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Imaging spectroscopy is of growing interest as a new approach to Earth remote sensing. The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) was the first imaging sensor to measure the solar reflected spectrum from 400 to 2500nm at 10 nm intervals.
A 12 station Lightning Mapping Array (LMA) network was deployed during October 2011 in the vicinity of Sao Paulo, Brazil (SP-LMA) to contribute total lightning measurements to an international field campaign [CHUVA - Cloud processes of tHe main precipitation systems in Brazil: A contribUtion to cloud resolVing modeling and to the GPM (GlobAl Precipitation Measurement)]. The SP-LMA was operational from November 2011 through March 2012 during the Vale do Paraiba campaign. Sensor spacing was on the order of 15-30 km, with a network diameter on the order of 40-50km. The SP-LMA provides good 3-D lightning mapping out to 150 km from the network center, with 2-D coverage considerably farther. In addition to supporting CHUVA science/mission objectives, the SP-LMA is supporting the generation of unique proxy data for the Geostationary Lightning Mapper (GLM) and Advanced Baseline Imager (ABI), on NOAA's Geostationary Operational Environmental Satellite-R (GOES-R: scheduled for a 2015 launch). These proxy data will be used to develop and validate operational algorithms so that they will be ready to use on "day1" following the GOES-R launch. As the CHUVA Vale do Paraiba campaign opportunity was formulated, a broad community-based interest developed for a comprehensive Lightning Location System (LLS) intercomparison and assessment study, leading to the participation and/or deployment of eight other ground-based networks and the space-based Lightning Imaging Sensor (LIS). The SP-LMA data is being intercompared with lightning observations from other deployed lightning networks to advance our understanding of the capabilities/contributions of each of these networks toward GLM proxy and validation activities. This paper addresses the network assessment including noise reduction criteria, detection efficiency estimates, and statistical and climatological (both temporal and spatially) analyses for intercomparison studies and GOES-R proxy activities.
Many regions of the world benefit from heating, ventilating, and air-conditioning (HVAC) systems to provide productive, comfortable, and healthy indoor environments, which are enabled by automatic building controls. Due to climate change, population growth, and industrialization, HVAC use is globally on the rise. Unfortunately, these systems often operate in a continuous fashion without regard to actual human presence, leading to unnecessary energy consumption. As a result, the heating, ventilation, and cooling of unoccupied building spaces makes a substantial contribution to the harmful environmental impacts associated with carbon-based electric power generation, which is important to remedy. For our modern electric power system, transitioning to low-carbon renewable energy is facilitated by integration with distributed energy resources. Automatic engagement between the grid and consumers will be necessary to enable a clean yet stable electric grid, when integrating these variable and uncertain renewable energy sources. We present the WHISPER (Wireless Home Identification and Sensing Platform for Energy Reduction) system to address the energy and power demand triggered by human presence in homes. The presented system includes a maintenance-free and privacy-preserving human occupancy detection system wherein a local wireless network of battery-free environmental, acoustic energy, and image sensors are deployed to monitor homes, record empirical data for a range of monitored modalities, and transmit it to a base station. Several machine learning algorithms are implemented at the base station to infer human presence based on the received data, harnessing a hierarchical sensor fusion algorithm. Results from the prototype system demonstrate an accuracy in human presence detection in excess of 95%; ongoing commercialization efforts suggest approximately 99% accuracy. Using machine learning, WHISPER enables various applications based on its binary occupancy prediction, allowing situation-specific controls targeted at both personalized smart home and electric grid modernization opportunities.
