for IR radiances, and participation in MODIS (project) related activities. Efforts in this contract period have focused on radiative transfer modeling, evaluation of atmospheric correction methodologies, involvement in field studies, production and evaluation of new computer networking strategies, and objective analysis approaches.

Brown, Otis B.

Space-based Doppler lidar sampling strategies: Algorithm development and simulated observation experiments

Lidar Atmospheric Wind Sounder (LAWS) Simulation Models (LSM) were developed to evaluate the potential impact of global wind observations on the basic understanding of the Earth's atmosphere and on the predictive skills of current forecast models (GCM and regional scale). Fully integrated top to bottom LAWS Simulation Models for global and regional scale simulations were developed. The algorithm development incorporated the effects of aerosols, water vapor, clouds, terrain, and atmospheric turbulence into the models. Other additions include a new satellite orbiter, signal processor, line of sight uncertainty model, new Multi-Paired Algorithm and wind error analysis code. An atmospheric wind field library containing control fields, meteorological fields, phenomena fields, and new European Center for Medium Range Weather Forecasting (ECMWF) data was also added. The LSM was used to address some key LAWS issues and trades such as accuracy and interpretation of LAWS information, data density, signal strength, cloud obscuration, and temporal data resolution.

Emmitt, G. D.

Utilization of Ancillary Data Sets for SMAP Algorithm Development and Product Generation

Algorithms being developed for the Soil Moisture Active Passive (SMAP) mission require a variety of both static and ancillary data. The selection of the most appropriate source for each ancillary data parameter is driven by a number of considerations, including accuracy, latency, availability, and consistency across all SMAP products and with SMOS (Soil Moisture Ocean Salinity). It is anticipated that initial selection of all ancillary datasets, which are needed for ongoing algorithm development activities on the SMAP algorithm testbed at JPL, will be completed within the year. These datasets will be updated as new or improved sources become available, and all selections and changes will be documented for the benefit of the user community. Wise choices in ancillary data will help to enable SMAP to provide new global measurements of soil moisture and freeze/thaw state at the targeted accuracy necessary to tackle hydrologically-relevant societal issues.

ONeill, P.

SPHERES as Formation Flight Algorithm Development and Validation Testbed: Current Progress and Beyond

The MIT-SSL SPHERES testbed provides a facility for the development of algorithms necessary for the success of Distributed Satellite Systems (DSS). The initial development contemplated formation flight and docking control algorithms; SPHERES now supports the study of metrology, control, autonomy, artificial intelligence, and communications algorithms and their effects on DSS projects. To support this wide range of topics, the SPHERES design contemplated the need to support multiple researchers, as echoed from both the hardware and software designs. The SPHERES operational plan further facilitates the development of algorithms by multiple researchers, while the operational locations incrementally increase the ability of the tests to operate in a representative environment. In this paper, an overview of the SPHERES testbed is first presented. The SPHERES testbed serves as a model of the design philosophies that allow for the various researches being carried out on such a facility. The implementation of these philosophies are further highlighted in the three different programs that are currently scheduled for testing onboard the International Space Station (ISS) and three that are proposed for a re-flight mission: Mass Property Identification, Autonomous Rendezvous and Docking, TPF Multiple Spacecraft Formation Flight in the first flight and Precision Optical Pointing, Tethered Formation Flight and Mars Orbit Sample Retrieval for the re-flight mission.

Kong, Edmund M.

Motion Cueing Algorithm Development: Initial Investigation and Redesign of the Algorithms

In this project four motion cueing algorithms were initially investigated. The classical algorithm generated results with large distortion and delay and low magnitude. The NASA adaptive algorithm proved to be well tuned with satisfactory performance, while the UTIAS adaptive algorithm produced less desirable results. Modifications were made to the adaptive algorithms to reduce the magnitude of undesirable spikes. The optimal algorithm was found to have the potential for improved performance with further redesign. The center of simulator rotation was redefined. More terms were added to the cost function to enable more tuning flexibility. A new design approach using a Fortran/Matlab/Simulink setup was employed. A new semicircular canals model was incorporated in the algorithm. With these changes results show the optimal algorithm has some advantages over the NASA adaptive algorithm. Two general problems observed in the initial investigation required solutions. A nonlinear gain algorithm was developed that scales the aircraft inputs by a third-order polynomial, maximizing the motion cues while remaining within the operational limits of the motion system. A braking algorithm was developed to bring the simulator to a full stop at its motion limit and later release the brake to follow the cueing algorithm output.

Telban, Robert J.

Algorithm-development activities

The task of algorithm-development activities at USF continues. The algorithm for determining chlorophyll alpha concentration, (Chl alpha) and gelbstoff absorption coefficient for SeaWiFS and MODIS-N radiance data is our current priority.

Carder, Kendall L.

Probabilistic structural analysis algorithm development for computational efficiency

The PSAM (Probabilistic Structural Analysis Methods) program is developing a probabilistic structural risk assessment capability for the SSME components. An advanced probabilistic structural analysis software system, NESSUS (Numerical Evaluation of Stochastic Structures Under Stress), is being developed as part of the PSAM effort to accurately simulate stochastic structures operating under severe random loading conditions. One of the challenges in developing the NESSUS system is the development of the probabilistic algorithms that provide both efficiency and accuracy. The main probability algorithms developed and implemented in the NESSUS system are efficient, but approximate in nature. In the last six years, the algorithms have improved very significantly.

Wu, Y.-T.

