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At least 955 records · Page 53
All sourcesNASA NTRSDOE OSTI
NASA NTRS2008

Near-Real Time Cloud Retrievals from Operational and Research Meteorological Satellites

A set of cloud retrieval algorithms developed for CERES and applied to MODIS data have been adapted to analyze other satellite imager data in near-real time. The cloud products, including single-layer cloud amount, top and base height, optical depth, phase, effective particle size, and liquid and ice water paths, are being retrieved from GOES- 10/11/12, MTSAT-1R, FY-2C, and Meteosat imager data as well as from MODIS. A comprehensive system to normalize the calibrations to MODIS has been implemented to maximize consistency in the products across platforms. Estimates of surface and top-of-atmosphere broadband radiative fluxes are also provided. Multilayered cloud properties are retrieved from GOES-12, Meteosat, and MODIS data. Native pixel resolution analyses are performed over selected domains, while reduced sampling is used for full-disk retrievals. Tools have been developed for matching the pixel-level results with instrumented surface sites and active sensor satellites. The calibrations, methods, examples of the products, and comparisons with the ICESat GLAS lidar are discussed. These products are currently being used for aircraft icing diagnoses, numerical weather modeling assimilation, and atmospheric radiation research and have potential for use in many other applications.

Minnis, Patrick↗
NASA NTRS2009

Development of the One-Sided Nonlinear Adaptive Doppler Shift Estimation

The new development of a one-sided nonlinear adaptive shift estimation technique (NADSET) is introduced. The background of the algorithm and a brief overview of NADSET are presented. The new technique is applied to the wind parameter estimates from a 2-micron wavelength coherent Doppler lidar system called VALIDAR located in NASA Langley Research Center in Virginia. The new technique enhances wind parameters such as Doppler shift and power estimates in low Signal-To-Noise-Ratio (SNR) regimes using the estimates in high SNR regimes as the algorithm scans the range bins from low to high altitude. The original NADSET utilizes the statistics in both the lower and the higher range bins to refine the wind parameter estimates in between. The results of the two different approaches of NADSET are compared.

Beyon, Jeffrey Y.↗
NASA NTRS2018

The SMAP Level-4 ECO Product - Phase 1: Improving Vegetation Simulations Through Observation-Driven Parameter Estimation

Simulations of hydrological fields as well as water, energy and carbon fluxes from the land surface to the atmosphere are crucial for a wide range of applications, including agricultural advisories, forecasts of (short-term) atmospheric behavior and seasonal weather predictions including forecasts of extreme events, such as heatwaves or droughts. The NASA Soil Moisture Active Passive (SMAP) mission Level-4 (L4) Eco-Hydrology (ECO) project aims to improve modeled estimates of the terrestrial water, energy and carbon fluxes and states by developing a fully-coupled hydrology-vegetation data assimilation (DA) algorithm. The DA system is developed for the NASA Goddard Earth Observing System version 5 (GEOS-5) Catchment-CN land surface model, which combines land hydrology components of the GEOS-5 Catchment model with dynamic vegetation components of the Community Land Model version 4. Catchment-CN fully couples the terrestrial water, energy and carbon cycles, allowing feedbacks from the land hydrology to the biosphere and vice versa. For SMAP L4 ECO a calibration of the Catchment-CN vegetation parameterization against observations of the fraction of absorbed photosynthetically active radiation (FPAR) from the Moderate Resolution Imaging Spectroradiometer (MODIS) is implemented to improve the model's standalone skill. Next, the DA algorithm used to produce the SMAP L4 soil moisture product is adapted to Catchment-CN to assimilate SMAP brightness temperatures and inform the model's land hydrology component. The DA system is further extended to assimilate MODIS FPAR observations in order to constrain the model's dynamic vegetation component. In this presentation, we demonstrate that the Catchment-CN parameter calibration leads to more realistic vegetation simulations and reduces the root mean squared error between modeled and observed vegetation states across the model's various plant functional types. We also show that the assimilation of SMAP observations is able to improve the average correlation, bias and unbiased RMSE between the modeled surface and root zone soil moisture estimates, and ground observations from the SMAP core validation sites.