The dark current of a transferred-electron photocathode with an InGaAs absorber, responsive over the 0.9-to-1.7- micron range, must be reduced to an ultralow level suitable for low signal spectral astrophysical measurements by lowering the temperature of the sensor incorporating the cathode. However, photocathode quantum efficiency (QE) is known to reduce to zero at such low temperatures. Moreover, it has not been demonstrated that the target dark current can be reached at any temperature using existing photocathodes. Changes in the transferred-electron photocathode epistructure (with an In- GaAs absorber lattice-matched to InP and exhibiting responsivity over the 0.9- to-1.7- m range) and fabrication processes were developed and implemented that resulted in a demonstrated >13x reduction in dark current at -40 C while retaining >95% of the approximately equal to 25% saturated room-temperature QE. Further testing at lower temperature is needed to confirm a >25 C predicted reduction in cooling required to achieve an ultralow dark-current target suitable for faint spectral astronomical observations that are not otherwise possible. This reduction in dark current makes it possible to increase the integration time of the imaging sensor, thus enabling a much higher near-infrared (NIR) sensitivity than is possible with current technology. As a result, extremely faint phenomena and NIR signals emitted from distant celestial objects can be now observed and imaged (such as the dynamics of redshifting galaxies, and spectral measurements on extra-solar planets in search of water and bio-markers) that were not previously possible. In addition, the enhanced NIR sensitivity also directly benefits other NIR imaging applications, including drug and bomb detection, stand-off detection of improvised explosive devices (IED's), Raman spectroscopy and microscopy for life/physical science applications, and semiconductor product defect detection.
Integrated circuits that exploit optical flow to sense motions of computer mice on or near surfaces ( optical mouse chips ) are used as navigation sensors in a class of small flying robots now undergoing development for potential use in such applications as exploration, search, and surveillance. The basic principles of these robots were described briefly in Insect-Inspired Flight Control for Small Flying Robots (NPO-30545), NASA Tech Briefs, Vol. 29, No. 1 (January 2005), page 61. To recapitulate from the cited prior article: The concept of optical flow can be defined, loosely, as the use of texture in images as a source of motion cues. The flight-control and navigation systems of these robots are inspired largely by the designs and functions of the vision systems and brains of insects, which have been demonstrated to utilize optical flow (as detected by their eyes and brains) resulting from their own motions in the environment. Optical flow has been shown to be very effective as a means of avoiding obstacles and controlling speeds and altitudes in robotic navigation. Prior systems used in experiments on navigating by means of optical flow have involved the use of panoramic optics, high-resolution image sensors, and programmable imagedata- processing computers.
Rotorcraft operating in high-threat environments fly close to the earth's surface to utilize surrounding terrain, vegetation, or man-made objects to minimize the risk of being detected by an enemy. The piloting of the rotorcraft is at best a very demanding task and the pilots need help from on-board automation tools in order to devote more time to mission-related activities. The Automated Nap-of-the-Earth (NOE) Flight Program is a cooperative NASA/Army program aimed at the development of technologies for enhancing piloted low-altitude/NOE flight path management and control through computer and sensor aiding. The long-term objective is to work towards achieving automation for aiding the pilot in NOE flight with a flight demonstration of resulting computer/sensor aiding concepts at an established course. The technology for pilot-centered NOE automation is not currently available. Success in automating NOE functions will depend on major breakthroughs in real-time flight path planning algorithms, effective methods for the pilot to interface to the automatic modes, understanding of visual images, sensor data processing/fusion, and sensor development. Our approach to developing the technologies required to solve this problem consist of the following phases: (1) algorithm development, (2) laboratory evaluation, (3) piloted ground simulation, and (4) evaluation in flight. An overview of the research in this area at NASA Ames Research Center is given.
This article examines the thermal behavior of a laser ignited thermite composed of aluminum and bismuth trioxide. Temperature data were collected during the reaction using a four-color pyrometer and a high-speed color camera modified for thermography. The two diagnostics were arranged to collect data simultaneously, with similar fields of view and with similar data acquisition rates, so that the two techniques could be directly compared. Results show that at initial and final stages of the reaction, a lower signal-to-noise ratio affects the accuracy of the measured temperatures. Both diagnostics captured the same trends in transient thermal behavior, but the average temperatures measured with thermography were about 750 K higher than those from the pyrometer. This difference was attributed to the lower dynamic range of the thermography camera’s image sensor, which was unable to resolve cooler temperatures in the field of view as well as the photomultiplier tube sensors in the pyrometer. Overall, while the camera could not accurately capture the average temperature of a scene, its ability to capture peak temperatures and spatial data make it the preferred method for tracking thermal behavior in thermite reactions.
