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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS1991

Debris mapping sensor technology project summary: Technology flight experiments program area of the space platforms technology program

The topics presented are covered in viewgraph form. Programmatic objectives are: (1) to improve characterization of the orbital debris environment; and (2) to provide a passive sensor test bed for debris collision detection systems. Technical objectives are: (1) to study LEO debris altitude, size and temperature distribution down to 1 mm particles; (2) to quantify ground based radar and optical data ambiguities; and (3) to optimize debris detection strategies.

Source record↗
NASA NTRS2010

Solid-State, High Energy 2-Micron Laser Development for Space-Based Remote Sensing

Lidar (light detection and ranging) remote sensing enjoys the advantages of excellent vertical and horizontal resolution; pointing capability; a signal source independent from natural light; and control and knowledge of transmitted wavelength, pulse shape, and polarization and received polarization. Lidar in space is an emerging technology now being developing to fit applications where passive sensors cannot meet current measurement requirements. Technical requirements for space lidar are more demanding than for ground-based or airborne systems. Perhaps the most distinguishing characteristics of space lidars are the environmental requirements. Space lidar systems must be specially designed to survive the mechanical vibration loads of launch and operate in the vacuum of space where exposure to ionizing radiation limits the electronic components available. Finally, space lidars must be designed to be highly reliable because they must operate without the need for repair or adjustment. Lifetime requirements tend to be important drivers of the overall system design. The maturity of the required technologies is a key to the development of any space lidar system. NASA entered a new era in the 1990 s with the approval of several space-based remote sensing missions employing laser radar (lidar) techniques. Following the steps of passive remote sensing and then active radar remote sensing, lidar sensors were a logical next step, providing independence from natural light sources, and better spatial resolution and smaller sensor size than radar sensors. The shorter electromagnetic wavelengths of laser light also allowed signal reflectance from air molecules and aerosol particles. The smaller receiver apertures allowed the concept of scanning the sensor field of view. However, technical problems with several space-based lidar missions during that decade led to concern at NASA about the risk of lidar missions. An external panel was convened to make recommendations to NASA. Their report in 2000 strongly advocated that NASA maintain in-house laser and lidar capability, and that NASA should work to lower the technology risk for all future lidar missions. A multi-Center NASA team formulated an integrated NASA strategy to provide the technology and maturity of systems necessary to make Lidar/Laser systems viable for space-based study and monitoring of the Earth's atmosphere. In 2002 the NASA Earth Science Enterprise (ESE) and Office of Aerospace Technology (OAT) created the Laser Risk Reduction Program (LRRP) and directed NASA Langley Research Center (LaRC) and Goddard Space Flight Center to carry out synergistic and complementary research towards solid-state lasers/lidars developments for space-based remote sensing applications.

Singh, Upendra N.↗
NASA NTRS1990

Kalman filter based range estimation for autonomous navigation using imaging sensors

The ability to detect and locate obstacles using on-board sensors and modify the nominal trajectory is necessary for safe landing of an autonomous lander on Mars. This paper examines some of the issues in the location of objects using a sequence of images from a passive sensor, and describes a Kalman filter approach to improve the range estimation to obstacles. The filter is also used to track features in the images leading to a significant reduction of search effort in the feature extraction step of the algorithm. The lack of suitable flight imagery data presents a problem in the verification of concepts for obstacle detection. An experiment is designed to acquire a sequence of images along with sensor motion parameters and the range estimation results using this imagery are presented.

Sridhar, B.↗
NASA NTRS2011

Airborne Remote Observations of L-Band Radio Frequency Interference and Implications for Satellite Missions