Kolassa, J.↗
NASA NTRS2020

Next Generation NASA Hazard Detection System Development

The SPLICE project is continuing NASA’s efforts to develop precision landing GN&C technologies for future lander missions. One of those technologies is the next generation Hazard Detection (HD) System, which consists of a new HD Lidar and HD Algorithms. The HD System is a modular system that will be adapted to meet specific mission needs in the future. This paper presents the design approach, the nominal concept of operations for which the first prototype is being designed, and the expected performance of the system.

Restrepo, Carolina I.↗
NASA NTRS2018

Practical Aspects of Real-Time Modeling for the Learn-To-Fly Concept

Practical aspects of autonomous onboard real-time modeling for the NASA Learn-to-Fly concept are examined using flight data from two subscale test aircraft. A practical real-time global nonlinear aerodynamic modeling method is developed and explained, along with the multiple-input excitation needed for effective real-time modeling. Critical issues for integrating real-time global nonlinear aerodynamic modeling and local linear modeling with the real-time learning adaptive control and guidance elements of the Learn-to-Fly algorithm are identified and discussed. Real-time modeling results from NASA Learn-to-Fly flight demonstrations are presented and evaluated using model fit metrics and prediction tests.

Morelli, Eugene A.↗
NASA NTRSDate not supplied

Adaptive Optimization for System Performance and Combined Bernstein Polynomial, Optimal Reciprocal Collision Avoidance, Differential Dynamic Programming for Trajectory Replanning and Collision Avoidance for UAM Vehicles

The emerging urban air mobility (UAM) sector in aerospace is driving development of unconventional multi-modal vehicle configurations and autonomous flight. The combination of multi-modal vehicle dynamics, complex environment, requirements to deal with flight contingencies in an efficient and safe manner, as well as necessity for precise trajectory following and performance, are the driving influence behind adaptive optimization for system performance. We are interested in trajectory optimization algorithm that would system parameter estimation and identifying the optimal switching time between modes of hybrid dynamical systems. This presentation discusses a parameterized optimal control trajectory optimization algorithm that is an extended and generalized version of Differential Dynamic Programming (DDP), titled Parameterized Differential Dynamic Programming (PDDP). DDP is an efficient trajectory optimization algorithm relying on second order approximations of a system’s dynamics and cost function and has recently been applied to optimize systems with time invariant parameters. Experiments are presented applying PDDP to solve model predictive control (MPC) and moving horizon estimation (MHE) tasks simultaneously. In particular, PDDP is used to determine the optimal transition point between flight regimes of a complex urban air mobility (UAM) class vehicle exhibiting multiple phases of flight and to identify and compensate for actuation faults.

optimization↗
NASA NTRS1983

Structural control research and experiments at NASA/LaRC

Research progress in the area of structural dynamics and control using the flexible beam facility at the NASA Langley Research Center is reviewed. Particular attention is placed on the progress in adaptive control and reliability improvements using advanced control concepts. Both theoretical and experimental results are given to indicate the nature of the work being undertaken. In the adaptive control area, emphasis is placed on parameter and system identification and in comparison of competing on-line algorithms. Also, results are presented for on-line modal control laws that are interfaced to a parameter identification scheme. This provides an on-line distributed adaptive control system. In the reliability area, a design process is outlined that incorporates reliability over the design mission life.

Montgomery, R. C.↗
NASA NTRS2017

Autonomous Guidance Navigation and Control for Agile Quadrotors Using Polynomial Trajectory Planning and L1 Adaptive Control

We address the challenge to allow efficient autonomous flight in real world environments, both indoor and outdoor. We use a straight-line SE-SCP (Spherical Expansion and Sequential Convex Programming) [algorithm] to find an initial route through the environment and minimum snap trajectory generation using piecewise polynomials. Then, we implement an adaptive robust control able to address some robustness issues for quadrotors in outdoor flight, such as mass variation and wind disturbances. Coupling these techniques we allow high-speed and aggressive autonomous flight through obstacle-dense indoor environments, as well as address outdoor disturbances.

