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At least 37 records · Page 2

Passive fetal heart rate monitoring apparatus and method with enhanced fetal heart beat discrimination

An apparatus for acquiring signals emitted by a fetus, identifying fetal heart beats and determining a fetal heart rate is presented. Multiple sensor signals are outputted by a passive fetal heart rate monitoring sensor. Multiple parallel nonlinear filters filter these multiple sensor signals to identify fetal heart beats in the signal data. A processor determines a fetal heart rate based on these identified fetal heart beats. The processor includes the use of a figure of merit weighting of heart rate estimates based on the identified heart beats from each filter for each signal. The fetal heart rate thus determined is outputted to a display, storage, or communications channel. A method for enhanced fetal heart beat discrimination includes acquiring signals from a fetus, identifying fetal heart beats from the signals by multiple parallel nonlinear filtering, and determining a fetal heart rate based on the identified fetal heart beats. A figure of merit operation in this method provides for weighting a plurality of fetal heart rate estimates based on the identified fetal heart beats and selecting the highest ranking fetal heart rate estimate.

Zahorian, Stephen A.↗

Passive fetal heart rate monitoring apparatus and method with enhanced fetal heart beat discrimination

An apparatus for acquiring signals emitted by a fetus, identifying fetal heart beats and determining a fetal heart rate. Multiple sensor signals are outputted by a passive fetal heart rate monitoring sensor. Multiple parallel nonlinear filters filter these multiple sensor signals to identify fetal heart beats in the signal data. A processor determines a fetal heart rate based on these identified fetal heart beats. The processor includes the use of a figure of merit weighting of heart rate estimates based on the identified heart beats from each filter for each signal. The fetal heart rate thus determined is outputted to a display, storage, or communications channel. A method for enhanced fetal heart beat discrimination includes acquiring signals from a fetus, identifying fetal heart beats from the signals by multiple parallel nonlinear filtering, and determining a fetal heart rate based on the identified fetal heart beats. A figure of merit operation in this method provides for weighting a plurality of fetal heart rate estimates based on the identified fetal heart beats and selecting the highest ranking fetal heart rate estimate.

Zahorian, Stephen A.↗

The earth's surface studied from space; Proceedings of Workshop II of the COSPAR 25th Plenary Meeting, Graz, Austria, June 25-July 7, 1984

Consideration is given to: Landsat image data quality studies; a preliminary evaluation of Landsat-4 Thematic Mapper (TM) data for mineral exploration; and the early evaluation of TM data for mapping forest, agricultural and soil resources. Among other topics discussed are: shortwave infrared detection of vegetation; SPOT image quality and post-launch assessment; an evaluation of SPOT HRV simulation data for Corps of Engineers applications; and the application potential of SPOT imagery for topographic mapping. Consideration is also given to: verification studies of MOS-1 sensors; multiple sensor geocoded data; and the utility of proposed sensors for coastal engineering studies.

Ungar, S. G.↗

Coherent Uncertainty Analysis of Aerosol Measurements from Multiple Satellite Sensors

Aerosol retrievals from multiple spaceborne sensors, including MODIS (on Terra and Aqua), MISR, OMI, POLDER, CALIOP, and SeaWiFS altogether, a total of 11 different aerosol products were comparatively analyzed using data collocated with ground-based aerosol observations from the Aerosol Robotic Network (AERONET) stations within the Multi-sensor Aerosol Products Sampling System (MAPSS, http://giovanni.gsfc.nasa.gov/mapss/ and http://giovanni.gsfc.nasa.gov/aerostat/). The analysis was performed by comparing quality-screened satellite aerosol optical depth or thickness (AOD or AOT) retrievals during 2006-2010 to available collocated AERONET measurements globally, regionally, and seasonally, and deriving a number of statistical measures of accuracy. We used a robust statistical approach to detect and remove possible outliers in the collocated data that can bias the results of the analysis. Overall, the proportion of outliers in each of the quality-screened AOD products was within 12%. Squared correlation coefficient (R2) values of the satellite AOD retrievals relative to AERONET exceeded 0.6, with R2 for most of the products exceeding 0.7 over land and 0.8 over ocean. Root mean square error (RMSE) values for most of the AOD products were within 0.15 over land and 0.09 over ocean. We have been able to generate global maps showing regions where the different products present advantages over the others, as well as the relative performance of each product over different landcover types. It was observed that while MODIS, MISR, and SeaWiFS provide accurate retrievals over most of the landcover types, multi-angle capabilities make MISR the only sensor to retrieve reliable AOD over barren and snow / ice surfaces. Likewise, active sensing enables CALIOP to retrieve aerosol properties over bright-surface shrublands more accurately than the other sensors, while POLDER, which is the only one of the sensors capable of measuring polarized aerosols, outperforms other sensors in certain smoke-dominated regions, including broadleaf evergreens in Brazil and South-East Asia.

