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At least 1,135 records · Page 63

Park Smart

The Parking Garage Automation System (PGAS) is based on a technology developed by a NASA-sponsored project called Robot sensorSkin(TM). Merritt Systems, Inc., of Orlando, Florida, teamed up with NASA to improve robots working with critical flight hardware at Kennedy Space Center in Florida. The system, containing smart sensor modules and flexible printed circuit board skin, help robots to steer clear of obstacles using a proximity sensing system. Advancements in the sensor designs are being applied to various commercial applications, including the PGAS. The system includes a smartSensor(TM) network installed around and within public parking garages to autonomously guide motorists to open facilities, and once within, to free parking spaces. The sensors use non-invasive reflective-ultrasonic technology for high accuracy, high reliability, and low maintenance. The system is remotely programmable: it can be tuned to site-specific requirements, has variable range capability, and allows remote configuration, monitoring, and diagnostics. The sensors are immune to interference from metallic construction materials, such as rebar and steel beams. Inside the garage, smart routing signs mounted overhead or on poles in front of each row of parking spots guide the motorist precisely to free spaces.

Source record↗

Space-Based Measurements of CO2 from the Japanese Greenhouse Gases Observing Satellite (GOSAT) and the NASA Orbiting Carbon Observatory-2 (OCO-2) Missions

Space-based remote sensing observations hold substantial promise for future long-term monitoring of CO2 and other greenhouse gases. The principal advantages of space based measurements include: (1) Spatial coverage (especially over oceans and tropical land) (2) Sampling density (needed to resolve CO2 weather). The principal challenge is the need for high precision To reach their full potential, space based CO2 measurements must be validated against surface measurements to ensure their accuracy. The TCCON network is providing the transfer standard There is a need for a long-term vision to establish and address community priorities (1) Must incorporate ground, air, space-based assets and models (2) Must balance calls for new observations with need to maintain climate data records.

Orbiting Carbon Observatory -↗

Ground-based retrievals of aerosol column absorption in the UV spectral region and their implications for GEMS measurements

Quantifying the spectral variation of column aerosol absorption in the ultraviolet (UV) and visible (Vis) wavelengths is required for accurate satellite-based aerosol and trace-gas retrievals. Retrievals of the column-averaged imaginary part of refractive index and single scattering albedo (SSA) in the UV–Vis range have been performed at Yonsei University, Seoul, Korea, since 2016 by combining co-located measurements from the NASA Aerosol Robotic Network (AERONET) Cimel sun-sky photometer, the Ultraviolet Multifilter Rotating Shadowband Radiometer (UV-MFRSR), the SKYNET Prede sky radiometer, and the NASA Pandora sun spectrometer. We investigated the spectral variation of column-averaged imaginary part of refractive index for UV–Vis wavelengths to refine models used in our aerosol retrieval algorithm to process measurements from the upcoming Geostationary Environment Monitoring Satellite (GEMS). The retrieved imaginary part of refractive index for highly absorbing fine pollution particles (BC), dust (DS), and non-absorbing (NA) particles in the selected UV–Vis range (380–440 nm) showed 0–20%, 30%, and 0–40% of spectral dependence, respectively. Retrievals of Ozone Monitoring Instrument (OMI) measurement data using the improved aerosol model showed improved correlation with AERONET data compared to the old algorithm that did not properly account for aerosol absorption effects. These results corroborate the advantage of using local climatology derived from ground-based UV–Vis spectral aerosol absorption measurements for satellite GEMS aerosol retrievals over East Asia. Moreover, this study reveals that spectral variations in the UV column aerosol absorption in East Asia differ from those in other regions.

ultraviolet (UV) and visible (Vis) wavelengths↗

Low-level water vapor fields from the VISSR Atmospheric Sounder (VAS) 'split window' channels

A simple physical algorithm is presented which calculates the water vapor content of the lower troposphere from the 11 and 12 micron (split window) channels on the VISSR Atmospheric Sounder (VAS) on the Geostationary Operational Environmental Satellites. The algorithm is used to analyze a time series of VAS split window radiances observed at 15 km horizontal resolution over eastern North America during a 12 hr period on 13 July 1981. Results of the color coded images of the derived precipitable water fields are found to show vivid water vapor features whose broad structure and evolution are verified by the radiosonde and surface networks. The satellite moisture fields also show significant mesoscale features and rapid developments which are not resolved by the conventional networks. The VAS split window is determined to clearly differentiate those areas in which water vapor extends over a deep layer and is more able to support convective cells from those areas in which water vapor is confined to a shallow layer and is therefore less able to support convection. It is concluded that the VAS split windows can be used operationally to monitor mesoscale developments in the low-level moisture fields over relatively cloud-free areas of the United States.