Landolfi, Mattia↗
NASA NTRS1990

Attitude determination and calibration using a recursive maximum likelihood-based adaptive Kalman filter

An adaptive Kalman filter design that utilizes recursive maximum likelihood parameter identification is discussed. At the center of this design is the Kalman filter itself, which has the responsibility for attitude determination. At the same time, the identification algorithm is continually identifying the system parameters. The approach is applicable to nonlinear, as well as linear systems. This adaptive Kalman filter design has much potential for real time implementation, especially considering the fast clock speeds, cache memory and internal RAM available today. The recursive maximum likelihood algorithm is discussed in detail, with special attention directed towards its unique matrix formulation. The procedure for using the algorithm is described along with comments on how this algorithm interacts with the Kalman filter.

Kelly, D. A.↗
NASA NTRS2004

The Development of Two Science Investigator-led Processing Systems (SIPS) for NASA's Earth Observation System (EOS)

In 2001, NASA Goddard Space Flight Center's Laboratory for Terrestrial Physics started the construction of a science Investigator-led Processing System (SIPS) for processing data from the Ozone Monitoring Instrument (OMI) which will launch on the Aura platform in mid 2004. The Ozone Monitoring Instrument (OMI) is a contribution of the Netherlands Agency for Aerospace Programs (NIVR) in collaboration with the Finnish Meteorological Institute (FMI) to the Earth Observing System (EOS) Aura mission. It will continue the Total Ozone Monitoring System (TOMS) record for total ozone and other atmospheric parameters related to ozone chemistry and climate. OMI measurements will be highly synergistic with the other instruments on the EOS Aura platform. The LTP previously developed the Moderate Resolution Imaging Spectrometer (MODIS) Data Processing System (MODAPS), which has been in full operations since the launches of the Terra and Aqua spacecrafts in December, 1999 and May, 2002 respectively. During that time, it has continually evolved to better support the needs of the MODIS team. We now run multiple instances of the system managing faster than real time reprocessings of the data as well as continuing forward processing. The new OMI Data Processing System (OMIDAPS) was adapted from the MODAPS. It will ingest raw data from the satellite ground station and process it to produce calibrated, geolocated higher level data products. These data products will be transmitted to the Goddard Distributed Active Archive Center (GDAAC) instance of the Earth Observing System (EOS) Data and Information System (EOSDIS) for long term archive and distribution to the public. The OMIDAPS will also provide data distribution to the OMI Science Team for quality assessment, algorithm improvement, calibration, etc. We have taken advantage of lessons learned from the MODIS experience and software already developed for MODIS. We made some changes in the hardware system organization, database and software to adapt the system for OMI. We replaced the fundamental database system, Sybase, with an Open Source RDBMS called PostgreSQL, and based the entire OMIDAPS on a cluster of Linux based commodity computers rather than the large SGI servers that MODAPS uses. Rather than relying on a central I/O server host, the new system distributes its data archive among multiple server hosts in the cluster. OMI is also customizing the graphical user interfaces and reporting structure to more closely meet the needs of the OMI Science Team. Prior to 2003, simulated OMI data and the science algorithms were not ready for production testing. We initially constructed a prototype system and tested using a 25 year dataset of Total Ozone Mapping Spectrometer (TOMS) and Solar Backscatter Ultraviolet Instrument (SBUV) data. This prototype system provided a platform to support the adaptation of the algorithms for OMI, and provided reprocessing of the historical data aiding in its analysis. In a recent reanalysis of the TOMS data, the OMIDAPS processed 108,000 full orbits of data through 4 processing steps per orbit, producing about 800,000 files (400 GiB) of level 2 and greater data files. More recently we have installed two instances of the OMIDAPS for integration and testing of OM1 science processes as they get delivered from the Science Team. A Test instance of the OMIDAPS has also supported a series of "Interface Confidence Tests" (ICTs) and End-to-End Ground System tests to ensure the launch readiness of the system. This paper will discuss the high-level hardware, software, and database organization of the OMIDAPS and how it builds on the MODAPS heritage system. It will also provide an overview of the testing and implementation of the production OMIDAPS.