remote sensing↗

Cross-Characterization of Aerosol Properties from Multiple Spaceborne Sensors Facilitated by Regional Ground-Based Observations

Aerosol observations from space have become a standard source for retrieval of aerosol properties on both regional and global scales. Indeed, the large number of currently operational spaceborne sensors provides for unprecedented access to the most complete set of complimentary aerosol measurements ever to be available. Nonetheless, this resource remains under-utilized, largely due to the discrepancies and differences existing between the sensors and their aerosol products. To characterize the inconsistencies and bridge the gap that exists between the sensors, we have designed and implemented an online Multi-sensor Aerosol Products Sampling System (MAPSS) that facilitates the joint sampling of aerosol data from multiple sensors. MAPSS consistently samples aerosol products from multiple spaceborne sensors using a unified spatial and temporal resolution, where each dataset is sampled over Aerosol Robotic Network (AERONET) locations together with coincident AERONET data samples. In this way, MAPSS enables a direct cross-characterization and data integration between aerosol products from multiple sensors. Moreover, the well-characterized co-located ground-based AERONET data provides the basis for the integrated validation of these products.

Petrenko, Maksym↗

Phase discriminating capacitive array sensor system

A phase discriminating capacitive sensor array system which provides multiple sensor elements which are maintained at a phase and amplitude based on a frequency reference provided by a single frequency stabilized oscillator. Sensor signals provided by the multiple sensor elements are controlled by multiple phase control units, which correspond to the multiple sensor elements, to adjust the sensor signals from the multiple sensor elements based on the frequency reference. The adjustment made to the sensor signals is indicated by output signals which indicate the proximity of the object. The output signals may also indicate the closing speed of the object based on the rate of change of the adjustment made, and the edges of the object based on a sudden decrease in the adjustment made.

Vranish, John M.↗

Spatial Distribution of Accuracy of Aerosol Retrievals from Multiple Satellite Sensors

Remote sensing of aerosols from space has been a subject of extensive research, with multiple sensors retrieving aerosol properties globally on a daily or weekly basis. The diverse algorithms used for these retrievals operate on different types of reflected signals based on different assumptions about the underlying physical phenomena. Depending on the actual retrieval conditions and especially on the geographical location of the sensed aerosol parcels, the combination of these factors might be advantageous for one or more of the sensors and unfavorable for others, resulting in disagreements between similar aerosol parameters retrieved from different sensors. In this presentation, we will demonstrate the use of the Multi-sensor Aerosol Products Sampling System (MAPSS) to analyze and intercompare aerosol retrievals from multiple spaceborne sensors, including MODIS (on Terra and Aqua), MISR, OMI, POLDER, CALIOP, and SeaWiFS. Based on this intercomparison, we are determining geographical locations where these products provide the greatest accuracy of the retrievals and identifying the products that are the most suitable for retrieval at these locations. The analyses are performed by comparing quality-screened satellite aerosol products to available collocated ground-based aerosol observations from the Aerosol Robotic Network (AERONET) stations, during the period of 2006-2010 when all the satellite sensors were operating concurrently. Furthermore, we will discuss results of a statistical approach that is applied to the collocated data to detect and remove potential data outliers that can bias the results of the analysis.