Passive remote sensing of the Earth s surface and atmosphere from space has significant importance in operational and research environmental studies, in particular for the scientific understanding, monitoring and prediction of climate change and its impacts. Passive remote sensing requires the measurement of naturally occurring radiations, usually of very low power levels, which contain essential information on the physical process under investigation. As such, these sensed radio frequency bands are a unique natural resource enabling space borne passive sensing of the atmosphere and the Earth s surface that deserves adequate allocation to the Earth Exploration Satellite Service and absolute protection from interference. Unfortunately, radio frequency interference (RFI) is an increasing problem for Earth remote sensing, particularly for passive observations of natural emissions. Because these natural signals tend to be very weak, even low levels of interference received by a passive sensor may degrade the fidelity of scientific data. The characteristics of RFI (low-level interference and radar-pulse noise) are not well known because there has been no systematic surveillance, spectrum inventory or mapping of RFI. While conducting a flight experiment over central Tennessee in May 2010, RFI, a concern for any instrument operating in the passive L band frequency, was observed across 16 subbands between 1402-1427 MHz. Such a survey provides rare characterization data from which to further develop mitigation technologies as well as to identify bandwidths to avoid in future sensor formulation.

Laymon, Charles↗
NASA NTRS2019

Can OMPS and VIIRS Be Used as a Single Virtual Sensor for Aerosol Retrieval?

Satellite earth observation of aerosols using a single sensor have been done for more than three decades. The retrieved global distribution of column integrated aerosol optical depth (AOD) has been refined with higher accuracy and finer resolutions. However, the other aerosol properties, such as aerosol absorption and aerosol height, haven not been mapped as extensively using passive sensors. The detectors sensitive to these properties (UV-based sensors such as Aura-OMI) lack the adequate visible channels to tease out the absorption, height and loading contributions. In addition, their spatial resolution is prone to frequent cloud contamination impacting aerosol loading retrievals using only these spectral ranges. However, the deployment of the VIIRS and OMPS-NM sensors on the same Suomi NPP platform provides a first opportunity to carry out retrievals of aerosol single scattering albedo (SSA) and AOD with little cloud contamination using an expanded spectral range from the UV to the near-IR wavelengths. After collocated VIIRS pixel within the large OMPS footprint during the high resolution OMPS observing mode, we compared the radiance from OMPS and VIIRS to ensure the calibration from individual sensors are comparable. Then a look up table (LUT) was created for a smoke case over central Africa. The LUT is generated using 10 channels from 0.357 to 2.1 micron with 44 combinations of aerosol models and 4 different aerosol heights. With CALIOP and AERONET observation nearby, the possibility of using OMPS and VIIRS radiance as a single virtual sensor to simultaneously and consistently retrieve AOD, SSA, and aerosol height is explored.

Shi, Yingxi↗
NASA NTRS1993

Simulation of a passive millimeter wave sensor

The visual display expected to be generated by a Passive Millimeter Wave (PMMW) camera and sensor system has been simulated on a Silicon Graphics IRIS workstation at the NASA Langley Research Center (LaRC). The low resolution of the sensor has been simulated by graphically manipulating the scene as it is being drawn by the IRIS in real time. Camera field of view, sensor resolution, and sensor update rate are the controllable parameters. Physical effects such as lens model, radome effects, and noise have not been included at this time. An approximate dynamic model of the atmospheric phenomenology has been included which generates the gray-scale intensity values in real time for the simulated image. The gray-scale values are proportional to temperature. A snapshot capability which captures individual image frames during real-time operation has been included. These images were used to validate the approximate phenomenology model against a more rigorous physical model.

Kahlbaum, William W.↗
NASA NTRS1994

Robotic vision techniques for space operations

Automation and robotics for space applications are being pursued for increased productivity, enhanced reliability, increased flexibility, higher safety, and for the automation of time-consuming tasks and those activities which are beyond the capacity of the crew. One of the key functional elements of an automated robotic system is sensing and perception. As the robotics era dawns in space, vision systems will be required to provide the key sensory data needed for multifaceted intelligent operations. In general, the three-dimensional scene/object description, along with location, orientation, and motion parameters will be needed. In space, the absence of diffused lighting due to a lack of atmosphere gives rise to: (a) high dynamic range (10(exp 8)) of scattered sunlight intensities, resulting in very high contrast between shadowed and specular portions of the scene; (b) intense specular reflections causing target/scene bloom; and (c) loss of portions of the image due to shadowing and presence of stars, Earth, Moon, and other space objects in the scene. In this work, developments for combating the adverse effects described earlier and for enhancing scene definition are discussed. Both active and passive sensors are used. The algorithm for selecting appropriate wavelength, polarization, look angle of vision sensors is based on environmental factors as well as the properties of the target/scene which are to be perceived. The environment is characterized on the basis of sunlight and other illumination incident on the target/scene and the temperature profiles estimated on the basis of the incident illumination. The unknown geometrical and physical parameters are then derived from the fusion of the active and passive microwave, infrared, laser, and optical data.