Accomplishing a task with telerobotics typically involves a combination of operator control/supervision and a 'script' of preprogrammed commands. These commands usually assume that the location of various objects in the task space conform to some internal representation (database) of that task space. The ability to quickly and accurately verify the task environment against the internal database would improve the robustness of these preprogrammed commands. In addition, the on-line initialization and maintenance of a task space database is difficult for operators using Cartesian coordinates alone. This paper describes the Interactive Scene' Analysis Module (ISAM) developed to provide taskspace database initialization and verification utilizing 3-D graphic overlay modelling, video imaging, and laser radar based range imaging. Through the fusion of taskspace database information and image sensor data, a verifiable taskspace model is generated providing location and orientation data for objects in a task space. This paper also describes applications of the ISAM in the Intelligent Systems Research Laboratory (ISRL) at NASA Langley Research Center, and discusses its performance relative to representation accuracy and operator interface efficiency.
Feature based registration is one of the most reliable methods to register multi-sensor images (both active and passive imagery) since features are often more reliable than intensity or radiometric values. The only situation where a feature based approach will fail is when the scene is completely homogenous or densely textural in which case a combination of feature and intensity based methods may yield better results. In this paper, we present some preliminary results of testing our scale space feature based registration technique, a modified version of feature based method developed earlier for classification of multi-sensor imagery. The proposed approach removes the sensitivity in parameter selection experienced in the earlier version as explained later.
Previous studies of tropical lightning activity using Tropical Rainfall Measurement Mission (TRMM) Lightning Imaging Sensor (LIS) data performed analyses of lightning behavior over mesoscale "feature" scales or over uniform grids. In order to study lightning and the governing ice microphysics intrinsic to thunderstorms at a more process-specific scale (i.e., the scale over which electrification processes and lightning occur in a "unit" thunderstorm), a new convective cell-scale database was developed by analyzing and refining the University of Utah's Precipitation Features database and retaining precipitation data parameters computed from the TRMM precipitation radar (PR), microwave imager (TMI) and LIS instruments. The resulting data base was to conduct a limited four-year study of tropical continental convection occurring over the Amazon Basin, Congo, Maritime Continent and the western Pacific Ocean. The analysis reveals expected strong correlations between lightning flash counts per cell and ice proxies, such as ice water path, minimum and average 85GHz brightness temperatures, and 18dBz echo top heights above the freezing level in all regimes, as well as regime-specific relationships between lighting flash counts and PR-derived surface rainfall rates. Additionally, radar CFADs were used to partition the 3D structure of cells in each regime at different flash counts. The resulting cell-scale analyses are compared to previous mesoscale feature and gridded studies wherever possible.