Petrenko, Maksym↗

Coherent Evaluation of Aerosol Data Products from Multiple Satellite Sensors

Aerosol retrieval from satellite has practically become routine, especially during the last decade. However, there is often disagreement between similar aerosol parameters retrieved from different sensors, thereby leaving users confused as to which sensors to trust for answering important science questions about the distribution, properties, and impacts of aerosols. As long as there is no consensus, and the inconsistencies are not well characterized and understood, there will be no way of developing reliable model inputs and climate data records from satellite aerosol measurements. Fortunately, the Aerosol Robotic Network (AERONET) is providing well-calibrated globally representative ground-based aerosol measurements corresponding to the satellite-retrieved products. Through a recently developed web-based Multi-sensor Aerosol Products Sampling System (MAPSS), we are utilizing the advantages offered by collocated AERONET and satellite products to characterize and evaluate aerosol retrieval from multiple sensors. Indeed, MAPSS and its companion statistical tool AeroStat are facilitating detailed comparative uncertainty analysis of satellite aerosol measurements from Terra-MODIS, Aqua-MODIS, Terra-MISR, Aura-OMI, Parasol-POLDER, and Calipso-CALIOP. In this presentation, we will describe the strategy of the MAPSS system, its potential advantages for the aerosol community, and the preliminary results of an integrated comparative uncertainly analysis of aerosol products from multiple satellite sensors.

Ichoku, Charles↗

DRAGONS-A Micrometeoroid and Orbital Debris Impact Sensor on the ISS

The Debris Resistive/Acoustic Grid Orbital Navy-NASA Sensor (DRAGONS) is intended to be a large area impact sensor for in situ measurements of micrometeoroids and orbital debris (MMOD) in the sub-millimeter to millimeter size regime in the near Earth space environment. These MMOD particles are too small to be detected by ground-based radars and optical telescopes, but still large enough to be a serious threat to human space activities and robotic missions in the low Earth orbit (LEO) region. The nominal detection area of DRAGONS is 1 sq m, consisting of four 0.5 m × 0.5 m independent panels, but the dimensions of the panels can easily be modified to accommodate different payload constraints. The approach of the DRAGONS design is to combine three particle impact detection concepts to maximize information that can be extracted from each detected impact. The first is a resistive grid consisting of 75-micrometer-wide resistive lines, coated in parallel and separated by 75 micrometer gaps on a 25-micrometer thin film. When a particle a few hundred micrometers or larger strikes the grid, it would penetrate the film and sever some resistive lines. The size of the damage area can be estimated from the increased resistance. The second concept is based on polyvinylidene fluoride (PVDF) acoustic impact sensors. Multiple PVDF sensors are attached to the thin film to provide the impact timing information. From the different signal arrival times at different acoustic sensors, the impact location can be calculated via triangulation algorithms. The third concept employs a dual-layer film system where a second 25-micrometer film is placed 15 cm behind the resistive-grid film. Multiple PVDF acoustic sensors are also attached to the second film. The combination of impact timing and location information from the two films allows for direct measurements of the impact direction and speed. The DRAGONS technology development has been funded by several NASA organizations since 2002, first by the NASA Science Mission Directorate and the NASA Exploration Systems Mission Directorate, then by the NASA JSC Innovative Research and Development Program and the NASA Orbital Debris Program Office. The NASA Orbital Debris Program Office leads the effort with collaboration from the U.S. Naval Academy, Naval Research Laboratory, University of Kent at Canterbury in Great Britain, and Virginia Tech. The project recently reached a major milestone when DRAGONS was approved for a technology demonstration mission by the International Space Station (ISS) Program in October 2014. The plan is to deploy a 1 sq m DRAGONS on the ISS with the detection surface facing the ram-direction for 2 to 3 years. The tentative launch schedule is in early 2017. This mission will collect data on orbital debris in the sub-millimeter size regime to better define the small orbital debris environment at the ISS altitude. The mission will also advance the DRAGONS Technology Readiness Level to 9 and greatly enhance the opportunities to deploy DRAGONS on other spacecraft to high LEO orbits in the future.