Krishen, Kumar↗
NASA NTRSDate not supplied

Cloud Macrophysical Changes Observed by MODIS, CALIPSO, and CloudSat for the 11-year Period

Using the Moderate Resolution Imaging Spectroradiometer (MODIS), Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO), and CloudSatsatellitemeasurements, cloud macrophysicalchanges are examined from 2007 to 2017(Ham et al., 2021). Particularly, we compare cloud changes derived from MODIS passive sensor and CALIPSO-CloudSat (CALCS) combined active sensor measurements. Both MODIS and CALCS well capture general features of the cloud changes related to El Niño–Southern Oscillation (ENSO) events. However, because of better detections of thin cirrus clouds, CALCS cloud volume anomalies are better correlated with relative humidity anomalies, compared to MODIS. In addition, MODIS observations show a stronger anticorrelation between low and mid/high cloud volume anomalies, compared to CALCS, mainly due to limitations in detecting overlapping clouds by MODIS passive sensor.In addition, the geometrical thickness of MODIS mid/high clouds is thinner than that from CALCS, less affecting cloud amounts at 0-3 km altitude.

Cloud↗
NASA NTRS1999

A Novel Technique for Performing Space Based Radiation Dosimetry Using DNA-Results from GRaDEx-I and the Design of GRaDEx-II

Because of the large amounts of cosmic radiation in the space environment relative to that on earth, the effects of radiation on the physiology of astronauts is of major concern. Doses of radiation which can cause acute or chronic biological effects are to be avoided, therefore determination of the amount of radiation exposure encountered during space flight and assessment of its impact on biological systems is critical. Quantifying the radiation dosage and damage to biological systems, especially to humans during repetitive high altitude flight and during long duration space flight is important for several reasons. Radiation can cause altered biosynthesis and long term genotoxicity resulting in cancer and birth defects etc. Radiation damage to biological systems depends in a complex way on incident radiation species and their energy spectra. Typically non-biological, i.e. film or electronic monitoring systems with narrow energy band sensitivity are used to perform dosimetry and then results are extrapolated to biological models. For this reason it may be desirable to perform radiation dosimetry by using biological molecules e.g. DNA or RNA strands as passive sensors. A lightweight genotoxicology experiment was constructed to determine the degree to which in vitro naked DNA extracted from tissues of a variety of vertebrate organisms is damaged by exposure to radiation in a space environment. The DNA is assayed by means of agarose gel electrophoresis to determine damage such as strand breakage caused by high momentum particles and photons, and base oxidation caused by free radicals. The length distribution of DNA fragments is directly correlated with the radiation dose. It is hoped that a low mass, low cost, passive biological system to determine dose response relationship (increase in strand breaks with increase in exposure) can be developed to perform radiation dosimetry in support of long duration space flight, and to predict negative effects on biological systems (e.g. astronauts and greenhouses) in space. The payload was flown in a 2.5 cubic foot Get Away Special (GAS) container through NASA's GAS program. It was subjected to the environment of the space shuttle cargo bay for the duration of the STS-91 mission (9 days). Results of the genotoxicology and radiation dosimetry experiment (GRaDEx-1) as well as the design of an improved follow on payload are presented.