We report on the design, build and planned airborne demonstration of a spaceflight-prototype Concurrent Artificially-intelligent Spectrometry and Adaptive Lidar System (CASALS). The CASALS lidar is an Adaptive Wavelength Scanning Lidar (AWSL) operating in push broom mode. The demonstration has three major goals: advance the Technical Readiness Level of the AWSL hardware, validate its measurement performance and mature algorithms and methods needed for the Surface Topography and Vegetation (STV) observing system. AWSL acquires parallel tracks of surface heights by rapidly steering a laser beam across a swath. A 1040nm-centered laser is tuned across 30nm and carved into 2-ns pulses, the pulse energy is fiber amplified and the pulses are dispersed cross-track using a non-mechanical wavelength-to-angle grating. For the spaceflight system the beam will be pointable to 1200 10m footprints across a 7km swath. For the airborne demonstration there will be 256 0.7m footprints across a 110m swath. In both cases the footprints overlap across- and along-track for uniform target illumination. For the airborne demonstration a steering mirror will increase the accessible swath width to 4km. At the receiver, solar radiation is filtered with a narrow-slit grating-spectrometer and the footprints are imaged onto a linear-mode, photon-sensitive HgCdTe APD-array. The received pulses are time-division-multiplexed to a few high-speed analog-to-digital converters to record waveforms. Spaceflight and airborne CASALS are designed to nominally detect 20 photons per pulse and, by averaging 27 overlapping footprints, achieve 2cm flat target range precision and high-quality vegetation structure waveforms The AWSL will be flown in the summer of 2024, along with a Headwall VNIR-SWIR hyperspectral sensor imaging a 4km wide swath, at NEON eddy covariance flux towers in the U.S. mid-Atlantic where high resolution hyperspectral and lidar data, acquired annually, are available for validation.
Princeton Observatory has been working for several years under NASA sponsorship to develop television type sensors to use in place of photographic film for space astronomy. The performance of an SEC-vidicon with a 25 mm x 25 mm active area, MgF2 window, and bi-alkali photocathode is discussed. Results from ground based use on the Coude spectrograph of the 200-inch Hale telescope are included. The intended use of this tube in an echelle spectrograph sounding rocket payload and on Stratoscope 2 for direct high resolution imagery is also discussed. The paper also discusses the large space telescope image sensor requirements and the development of a larger television tube for this mission.
A four station Advanced Lightning Direction Finder (ALDF) network was established in the state of Rondonia in western Brazil in 1999 through a collaboration of U.S. and Brazilian participants from NASA, INPE, INMET, and various universities. The network utilizes ALDF IMPACT (Improved Accuracy from Combined Technology) sensors to provide cloud-to-ground lightning observations (i.e., stroke/flash locations, signal amplitude, and polarity) using both time-of- arrival and magnetic direction finding techniques. The observations are collected, processed and archived at a central site in Brasilia and at the NASA/Marshall Space Flight Center in Huntsville, Alabama. Initial, non-quality assured quick-look results are made available in near real-time over the Internet. The network, which is still operational, was deployed to provide ground truth data for the Lightning Imaging Sensor (LIS) on the Tropical Rainfall Measuring Mission (TRMM) satellite that was launched in November 1997. The measurements are also being used to investigate the relationship between the electrical, microphysical and kinematic properties of tropical convection. In addition, the long-time series observations produced by this network will help establish a regional lightning climatological database, supplementing other databases in Brazil that already exist or may soon be implemented. Analytic inversion algorithms developed at the NASA/Marshall Space Flight Center have been applied to the Rondonian ALDF lightning observations to obtain site error corrections and improved location retrievals. The data will also be corrected for the network detection efficiency. The processing methodology and the results from the analysis of four years of network operations will be presented.
Princeton Observatory has been working for several years under NASA sponsorship to develop television type sensors to use in place of photographic film for space astronomy. This paper discusses the performance of an SEC-vidicon with a 25 mm x 25 mm active area, MgF2 window, and bi-alkali photocathode. Results from ground based use on the Coude spectrograph of the 200-inch Hale telescope are included. The intended use of this tube in an echelle spectrograph sounding rocket payload and on Stratoscope II for direct high resolution imagery is also discussed. The paper also discusses the Large Space Telescope image sensor requirements and the development of a larger television tube for this mission.
Performance parameters of the 800 x 800 three phase and virtual phase CCD imaging sensors for the planned Project Galileo and Space Telescope Wide Field/Planetary Camera are compared, and the significance of some of the parameters for device radiation performance is discussed. The problems encountered by the three phase device that resulted in its being considered not suitable for the Galileo mission are described, and the radiation hardening performed on the virtual phase device to permit it to cope with Jupiter's radiation belts is addressed. Major research tasks in the effort to advance the technology of large area virtual phase imagers are stated.