Chesters, D.↗

Extraction of Qualitative Features from Sensor Data Using Windowed Fourier Transform

In this paper, we use Matlab to model the health monitoring of a system through the information gathered from sensors. This implies assessment of the condition of the system components. Once a normal mode of operation is established any deviation from the normal behavior indicates a change. This change may be due to a malfunction of an element, a qualitative change, or a change due to a problem with another element in the network. For example, if one sensor indicates that the temperature in the tank has experienced a step change then a pressure sensor associated with the process in the tank should also experience a step change. The step up and step down as well as sensor disturbances are assumed to be exponential. An RC network is used to model the main process, which is step-up (charging), drift, and step-down (discharging). The sensor disturbances and spike are added while the system is in drift. The system is allowed to run for a period equal to three time constant of the main process before changes occur. Then each point of the signal is selected with a trailing data collected previously. Two trailing lengths of data are selected, one equal to two time constants of the main process and the other equal to two time constants of the sensor disturbance. Next, the DC is removed from each set of data and then the data are passed through a window followed by calculation of spectra for each set. In order to extract features the signal power, peak, and spectrum are plotted vs time. The results indicate distinct shapes corresponding to each process. The study is also carried out for a number of Gaussian distributed noisy cases.

Amini, Abolfazl M.↗

Exploring the Production of NOx by Lightning and Its Impact on Tropospheric Ozone

Our quantitative understanding of free tropospheric (FT) chemistry is quite poor. State-of-the-art regional air quality models (e.g., US EPA's CMAQ) perform very poorly in simulating FT chemistry, with Uniform ozone around 70 ppb throughout the FT in summer, while ozonesonde data show much higher levels of ozone and much spatial-temporal structure. Such models completely neglect lightning-NOx (LNOx) emissions (the most significant source of NOx in the FT), and also contain large uncertainties in the specifications of intercontinental transport, stratosphere-troposphere exchange (STE) and PBLFT exchange (PFTE). Global air chemistry models include LNOx, but in very crude fashion, with the frequency and distribution of lightning being based on modeled cloud parameters (hence large uncertainty), lightning energetics being assumed to be constant for all flashes (literature value, while in reality there is at least a two-orders of magnitude variability from flash-to-flash), and the production of NOx in the surrounding heated air, per Joule of heating, being assumed to be constant also (literature value, while in fact it is a non-linear function of the dissipated heat and local air density, p). This situation is commonly blamed on paucity of pertinent observational data, but for the USA, there is now a wealth of surface- and satellite-based data of lightning available to permit much improved observation-based estimation of LNOx emissions. In the FT, such NOx has a long residence time, and also the ozone production efficiency from NOx there is considerably higher than in the PBL. It is, therefore, of critical importance in FT chemistry. This paper will describe the approach and data products of an ongoing NSSTC project aimed at a much-improved quantification of not only LNOx production on the scale of continental USA based on local and regional lightning observations, but also of intercontinental transport, STE and PFTE, all in upgraded simulations of tropospheric transport and chemistry. In our approach for LNOx, (a) we utilize continuous observed lightning information from the NLDN ground network and from satellite imagers (OTD and LIS) to quantify lightning frequency and distribution at the spatial-temporal scales of models such as CMAQ; (b) we develop new methodologies to quantify flash-specific lightning energy dissipation as heat (epsilon) using data from the research-grade lightning measurement facility at NASA-KSC, and to parameterize epsilon based on regional lightning monitoring data (ground- and satellite-based); and, (c) we develop a new parameterization of NOx production as a function of epsilon and rho. Based on such observation-based information, we are working to develop a gridded, episodic LNOx emissions inventory for the USA for use in models like CMAQ. We are also developing approaches for global(MOZART)- regional(CMAQ) chemistry coupling to improve intercontinental transport and STE. Finally, we are developing new methodologies for assimilation of satellite-observed (GOES) clouds into meteorological modeling (MM5), to improve PFTE and to optimize co-location of cloud convection and observed lightning. We will incorporate these improvements in CMAQ simulations over the USA to better understand FT processes and chemistry, and its impact on ground-level ozone.