Liou, J.-C.↗

Field Evaluation of Portable Soil Water Content Sensors in a Sandy Loam

Ground observations are critical in the validation of soil water content (SWC) estimates from both satellites and land surface models. Portable SWC sensors provide useful information to determine the amount of SWC in the topsoil layer for various applications; however, these probes are not accurate without site‐specific correction. In the present study, we examined and compared six different types of portable electromagnetic (EM) SWC sensors, including multiple sensors made by the same manufacturers, for a total of 16 EM‐based SWC probes equipped with portable data loggers. All SWC probes met the target accuracy after onsite correction—the RMSD was <0.025 m(exp 3) m(exp -3). Using the two‐sample t-tests, we observed that SWC data obtained from similar electrode lengths and from different manufacturers showed similar distributions over time with the same mean. Furthermore, using the maximize R method to combine SWC data from two different types of sensors increased the accuracy of the results. When datasets from two different types of sensors were combined, the Pearson's correlation coefficient (R value) and RMSD values were improved. The average R value improved from .930 to .945, and the RMSD decreased from 0.036 m(exp 3) m(exp -3) to 0.018 m(exp 3) m(exp −3). These results indicate that, along with site‐specific correction, synergetic use of multiple manufacturers’ EM‐based SWC probes can improve the R value and reduce systematic bias.

soil moisture data↗

FPGA development for high altitude subsonic parachute testing

This paper describes a rapid, top down requirements-driven design of an FPGA used in an Earth qualification test program for a new Mars subsonic parachute. The FPGA is used to process and store data from multiple sensors at multiple rates during launch, ascent, deployment and descent phases of the subsonic parachute test.

telemetry↗

North American Vegetation Dynamics Observed with Multi-Resolution Satellite Data

North American vegetation has been discovered to be a net carbon sink, with atypical behavior of drawing down more carbon from the atmosphere during the past century. It has been suggested that the Northern Hemisphere will respond favorably to climate warming by enhancing productivity and reducing the impact of fossil fuel emissions into the atmosphere. Many investigations are currently underway to understand and identify mechanisms of storage so they might be actively managed to offset carbon emissions which have detrimental consequences to the functioning of ecosystems and human well being. This paper used a time series of satellite data from multiple sensors at multiple resolutions over the past thlrty years to identify and understand mechanisms of change to vegetation productivity throughout North America. We found that humans had a marked impact to vegetation growth in half of the six selected study regions which cover greater than two million km2. We found climatic influences of increasing temperatures, and longer growing seasons with reduced snow cover in the northern regions of North America with forest fire recovery in the Northern coniferous forests of Canada. The Mid-latitudes had more direct land cover changes induced by humans coupled with climatic influences such as severe drought and altered production strategies of rain-fed agriculture in the upper Midwest, expansion of irrigated agriculture in the lower Midwest, and insect outbreaks followed by subsequent logging in the upper Northeast. Vegetation growth over long time periods (20+ years) in North America appears to be associated with long term climate change but most of the marked changes appear to be associated with climate variability on decadal and shorter time scales along with direct human land cover conversions. Our results document regional land cover land use change and climatic influences that have altered continental scale vegetation dynamics in North America.