Ritter, Joe↗
NASA NTRS1999

A Novel Technique for Performing Space Based Radiation Dosimetry Using DNA: Results from GRaDEx-I and the Design of GRaDEx-II

Because of the large amounts of cosmic radiation in the space environment relative to that on earth, the effects of radiation on the physiology of astronauts is of major concern. Doses of radiation which can cause acute or chronic biological effects are to be avoided, therefore determination of the amount of radiation exposure encountered during space flight and assessment of its impact on biological systems is critical. Quantifying the radiation dosage and damage to biological systems, especially to humans during repetitive high altitude flight and during long duration space flight is important for several reasons. Radiation can cause altered biosynthesis and long term genotoxicity resulting in cancer and birth defects, etc. Radiation damage to biological systems depends in a complex way on incident radiation species and their energy spectra. Typically non-biological, i.e. film or electronic monitoring systems with narrow energy band sensitivity are used to perform dosimetry and then results are extrapolated to biological models. For this reason it may be desirable to perform radiation dosimetry by using biological molecules e.g. DNA or RNA strands as passive sensors. A lightweight genotoxicology experiment was constructed to determine the degree to which in-vitro naked DNA extracted from tissues of a variety of vertebrate organisms is damaged by exposure to radiation in a space environment. The DNA is assayed by means of agarose gel electrophoresis to determine damage such as strand breakage caused by high momentum particles and photons, and base oxidation caused by free radicals. The length distribution of DNA fragments is directly correlated with the radiation dose. It is hoped that a low mass, low cost, passive biological system to determine dose-response relationship (increase in strand breaks with increase in exposure) can be developed to perform radiation dosimetry in support of long duration space flight, and to predict negative effects on biological systems (e.g. astronauts and greenhouses) in space. The payload was flown in a 2.5 cubic foot Get Away Special (GAS) container through NASA's GAS program. It was subjected to the environment of the space shuttle cargo bay for the duration of the STS-91 mission (9 days). Results of the genotoxicology and radiation dosimetry experiment (GRaDEx-I) as well as the design of an improved follow on payload are presented.

Ritter, Joe↗
NASA NTRS2000

Recent Enhancements of the Phased Array Mirror Extendible Large Aperture (PAMELA) Telescope Testbed at MSFC

Recent incremental upgrades to the Phased Array Mirror Extendible Large Aperture (PAMELA) telescope testbed have enabled the demonstration of phasing (with a monochromatic source) of clusters of primary mirror segments down to the diffraction limit. PAMELA upgrades include an improved Shack-Hartmann wavefront sensor, passive viscoelastic damping treatments for the voice-coil actuators, mechanical improvement of mirror surface figures, and optical bench baffling. This report summarizes the recent PAMELA upgrades, discusses the lessons learned, and presents a status of this unique testbed for wavefront sensing and control. The Marshall Space Flight Center acquired the Phased Array Mirror Extendible Large Aperture (PAMELA) telescope in 1993 after Kaman Aerospace was unable to complete integration and testing under the limited SDIO and DARPA funding. The PAMELA is a 36-segment, half-meter aperture, adaptive telescope which utilizes a Shack-Hartmann wavefront sensor, inductive coil edge sensors, voice coil actuators, imaging CCD cameras and interferometry for figure alignment, wavefront sensing and control. MSFC originally obtained the PAMELA to supplement its research in the interactions of control systems with flexible structures. In August 1994, complete tip, tilt and piston control was successfully demonstrated using the Shack-Hartmann wavefront sensor and the inductive edge sensors.

Rakoczy, John↗
NASA NTRS2001

Recent Enhancements of the Phased Array Mirror Extendible Large Aperture (PAMELA) Telescope Testbed at MSFC

Recent incremental upgrades to the Phased Array Mirror Extendible Large Aperture (PAMELA) telescope testbed have enabled the demonstration of phasing (with a monochromatic source) of clusters of primary mirror segments down to the diffraction limit. PAMELA upgrades include in improved Shack-Hartmann wavefront sensor, passive viscoelastic damping treatments for the voice-coil actuators, mechanical improvement of mirror surface figures, and optical bench baffling. This report summarizes the recent PAMELA upgrades, discusses the lessons learned, and presents a status of this unique testbed for wavefront sensing and control. The Marshall Space Flight Center acquired the Phased Array Mirror Extendible Large Aperture (PAMELA) telescope in 1993 after Kaman Aerospace was unable to complete integration and testing under the limited SDIO and DARPA funding. The PAMELA is a 36-segment, half-meter aperture, adaptive telescope which utilizes a Shack-Hartmann wavefront sensor, inductive coil edge sensors, voice coil actuators, imaging CCD cameras and interferometry for figure alignment, wavefront sensing and control. MSFC originally obtained the PAMELA to supplement its research in the interactions of control systems with flexible structures. In August 1994, complete tip, tilt and piston control was successfully demonstrated using the Shack-Hartmann wavefront sensor and the inductive edge sensors.