Gillani, Noor↗

The 2nd Generation Real Time Mission Monitor (RTMM) Development

The NASA Real Time Mission Monitor (RTMM) is a visualization and information system that fuses multiple Earth science data sources, to enable real time decisionmaking for airborne and ground validation experiments. Developed at the National Aeronautics and Space Administration (NASA) Marshall Space Flight Center, RTMM is a situational awareness, decision-support system that integrates satellite imagery and orbit data, radar and other surface observations (e.g., lightning location network data), airborne navigation and instrument data sets, model output parameters, and other applicable Earth science data sets. The integration and delivery of this information is made possible using data acquisition systems, network communication links, network server resources, and visualizations through the Google Earth virtual globe application. In order to improve the usefulness and efficiency of the RTMM system, capabilities are being developed to allow the end-user to easily configure RTMM applications based on their mission-specific requirements and objectives. This second generation RTMM is being redesigned to take advantage of the Google plug-in capabilities to run multiple applications in a web browser rather than the original single application Google Earth approach. Currently RTMM employs a limited Service Oriented Architecture approach to enable discovery of mission specific resources. We are expanding the RTMM architecture such that it will more effectively utilize the Open Geospatial Consortium Sensor Web Enablement services and other new technology software tools and components. These modifications and extensions will result in a robust, versatile RTMM system that will greatly increase flexibility of the user to choose which science data sets and support applications to view and/or use. The improvements brought about by RTMM 2nd generation system will provide mission planners and airborne scientists with enhanced decision-making tools and capabilities to more efficiently plan, prepare and execute missions, as well as to playback and review past mission data. To paraphrase the old television commercial RTMM doesn t make the airborne science, it makes the airborne science easier.

Blakeslee, Richard↗

What Can Geolocated Sferics Tell Us About Terrestrial Gamma-Ray Flashes?

The Fermi Gamma-ray Burst Monitor (GBM) has been detecting TGFs with increasing sensitivity over the past two years, owing to changes in flight software that have lowered its threshold for triggering and, recently, allowed a search for TGFs weaker than those which would cause an onboard trigger. Associations between TGFs detected in the first 18 months of operation and sferics detected using the World Wide Lightning Location Network (WWLLN) show that TGF peaks and lightning discharges are simultaneous to within tens of microseconds, and that GBM triggered on TGFs that occurred up to a distance of 300 km from the sub-spacecraft position. In the work presented here, we look for associations between TGFs detected by the Reuven Ramaty High Energy Solar Spectroscopic Imager (RHESSI) and WWLLN sferics over the same 18 months, and we compare the match rate and detection horizon of the two instruments. We also look for associations between WWLLN sferics and more recent GBM TGFs, both triggered events and weaker TGFs uncovered in our untriggered search. We discuss whether in this new mode, GBM is detecting TGFs that are more distant from the sub-spacecraft point than 300 km, or whether the weaker TGFs are instead indicative of a luminosity distribution, either because the weaker ones originate deeper in the atmosphere or because they are intrinsically dimmer.

Connaughton, V.↗

Very High Resolution Tree Cover Mapping for Continental United States using Deep Convolutional Neural Networks

Uncertainties in input land cover estimates contribute to a significant bias in modeled above ground biomass (AGB) and carbon estimates from satellite-derived data. The resolution of most currently used passive remote sensing products is not sufficient to capture tree canopy cover of less than ca. 10-20 percent, limiting their utility to estimate canopy cover and AGB for trees outside of forest land. In our study, we created a first of its kind Continental United States (CONUS) tree cover map at a spatial resolution of 1-m for the 2010-2012 epoch using the USDA NAIP imagery to address the present uncertainties in AGB estimates. The process involves different tasks including data acquisition ingestion to pre-processing and running a state-of-art encoder-decoder based deep convolutional neural network (CNN) algorithm for automatically generating a tree non-tree map for almost a quarter million scenes. The entire processing chain including generation of the largest open source existing aerial satellite image training database was performed at the NEX supercomputing and storage facility. We believe the resulting forest cover product will substantially contribute to filling the gaps in ongoing carbon and ecological monitoring research and help quantifying the errors and uncertainties in derived products.