Neigh, Christopher S. R.↗

DRAGONS - A Micrometeoroid and Orbital Debris Impact Sensor

The Debris Resistive/Acoustic Grid Orbital Navy Sensor (DRAGONS) is intended to be a large area impact sensor for in-situ measurements of micrometeoroids and orbital debris (MMOD) in the approx.0.2 to 1 mm size regime. These MMOD particles are too small to be detected by groundbased radars and optical telescopes, but still large enough to be a safety concern for human space activities and robotic missions in the low Earth orbit (LEO) region. The nominal detection area of DRAGONS is 1 sq m, consisting of four 0.5 m x 0.5 m independently operated panels. The concept of the DRAGONS design is to combine three different detection technologies to maximize information extracted from each detected impact. The first technology is a resistive grid consisting of 62.5-microns-wide resistive lines, coated in parallel and separated by 62.5 micron gaps on a Kapton film. When a particle a few hundred micrometers or larger strikes the grid, it world penetrate the film and sever some resistive lines. The size of the damage area can be estimated from the increased resistance. The second technology employs a dual-layer, 25-microns-thick Kapton film with a 10 cm separation. By measuring the time difference between impacts on the two films, the impact speed can be calculated. The third technology is based on polyvinylidene fluoride (PVDF) acoustic impact sensors. Multiple PVDF sensors are attached to the backside of both Kapton films to provide impact timing measurements. The impact location on each film can be identified from the triangulation of signals received at different PVDF sensors and provides an estimate of the impact direction. The development of DRAGONS is supported by the NASA Orbital Debris Program Office. The project is led by the U.S. Naval Academy (USNA), with additional collaboration from the U.S. Naval Research Laboratory (NRL), the University of Kent at Canterbury in Great Britain, and Virginia Tech (VT). The short-term goal of DRAGONS is to advance its Technology Readiness Level to 9 and to demonstrate the system capabilities of detecting and characterizing submillimeter MMOD impacts. The long-term goal is to deploy a large detection area (>1 sq m) DRAGONS to 700-1000 km altitude and collect sufficient data for better environment definition of MMOD in the 0.2- to 1-mm size regime. The Preliminary Design Review (PRD) of DRAGONS was held at the USNA in June 2012. The Critical Design Review (CDR) is scheduled for early 2013. A flight-ready unit with a 0.25 sq m detection area will be completed and tested by the end of September 2013. The biggest challenge for the project, however, is to identify a demonstration opportunity on the International Space Station in the coming years.

Liou, J. C.↗

Multiple-Parameter, Low-False-Alarm Fire-Detection Systems

Fire-detection systems incorporating multiple sensors that measure multiple parameters are being developed for use in storage depots, cargo bays of ships and aircraft, and other locations not amenable to frequent, direct visual inspection. These systems are intended to improve upon conventional smoke detectors, now used in such locations, that reliably detect fires but also frequently generate false alarms: for example, conventional smoke detectors based on the blockage of light by smoke particles are also affected by dust particles and water droplets and, thus, are often susceptible to false alarms. In contrast, by utilizing multiple parameters associated with fires, i.e. not only obscuration by smoke particles but also concentrations of multiple chemical species that are commonly generated in combustion, false alarms can be significantly decreased while still detecting fires as reliably as older smoke-detector systems do. The present development includes fabrication of sensors that have, variously, micrometer- or nanometer-sized features so that such multiple sensors can be integrated into arrays that have sizes, weights, and power demands smaller than those of older macroscopic sensors. The sensors include resistors, electrochemical cells, and Schottky diodes that exhibit different sensitivities to the various airborne chemicals of interest. In a system of this type, the sensor readings are digitized and processed by advanced signal-processing hardware and software to extract such chemical indications of fires as abnormally high concentrations of CO and CO2, possibly in combination with H2 and/or hydrocarbons. The system also includes a microelectromechanical systems (MEMS)-based particle detector and classifier device to increase the reliability of measurements of chemical species and particulates. In parallel research, software for modeling the evolution of a fire within an aircraft cargo bay has been developed. The model implemented in the software can describe the concentrations of chemical species and of particulate matter as functions of time. A system of the present developmental type and a conventional fire detector were tested under both fire and false-alarm conditions in a Federal Aviation Administration cargo-compartment- testing facility. Both systems consistently detected fires. However, the conventional fire detector consistently generated false alarms, whereas the developmental system did not generate any false alarms.