Rakoczy, John↗
NASA NTRS2012

Application of Artificial Neural Networks to the Development of Improved Multi-Sensor Retrievals of Near-Surface Air Temperature and Humidity Over Ocean

Improved estimates of near-surface air temperature and air humidity are critical to the development of more accurate turbulent surface heat fluxes over the ocean. Recent progress in retrieving these parameters has been made through the application of artificial neural networks (ANN) and the use of multi-sensor passive microwave observations. Details are provided on the development of an improved retrieval algorithm that applies the nonlinear statistical ANN methodology to a set of observations from the Advanced Microwave Scanning Radiometer (AMSR-E) and the Advanced Microwave Sounding Unit (AMSU-A) that are currently available from the NASA AQUA satellite platform. Statistical inversion techniques require an adequate training dataset to properly capture embedded physical relationships. The development of multiple training datasets containing only in-situ observations, only synthetic observations produced using the Community Radiative Transfer Model (CRTM), or a mixture of each is discussed. An intercomparison of results using each training dataset is provided to highlight the relative advantages and disadvantages of each methodology. Particular emphasis will be placed on the development of retrievals in cloudy versus clear-sky conditions. Near-surface air temperature and humidity retrievals using the multi-sensor ANN algorithms are compared to previous linear and non-linear retrieval schemes.

Roberts, J. Brent↗
NASA NTRS2005

Global Survey and Statistics of Radio-Frequency Interference in AMSR-E Land Observations

Radio-frequency interference (RFI) is an increasingly serious problem for passive and active microwave sensing of the Earth. To satisfy their measurement objectives, many spaceborne passive sensors must operate in unprotected bands, and future sensors may also need to operate in unprotected bands. Data from these sensors are likely to be increasingly contaminated by RFI as the spectrum becomes more crowded. In a previous paper we reported on a preliminary investigation of RFI observed over the United States in the 6.9-GHz channels of the Advanced Microwave Scanning Radiometer (AMSR-E) on the Earth Observing System Aqua satellite. Here, we extend the analysis to an investigation of RFI in the 6.9- and 10.7-GHz AMSR-E channels over the global land domain and for a one-year observation period. The spatial and temporal characteristics of the RFI are examined by the use of spectral indices. The observed RFI at 6.9 GHz is most densely concentrated in the United States, Japan, and the Middle East, and is sparser in Europe, while at 10.7 GHz the RFI is concentrated mostly in England, Italy, and Japan. Classification of RFI using means and standard deviations of the spectral indices is effective in identifying strong RFI. In many cases, however, it is difficult, using these indices, to distinguish weak RFI from natural geophysical variability. Geophysical retrievals using RFI-filtered data may therefore contain residual errors due to weak RFI. More robust radiometer designs and continued efforts to protect spectrum allocations will be needed in future to ensure the viability of spaceborne passive microwave sensing.

microwave remote sensing↗
NASA NTRS2014

How Well Do Satellite AOD Observations Represent the Spatial and Temporal Variability of PM2.5 Concentration for the United States?