High Resolution↗

Deep Learning Emulation of Atmospheric Correction for Geostationary Sensors

New generation geostationary satellites make reflectance observations available at a continental scale with unprecedented spatiotemporal resolution and spectral range. Generating Earth monitoring products from these observations requires retrieval of the basic parameter, surface reflectance (SR), by atmospheric correction (AC). Algorithms for atmospheric correction, including Multi-Angle Implementation of Atmospheric Correction (MAIAC), are adapted for each sensor and are too computationally complex to be run in real time, relying instead on look-up tables with precomputed values. Machine learning methods, including convolutional neural networks, have demonstrated performance in learning complex, nonlinear mappings and extracting insight from high-dimensional remote sensing data. In this work, we present a deep learning emulator of MAIAC to retrieve both SR and cloud products. Using this adaptation of deep learning-based emulation to remote sensing, we demonstrate stable SR retrieval over a variety of land covers and viewing conditions and accurate cloud detection. Further, a comparison of computation time suggests emulation as a compelling alternative for expensive physical simulation, especially for applications benefited by near-real time data, such as agricultural management and disaster response.

Duffy, Kate↗

The Deep Space Network

The primary objectives during this portion of the extended mission were to assure survival of the spacecraft for a third Mercury encounter through conservation of attitude control gas and to conduct trajectory correction maneuvers (TCMs) as necessary to target the spacecraft for a solar occultation zone pass. Special support activities included TCMs 6 and 7 conducted on October 30, 1974 and on February 12-13, 1975, respectively. This period also saw the DSN interface organization involved in (1) the allocation of sufficient coverage to assure accurate orbit determination solutions, (2) monitoring of DSN implementation for Viking to assure maintenance of compatible interfaces and capabilities required for Mariner 10, and (3) the development of encounter coverage, sequences, and readiness test plans.

Source record↗

Operational radio interferometry observation network (ORION) mobile VLBI station

The design and current status of the ORION mobile VLBI station is described. The station consists of a five-meter antenna, a receiving and recording system installed in a mobile antenna transporter, and an electronics transporter. The station is designed for field operation by a two-person crew at the rate of two sites per week. The various subsystems are described in detail, including the antenna, housing facilities for electronics and crew, microwave equipment, receiver, data acquisition subsystem, frequency and timing subsystem, phase calibration, monitoring and control, water vapor radiometer, and communications.

Renzetti, N. A.↗

Investigation of remote sensing techniques as inputs to operational resource management

The author has identified the following significant results. Visual interpretation of 1:125,000 color LANDSAT prints produced timely level 1 maps of accuracies in excess of 80% for agricultural land identification. Accurate classification of agricultural land via digital analysis of LANDSAT CCT's required precise timing of the date of data collection with mid to late June optimum for western South Dakota. The LANDSAT repetitive nine day cycle over the state allowed the surface areas of stockdams and small reservoir systems to be monitored to provide a timely approximation of surface water conditions on the range. Combined use of DIRS, K-class, and LANDSAT CCT's demonstrated the ability to produce aspen maps of greater detail and timeliness than was available using US Forest Service maps. Visual temporal analyses of LANDSAT imagery improved highway map drainage information and were used to prepare a seven county drainage network. An optimum map of flood-prone areas was developed, utilizing high altitude aerial photography and USGS maps.

Schmer, F. A.↗

Remote voice training: A case study on space shuttle applications, appendix C

The Tile Automation System includes applications of automation and robotics technology to all aspects of the Shuttle tile processing and inspection system. An integrated set of rapid prototyping testbeds was developed which include speech recognition and synthesis, laser imaging systems, distributed Ada programming environments, distributed relational data base architectures, distributed computer network architectures, multi-media workbenches, and human factors considerations. Remote voice training in the Tile Automation System is discussed. The user is prompted over a headset by synthesized speech for the training sequences. The voice recognition units and the voice output units are remote from the user and are connected by Ethernet to the main computer system. A supervisory channel is used to monitor the training sequences. Discussions include the training approaches as well as the human factors problems and solutions for this system utilizing remote training techniques.