Hunter, Gary W.↗

Using DSCOVR EPIC as a Transfer Radiometer to Scale Multiple VIIRS Sensors Over Tropical Earth Views

The NASA CERES project provides Energy Balanced and Filled (EBAF) product climate-quality observed TOA and computed surface fluxes to the climate community. The CERES instruments are on board the Terra, Aqua, Suomi-NPP, and NOAA-20 satellites. The CERES project radiometrically scales the MODIS and VIIRS imager visible channel radiances to the Aqua- MODIS reference to retrieve consistent imager cloud properties between sensors, which are used to retrieve cloud properties required for converting CERES radiance observations into fluxes. The NPP, NOAA-20, and the future NOAA-21 VIIRS imagers will be in the same sun- synchronous orbit but spaced equally apart, which means that no simultaneous nadir overpasses (SNO) may be used to inter-calibrate the VIIRS imagers to each one another. Currently, the CERES project uses Aqua-MODIS to radiometrically scale between VIIRS imagers. Once the Terra and Aqua satellites start drifting toward the terminator, Aqua-MODIS can no longer be utilized as the transfer radiometer between VIIRS sensors and there will be no SNOs in common between either MODIS and or VIIRS imagers. The DSCOVR satellite orbits the Lagrange-1 (L1) point about 1.5 million kilometers from Earth. The Earth Polychromatic Imaging Camera (EPIC) instrument on the Earth-facing side of DSCOVR takes images ranging from the UV to the NIR of the sunlit side of the Earth. While the EPIC sensor has no onboard calibration systems, multiple inter-calibration studies have indicated that the EPIC instrument response is radiometrically stable. The stability of the EPIC instrument allows it to be used as a transfer radiometer between all MODIS and VIIRS imagers and is especially suited for drifting orbits because EPIC imager frequently samples the Earth diurnally. The study will demonstrate the use of EPIC as a transfer radiometer to radiometrically scale the NPP and NOAA-20 VIIRS imagers. The scaling factors will be compared with the scaling factors using Aqua-MODIS as the transfer radiometer.

Conor Haney↗

Retrieving the Height of Smoke and Dust Aerosols by Synergistic Use of Multiple Satellite Sensors

The Aerosol Single scattering albedo and Height Estimation (ASHE) algorithm was first introduced in Jeong and Hsu (2008) to provide aerosol layer height and single scattering albedo (SSA) for biomass burning smoke aerosols. By using multiple satellite sensors synergistically, ASHE can provide the height information over much broader areas than lidar observations alone. The complete ASHE algorithm uses aerosol data from MODIS or VIIRS, OMI or OMPS, and CALIOP. A simplified algorithm also exists that does not require CALIOP data as long as the SSA of the aerosol layer is provided by another source. Several updates have recently been made: inclusion of dust layers in the retrieval process, better determination of the input aerosol layer height from CALIOP, improvement in aerosol optical depth (AOD) for nonspherical dust, development of quality assurance (QA) procedure, etc.

satellite remote sensing↗

Toward a Coherent Detailed Evaluation of Aerosol Data Products from Multiple Satellite Sensors

Atmospheric aerosols represent one of the greatest uncertainties in climate research. Although satellite-based aerosol retrieval has practically become routine, especially during the last decade, there is often disagreement between similar aerosol parameters retrieved from different sensors, leaving users confused as to which sensors to trust for answering important science questions about the distribution, properties, and impacts of aerosols. As long as there is no consensus and the inconsistencies are not well characterized and understood, there will be no way of developing reliable climate data records from satellite aerosol measurements. Fortunately, the most globally representative well-calibrated ground-based aerosol measurements corresponding to the satellite-retrieved products are available from the Aerosol Robotic Network (AERONET). To adequately utilize the advantages offered by this vital resource, an online Multi-sensor Aerosol Products Sampling System (MAPSS) was recently developed. The aim of MAPSS is to facilitate detailed comparative analysis of satellite aerosol measurements from different sensors (Terra-MODIS, Aqua-MODIS, TerraMISR, Aura-OMI, Parasol-POLDER, and Calipso-CALIOP) based on the collocation of these data products over AERONET stations. In this presentation, we will describe the strategy of the MA~SS system, its potential advantages for the aerosol community, and the preliminary results of an integrated comparative uncertainly analysis of aerosol products from multiple satellite sensors.

Ichoku, Charles↗