Tilmes, Curt↗
NASA NTRS1996

A study of GPS measurement errors due to noise and multipath interference for CGADS

This report describes a study performed by the Colorado Center for Astrodynamics Research (CCAR) on GPS measurement errors in the Codeless GPS Attitude Determination System (CGADS) due to noise and multipath interference. Preliminary simulation models fo the CGADS receiver and orbital multipath are described. The standard FFT algorithms for processing the codeless data is described and two alternative algorithms - an auto-regressive/least squares (AR-LS) method, and a combined adaptive notch filter/least squares (ANF-ALS) method, are also presented. Effects of system noise, quantization, baseband frequency selection, and Doppler rates on the accuracy of phase estimates with each of the processing methods are shown. Typical electrical phase errors for the AR-LS method are 0.2 degrees, compared to 0.3 and 0.5 degrees for the FFT and ANF-ALS algorithms, respectively. Doppler rate was found to have the largest effect on the performance.

Axelrad, Penina↗
NASA NTRSDate not supplied

Simultaneous Aerosol and Ocean Polarimeter Products Using Coupled Atmosphere-Ocean Vector Radiative Transfer and Neural Networks: The PACE-MAPP Algorithm

We describe the PACE-MAPP algorithm that simultaneously retrieves aerosol and ocean optical parameters using multiangle and multi-channel polarimeter measurements from the SPEXone, Hyper-Angular Rainbow Polarimeter 2 (HARP2), and Ocean Color Instrument (OCI) instruments onboard the NASA Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) observing system PACE-MAPP is adapted from the Research Scanning Polarimeter (RSP) Microphysical Aerosol Properties from Polarimetry (RSP-MAPP) algorithm. A key feature of the MAPP family of algorithms is the use of a coupled vector radiative transfer model such that the atmosphere and ocean are always considered together as one system. Consequently, conservation of energy ensures that negative water-leaving radiances do not occur. PACE-MAPP uses optimal estimation to simultaneously characterize the optical and microphysical properties of aerosol and ocean constituents, find the optimal solution, and reliably account for the uncertainties of each parameter. This coupled approach, together with multiangle, multi-channel polarimeter measurements, will enable retrievals of aerosol and water properties across the Earth’s oceans. The PACE-MAPP algorithm provides aerosol and ocean products for both the open ocean and coastal areas and is designed to be accurate, modular, and efficient by using fast neural networks that replace the time-consuming vector radiative transfer calculations. We provide an overview of the PACE-MAPP framework and also describe its modular components including its aerosol and hydrosol models, ocean bio-optical models, and thin cirrus model.

Snorre Stamnes↗
NASA NTRS2013

A Green's Function Approach to Simulate DNA Damage by the Indirect Effect

The DNA damage is of fundamental importance in the understanding of the effects of ionizing radiation. DNA is damaged by the direct effect of radiation (e.g. direct ionization) and by indirect effect (e.g. damage by.OH radicals created by the radiolysis of water). Despite years of research, many questions on the DNA damage by ionizing radiation remains. In the recent years, the Green's functions of the diffusion equation (GFDE) have been used extensively in biochemistry [1], notably to simulate biochemical networks in time and space [2]. In our future work on DNA damage, we wish to use an approach based on the GFDE to refine existing models on the indirect effect of ionizing radiation on DNA. To do so, we will use the code RITRACKS [3] developed at the NASA Johnson Space Center to simulate the radiation track structure and calculate the position of radiolytic species after irradiation. We have also recently developed an efficient Monte‐Carlo sampling algorithm for the GFDE of reversible reactions with an intermediate state [4], which can be modified and adapted to simulate DNA damage by free radicals. To do so, we will use the known reaction rate constants between radicals (OH, eaq, H,...) and the DNA bases, sugars and phosphates and use the sampling algorithms to simulate the diffusion of free radicals and chemical reactions with DNA. These techniques should help the understanding of the contribution of the indirect effect in the formation of DNA damage and double‐strand breaks.

Plante, Ianik↗
NASA NTRS1994

Minimal time change detection algorithm for reconfigurable control system and application to aerospace

System parameters should be tracked on-line to build a reconfigurable control system even though there exists an abrupt change. For this purpose, a new performance index that we are studying is the speed of adaptation- how quickly does the system determine that a change has occurred? In this paper, a new, robust algorithm that is optimized to minimize the time delay in detecting a change for fixed false alarm probability is proposed. Simulation results for the aircraft lateral motion with a known or unknown change in control gain matrices, in the presence of doublet input, indicate that the algorithm works fairly well. One of its distinguishing properties is that detection delay of this algorithm is superior to that of Whiteness Test.