A four station Advanced Lightning Direction Finder (ALDF) network was recently established in the state of Rondonia in western Brazil through a collaboration of U.S. and Brazilian participants from NASA, INPE, INMET, and various universities. The network utilizes ALDF IMPACT (Improved Accuracy from Combined Technology) sensors to provide cloud-to-ground lightning observations (i.e., stroke/flash locations, signal amplitude, and polarity) using both time-of-arrival and magnetic direction finding techniques. The observations are collected, processed and archived at a central site in Brasilia and at the NASA/Marshall Space Flight Center (MSFC) in Huntsville, Alabama. Initial, non-quality assured quick-look results are made available in near real-time over the internet. The network will remain deployed for several years to provide ground truth data for the Lightning Imaging Sensor (LIS) on the Tropical Rainfall Measurement Mission (TRMM) satellite which was launched in November 1997. The measurements will also be used to investigate the relationship between the electrical, microphysical and kinematic properties of tropical convection. In addition, the long-term observations from this network will contribute in establishing a regional lightning climatological data base, supplementing other data bases in Brazil that already exist or may soon be implemented. Analytic inversion algorithms developed at NASA/MSFC are now being applied to the Rondonian ALDF lightning observations to obtain site error corrections and improved location retrievals. The processing methodology and the initial results from an analysis of the first 6 months of network operations will be presented.
A four station Advanced Lightning Direction Finder (ALDF) network was recently established in the state of Rondonia in western Brazil through a collaboration of U.S. and Brazilian participants from NASA, INPE, INMET, and various universities. The network utilizes ALDF IMPACT (Improved Accuracy from Combined Technology) sensors to provide cloud-to-ground lightning observations (i.e., stroke/flash locations, signal amplitude, and polarity) using both time-of-arrival and magnetic direction finding techniques. The observations are collected, processed and archived at a central site in Brasilia and at the NASA/ Marshall Space Flight Center (MSFC) in Huntsville, Alabama. Initial, non-quality assured quick-look results are made available in near real-time over the internet. The network will remain deployed for several years to provide ground truth data for the Lightning Imaging Sensor (LIS) on the Tropical Rainfall Measuring Mission (TRMM) satellite which was launched in November 1997. The measurements will also be used to investigate the relationship between the electrical, microphysical and kinematic properties of tropical convection. In addition, the long-term observations from this network will contribute in establishing a regional lightning climatological data base, supplementing other data bases in Brazil that already exist or may soon be implemented. Analytic inversion algorithms developed at NASA/Marshall Space Flight Center (MSFC) are now being applied to the Rondonian ALDF lightning observations to obtain site error corrections and improved location retrievals. The processing methodology and the initial results from an analysis of the first 6 months of network operations will be presented.
This report summarizes an investigation of zoom lens calibration, with emphasis on the effects of lens-image-plane misalignment. Measurements have been made of the photogrammetric principal point and radial (symmetrical) and decentering (asymmetrical) distortion components as a function of the principal distance (zoom setting) of several zoom lenses. Data were also taken with the axis of symmetry (optical axis) of a zoom lens aligned and misaligned to the same solid-state video camera. An explanation is offered regarding the variation of the principal point as a function of zoom setting based on these measurements. In addition the relationship of the decentering distortion to radial distortion, principal distance, and lens-image-plane misalignment angle is discussed. A technique for determining the proper point of symmetry to be used for distortion computations (as opposed to the principal point) is also suggested. A simple technique for measuring the misalignment angle of zoom lenses when attached to video cameras is presented, along with measurements for seven solid-state cameras. A method to reduce the additional error introduced by zoom lens misalignment is presented. The implications of this study are that special measures to properly align a zoom lens to the sensor image plane are probably not necessary, but that as the accuracy obtainable in digital photogrammetry approaches the 0.01 or less pixel level, additional calibration including the point of symmetry for distortion computation should be considered.