Due to their extensive spatial coverage, satellite Aerosol Optical Depth (AOD) observations have been widely used to estimate and predict surface PM2.5 concentrations. While most previous studies have focused on establishing relationships between collocated, hourly or daily AOD and PM2.5 measurements, in this study, we instead focus on the comparison of the large-scale spatial and temporal variability between satellite AOD and PM2.5 using monthly mean measurements. A newly developed spectral analysis technique e Combined Maximum Covariance Analysis (CMCA) is applied to Moderate Resolution Imaging Spectroradiometer (MODIS), Multi-angle Imaging Spectroradiometer (MISR), Sea-viewing Wide Field-of-view Sensor (SeaWiFS) and Ozone Monitoring Instrument (OMI) AOD datasets and Environmental Protection Agency (EPA) PM2.5 data, in order to extract and compare the dominant modes of variability. Results indicate that AOD and PM2.5 agree well in terms of interannual variability. An overall decrease is found in both AOD and PM2.5 across the United States, with the strongest signal over the eastern US. With respect to seasonality, good agreement is found only for Eastern US, while for Central and Western US, AOD and PM2.5 seasonal cycles are largely different or even reversed. These results are verified using Aerosol Robotic Network (AERONET) AOD observations and differences between satellite and AERONET are also examined. MODIS and MISR appear to have the best agreement with AERONET. In order to explain the disagreement between AOD and PM2.5 seasonality, we further use Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) extinction profile data to investigate the effect of two possible contributing factors, namely aerosol vertical distribution and cloud-free sampling. We find that seasonal changes in aerosol vertical distribution, due to the seasonally varying mixing height, is the primary cause for the AOD and PM2.5 seasonal discrepancy, in particular, the low AOD but high PM2.5 observed during the winter season for Central and Western US. In addition, cloud-free sampling by passive sensors also induces some bias in AOD seasonality, especially for the Western US, where the largest seasonal change in cloud fraction is found. The seasonal agreement between low level (below 500 m AGL), all sky CALIOP AOD and PM2.5 is significantly better than column AOD from MODIS, MISR, SeaWiFS and OMI. In particular, the correlation between low level, all sky AOD and PM2.5 seasonal cycles increases to above 0.7 for Central and Western US, as opposed to near zero or negative correlation for column, clear sky AOD. This result highlights the importance of accounting for the seasonally varying aerosol profiles and cloud-free sampling bias when using column AOD measurements to infer surface PM2.5 concentrations.

MODIS (radiometry)↗
NASA NTRS1975

System definition of SEASAT-A, an ocean observation satellite

SEASAT will be an earth-satellite system designed to monitor and observe ocean dynamics in order to provide data for real-time use and predictive purposes. SEASAT-A will be a prototype satellite which will provide experience for system development and some operational demonstration capability. The SEASAT-A will use passive and active visible, infrared, and microwave sensing techniques. The payload will include a scanning radiometer (SR) and a scanning multichannel microwave radiometer (SMMR), which are passive sensors, a short-pulse altimeter, a scatterometer, and a synthetic aperture radar, which are active. The major functional elements considered in the definition-phase studies are the sensors, data handling, communications, attitude control, power, orbit adjust, thermal control, structures, and mechanical design. An existing satellite bus, with sensors and sensor modules to be developed, is to be used on SEASAT-A.

Rose, J. R.↗
NASA NTRS1978

Analysis of differential absorption lidar from the Space Shuttle

A parametric analysis of the Shuttle-borne differential absorption lidar concept for the measurement of atmospheric trace constituent profiles in the nadir viewing mode is presented. The criterion of an optimum constituent optical depth is developed and applied to generate estimates of range resolved measurement errors. These errors emphasize the fundamental limitations for establishing the feasibility of range-resolved differential absorption lidar measurements from Shuttle. With current lidar system technology, atmospheric backscatter density profiles may be adequately determined up to about 60-km altitude at the doubled-ruby wavelength, 3472 A, for a 1-J/pulse laser and a 1-sq m receiver. Potential range-resolved measurements of stratospheric and mesospheric trace constituents by differential absorption from Shuttle altitudes are limited to H2O, CH4, N2O, O3, and CO, species which can be more easily measured by passive limb viewing techniques. Range-resolved water vapor data for the lower troposphere may be obtained with accuracies which would be competitive with those from passive sensors.

Remsberg, E. E.↗
NASA NTRS1981

Role of optical computers in aeronautical control applications

The role that optical computers play in aircraft control is determined. The optical computer has the potential high speed capability required, especially for matrix/matrix operations. The optical computer also has the potential for handling nonlinear simulations in real time. They are also more compatible with fiber optic signal transmission. Optics also permit the use of passive sensors to measure process variables. No electrical energy need be supplied to the sensor. Complex interfacing between optical sensors and the optical computer is avoided if the optical sensor outputs can be directly processed by the optical computer.

Baumbick, R. J.↗