Kim, Sungwan↗
NASA NTRS2010

Evaluation of the VIIRS Land Algorithms at Land PEATE

The Land Product Evaluation and Algorithm Testing Element (Land PEATE), a component of the Science Data Segment of the National Polar-orbiting Operational Environmental Satellite System (NPOESS) Preparatory Project (NPP), is being developed at the NASA Goddard Space Flight Center (GSFC). The primary task of the Land PEATE is to assess the quality of the Visible Infrared Imaging Radiometer Suite (VIIRS) Land data products made by the Interface Data Processing System (IDPS) using the Operational (OPS) Code during the NPP era and to recommend improvements to the algorithms in the IDPS OPS code. The Land PEATE uses a version of the MODIS Adaptive Processing System (MODAPS), NPPDAPS, that has been modified to produce products from the IDPS OPS code and software provided by the VIIRS Science Team, and uses the MODIS Land Data Operational Product Evaluation (LDOPE) team for evaluation of the data records generated by the NPPDAPS. Land PEATE evaluates the algorithms by comparing data products generated using different versions of the algorithm and also by comparing to heritage products generated from different instrument such as MODIS using various quality assessment tools developed at LDOPE. This paper describes the Land PEATE system and some of the approaches used by the Land PEATE for evaluating the VIIRS Land algorithms during the pre-launch period of the NPP mission and the proposed plan for long term monitoring of the quality of the VIIRS Land products post-launch.

Wolfe, Robert E.↗
NASA NTRS1994

Adaptive Wing Camber Optimization: A Periodic Perturbation Approach

Available redundancy among aircraft control surfaces allows for effective wing camber modifications. As shown in the past, this fact can be used to improve aircraft performance. To date, however, algorithm developments for in-flight camber optimization have been limited. This paper presents a perturbational approach for cruise optimization through in-flight camber adaptation. The method uses, as a performance index, an indirect measurement of the instantaneous net thrust. As such, the actual performance improvement comes from the integrated effects of airframe and engine. The algorithm, whose design and robustness properties are discussed, is demonstrated on the NASA Dryden B-720 flight simulator.

Espana, Martin↗
NASA NTRS2004

Distributed Control by Lagrangian Steepest Descent

Often adaptive, distributed control can be viewed as an iterated game between independent players. The coupling between the players mixed strategies, arising as the system evolves from one instant to the next, is determined by the system designer. Information theory tells us that the most likely joint strategy of the players, given a value of the expectation of the overall control objective function, is the minimizer of a function o the joint strategy. So the goal of the system designer is to speed evolution of the joint strategy to that Lagrangian mhimbhgpoint,lowerthe expectated value of the control objective function, and repeat Here we elaborate the theory of algorithms that do this using local descent procedures, and that thereby achieve efficient, adaptive, distributed control.

Wolpert, David H.↗
NASA NTRS1994

Maximum-likelihood spectral estimation and adaptive filtering techniques with application to airborne Doppler weather radar

This dissertation focuses on the signal processing problems associated with the detection of hazardous windshears using airborne Doppler radar when weak weather returns are in the presence of strong clutter returns. In light of the frequent inadequacy of spectral-processing oriented clutter suppression methods, we model a clutter signal as multiple sinusoids plus Gaussian noise, and propose adaptive filtering approaches that better capture the temporal characteristics of the signal process. This idea leads to two research topics in signal processing: (1) signal modeling and parameter estimation, and (2) adaptive filtering in this particular signal environment. A high-resolution, low SNR threshold maximum likelihood (ML) frequency estimation and signal modeling algorithm is devised and proves capable of delineating both the spectral and temporal nature of the clutter return. Furthermore, the Least Mean Square (LMS) -based adaptive filter's performance for the proposed signal model is investigated, and promising simulation results have testified to its potential for clutter rejection leading to more accurate estimation of windspeed thus obtaining a better assessment of the windshear hazard.

Lai, Jonathan Y.↗