Motion Cueing Algorithm Development: Piloted Performance Testing of the Cueing Algorithms

The relative effectiveness in simulating aircraft maneuvers with both current and newly developed motion cueing algorithms was assessed with an eleven-subject piloted performance evaluation conducted on the NASA Langley Visual Motion Simulator (VMS). In addition to the current NASA adaptive algorithm, two new cueing algorithms were evaluated: the optimal algorithm and the nonlinear algorithm. The test maneuvers included a straight-in approach with a rotating wind vector, an offset approach with severe turbulence and an on/off lateral gust that occurs as the aircraft approaches the runway threshold, and a takeoff both with and without engine failure after liftoff. The maneuvers were executed with each cueing algorithm with added visual display delay conditions ranging from zero to 200 msec. Two methods, the quasi-objective NASA Task Load Index (TLX), and power spectral density analysis of pilot control, were used to assess pilot workload. Piloted performance parameters for the approach maneuvers, the vertical velocity upon touchdown and the runway touchdown position, were also analyzed but did not show any noticeable difference among the cueing algorithms. TLX analysis reveals, in most cases, less workload and variation among pilots with the nonlinear algorithm. Control input analysis shows pilot-induced oscillations on a straight-in approach were less prevalent compared to the optimal algorithm. The augmented turbulence cues increased workload on an offset approach that the pilots deemed more realistic compared to the NASA adaptive algorithm. The takeoff with engine failure showed the least roll activity for the nonlinear algorithm, with the least rudder pedal activity for the optimal algorithm.

Houck, Jacob A.

SMAP's Radar OBP Algorithm Development

An approach for algorithm specifications and development is described for SMAP's radar onboard processor with multi-stage demodulation and decimation bandpass digital filter. Point target simulation is used to verify and validate the filter design with the usual radar performance parameters. Preliminary FPGA implementation is also discussed.

soil moisture

Preliminary results from a subsonic high-angle-of-attack flush airdata sensing (HI-FADS) system - Design, calibration, algorithm development, and flight test evaluation

A nonintrusive high angle-of-attack flush airdata sensing (HI-FADS) system was installed and flight-tested on the F-18 high alpha research vehicle. This paper discusses the airdata algorithm development and composite results expressed as airdata parameter estimates and describes the HI-FADS system hardware, calibration techniques, and algorithm development. An independent empirical verification was performed over a large portion of the subsonic flight envelope. Test points were obtained for Mach numbers from 0.15 to 0.94 and angles of attack from -8.0 to 55.0 deg. Angles of sideslip ranged from -15.0 to 15.0 deg, and test altitudes ranged from 18,000 to 40,000 ft. The HI-FADS system gave excellent results over the entire subsonic Mach number range up to 55 deg angle of attack. The internal pneumatic frequency response of the system is accurate to beyond 10 Hz.

Whitmore, Stephen A.

Algorithm development

The past decade has seen considerable activity in algorithm development for the Navier-Stokes equations. This has resulted in a wide variety of useful new techniques. Some examples for the numerical solution of the Navier-Stokes equations are presented, divided into two parts. One is devoted to the incompressible Navier-Stokes equations, and the other to the compressible form.

Barth, Timothy J.

Floating Potential Measurement Unit (FPMU) Data Processing Algorithm Development and Analysis Assessment

The NASA Engineering and Safety Center (NESC) was requested to provide space plasma instrumentation data analysis expertise in support of Floating Potential Measurement Unit (FPMU) data analysis and data processing algorithm development. Subject matter expertise was requested to support modification of FPMU data processing algorithms to account for aging of the FPMU instrument suite, improve the science quality of the FPMU data sets that are made available to the science community, and provide analysis of FPMU data for complex spacecraft orientation and geophysical situations. This document contains the results of the NESC assessment.

Floating Potential Measurement Unit

QuAIL Tools for Benchmarking, Analysis and Quantum Algorithm Development

HybridQ and PySA are open-source tools developed by NASA to support benchmarking, analysis and quantum algorithm development in areas such as simulation, optimization and machine learning. These tools leverage classical hardware acceleration via high-performance computing CPU and GPU architectures and support high-performance computing. HybridQ is a highly extensible platform designed to provide a common framework to integrate multiple state-of-the-art techniques to simulate large scale quantum circuits. PySA is an extensible platform to optimize a classical cost function. We provide an outline of each of these open-source tools and highlight projects using each of these tools in contexts of simulation, optimization and machine learning.

Quantum Computing

Progress in AMSR Snow Algorithm Development

Advanced Microwave Scanning Radiometer (AMSR) will be flown on-board of the Japanese Advanced Earth Observing Satellite-II (ADEOS-II) and United States Earth Observation System (EOS) PM-1 satellite. AMSR is a passive microwave radiometer with frequency ranges from 6.9 GHz to 89 GHz. It scans conically with a constant incidence angle of 55 deg at the Earth's surface. The swath width is about 1600 km. With a large antenna, AMSR will provide the best spatial resolution of multi-frequency radiometer from space. This provides us an opportunity to improve the snow parameter retrieval. Accurate determination of snow parameters from space is a challenging effort. Over the years, many different techniques have been used to account for the complicated snow parameters such as the density, stratigraphy, snow grain size, temperature variation of the snow-pack. Forest type, fractional forest cover and land use type also need to be considered in developing an improved retrieval algorithm. However, snow is such a dynamic variable, snow-pack parameter keeps changing once the snow is deposited on the earth surface. Currently, NASDA and NASA are developing AMSR snow retrieval algorithms. These algorithms are now being carefully tested and evaluated using the SSM/I data. Due to limited snow-pack data available for comparison, this activity is progressing slowly. However, it is clear that in order to improve the snow retrieval algorithm, it is necessary to model the metamorphism history of the snow-pack.

Chang, Alfred