Mollakarimi, Cindy↗

Measurements over distributed high performance computing and storage systems

Requirements are carefully described in descriptions of systems to be acquired but often there is no requirement to provide measurements and performance monitoring to ensure that requirements are met over the long term after acceptance. A set of measurements for various UNIX-based systems will be available at the 1992 Goddard Conference on Mass Storage Systems and Technologies. The authors invite others to contribute to the set of measurements. The framework for presenting the measurements of supercomputers, workstations, file servers, mass storage systems, and the networks that interconnect them are given. Production control and database systems are also included. Though other applications and third party software systems are not addressed, it is important to measure them as well. The capability to integrate measurements from all these components from different vendors, and from the third party software systems was recognized and there are efforts to standardize a framework to do this. The measurement activity falls into the domain of management standards. Standards work is ongoing for Open Systems Interconnection (OSI) systems management; AT&T, Digital, and Hewlett-Packard are developing management systems based on this architecture even though it is not finished. Another effort is in the UNIX International Performance Management Working Group. In addition, there are the Open Systems Foundation's Distributed Management Environment and the Object Management Group. A paper comparing the OSI systems management model and the Object Management Group model has been written. The IBM world has had a capability for measurement for various IBM systems since the 1970's and different vendors were able to develop tools for analyzing and viewing these measurements. Since IBM was the only vendor, the user groups were able to lobby IBM for the kinds of measurements needed. In the UNIX world of multiple vendors, a common set of measurements will not be as easy to get.

Williams, Elizabeth↗

Software metrics: The key to quality software on the NCC project

Network Control Center (NCC) Project metrics are captured during the implementation and testing phases of the NCCDS software development lifecycle. The metrics data collection and reporting function has interfaces with all elements of the NCC project. Close collaboration with all project elements has resulted in the development of a defined and repeatable set of metrics processes. The resulting data are used to plan and monitor release activities on a weekly basis. The use of graphical outputs facilitates the interpretation of progress and status. The successful application of metrics throughout the NCC project has been instrumental in the delivery of quality software. The use of metrics on the NCC Project supports the needs of the technical and managerial staff. This paper describes the project, the functions supported by metrics, the data that are collected and reported, how the data are used, and the improvements in the quality of deliverable software since the metrics processes and products have been in use.

Burns, Patricia J.↗

Development of Algorithms for Control of Humidity in Plant Growth Chambers

Algorithms were developed to control humidity in plant growth chambers used for research on bioregenerative life support at Kennedy Space Center. The algorithms used the computed water vapor pressure (based on measured air temperature and relative humidity) as the process variable, with time-proportioned outputs to operate the humidifier and de-humidifier. Algorithms were based upon proportional-integral-differential (PID) and Fuzzy Logic schemes and were implemented using I/O Control software (OPTO-22) to define and download the control logic to an autonomous programmable logic controller (PLC, ultimate ethernet brain and assorted input-output modules, OPTO-22), which performed the monitoring and control logic processing, as well the physical control of the devices that effected the targeted environment in the chamber. During limited testing, the PLC's successfully implemented the intended control schemes and attained a control resolution for humidity of less than 1%. The algorithms have potential to be used not only with autonomous PLC's but could also be implemented within network-based supervisory control programs. This report documents unique control features that were implemented within the OPTO-22 framework and makes recommendations regarding future uses of the hardware and software for biological research by NASA.

Costello, Thomas A.↗

Characterizing DSN System Frequency Stability with Spacecraft Tracking Data

This paper describes a recent effort in characterizing frequency stability performance of the ground system in the NASA Deep Space Network (DSN). Unlike the traditional approach where performance is obtained from special calibration sessions that are both time consuming and require manual setup, the new method taps into the daily spacecraft tracking data. This method significantly increases the amount of data available for analysis, roughly by two orders of magnitude; making it possible to conduct trend analysis with reasonable confidence. Since the system is monitored daily, any significant variation in performance can be detected timely. This helps the DSN maintain its performance commitment to customers.

performance analysis↗