Search NASA⌕ Search

SEARCH · Search NASA

Results for “Light Detection & Ranging (LIDAR)”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 199 records · Page 11

Scheimpflug LIDAR for Gas Sensing at Elevated Temperatures

Localized operating conditions inside boilers, heat recovery steam generators, or other large thermal systems have a huge impact on the efficiency, environmental performance, and lifetime of components. It is extremely difficult to measure species accurately within these systems due to the high temperatures and harsh environments, locally oxidizing or reducing atmospheres, ash, other particulates, and other damaging chemical species. Physical probes quickly suffer damage and are rendered nonfunctional. This work has attempted to adapt the measurement approach based on Scheimpflug light detection and ranging (S-LIDAR) for the remote sensing of gas species inside the high-temperature boiler environment. For a proof-of-concept, the detection of Raman signals of N 2 , O 2 , and CO 2 and their behavior with increasing temperature have been presented.

47 OTHER INSTRUMENTATION↗

Gravity Waves and Mesospheric Clouds in the Summer Middle Atmosphere: A Comparison of Lidar Measurements and Ray Modeling of Gravity Waves Over Sondrestrom, Greenland

We conducted gravity wave ray-tracing experiments within an atmospheric region centered near the ARCLITE lidar system at Sondrestrom, Greenland (67N, 310 deg E), in efforts to understand lidar observations of both upper stratospheric gravity wave activity and mesospheric clouds during August 1996 and the summer of 2001. The ray model was used to trace gravity waves through realistic three-dimensional daily-varying background atmospheres in the region, based on forecasts and analyses in the troposphere and stratosphere and climatologies higher up. Reverse ray tracing based on upper stratospheric lidar observations at Sondrestrom was also used to try to objectively identify wave source regions in the troposphere. A source spectrum specified by reverse ray tracing experiments in early August 1996 (when atmospheric flow patterns produced enhanced transmission of waves into the upper stratosphere) yielded model results throughout the remainder of August 1996 that agreed best with the lidar observations. The model also simulated increased vertical group propagation of waves between 40 km and 80 km due to intensifying mean easterlies, which allowed many of the gravity waves observed at 40 km over Sondrestrom to propagate quasi-vertically from 40-80 km and then interact with any mesospheric clouds at 80 km near Sondrestrom, supporting earlier experimentally-inferred correlations between upper stratospheric gravity wave activity and mesospheric cloud backscatter from Sondrestrom lidar observations. A pilot experiment of real-time runs with the model in 2001 using weather forecast data as a low-level background produced less agreement with lidar observations. We believe this is due to limitations in our specified tropospheric source spectrum, the use of climatological winds and temperatures in the upper stratosphere and mesosphere, and missing lidar data from important time periods.

LIDAR (LIGHT DETECTION AND RANGING)↗

TLSLEAF: Automatic Leaf Angle Estimates From Single-Scan Terrestrial Laser Scanning

Leaf angle distribution (LAD) in forest canopies affects estimates of leaf area, light interception, and global-scale photosynthesis, but is often simplified to a single theoretical value. Here, we present TLSLeAF (Terrestrial Laser Scanning Leaf Angle Function), an automated open-source method of deriving LADs from terrestrial laser scanning. TLSLeAF produces canopy-scale leaf angle and LADs by relying on gridded laser scanning data. The approach increases processing speed, improves angle estimates, and requires minimal user input. Key features are automation, leaf–wood classification, beta parameter output, and implementation in R to increase accessibility for the ecology community. TLSLeAF precisely estimates leaf angle with minimal distance effects on angular estimates while rapidly producing LADs on a consumer-grade machine. We challenge the popular spherical LAD assumption, showing sensitivity to ecosystem type in plant area index and foliage profile estimates that translate to c. 25% and c. 11% increases in canopy net photosynthesis (c. 25%) and solar-induced chlorophyll fluorescence (c. 11%). TLSLeAF can now be applied to the vast catalog of laser scanning data already available from ecosystems around the globe. The ease of use will enable widespread adoption of the method outside of remote-sensing experts, allowing greater accessibility for addressing ecological hypotheses and large-scale ecosystem modeling efforts.

3D↗

Study of atmospheric parameters measurements using MM-wave radar in synergy with LITE-2

The Lidar In-Space Technology Experiment, (LITE), has been developed, designed, and built by NASA Langley Research Center, to be flown on the space shuttle 'Discovery' on September 9, 1994. Lidar, which stands for light detecting and ranging, is a radar system that uses short pulses of laser light instead of radio waves in the case of the common radar. This space-based lidar offers atmospheric measurements of stratospheric and tropospheric aerosols, the planetary boundary layer, cloud top heights, and atmospheric temperature and density in the 10-40 km altitude range. A study is being done on the use, advantages, and limitations of a millimeterwave radar to be utilized in synergy with the Lidar system, for the LITE-2 experiment to be flown on a future space shuttle mission. The lower atmospheric attenuation, compared to infrared and optical frequencies, permits the millimeter-wave signals to penetrate through the clouds and measure multi-layered clouds, cloud thickness, and cloud-base height. These measurements would provide a useful input to radiation computations used in the operational numerical weather prediction models, and for forecasting. High power levels, optimum modulation, data processing, and high antenna gain are used to increase the operating range, while space environment, radar tradeoffs, and power availability are considered. Preliminary, numerical calculations are made, using the specifications of an experimental system constructed at Georgia Tech. The noncoherent 94 GHz millimeter-wave radar system has a pulsed output with peak value of 1 kW. The backscatter cross section of the particles to be measured, that are present in the volume covered by the beam footprint, is also studied.

Andrawis, Madeleine Y.↗

Lidar instruments proposed for Eos

Lidar, an acronym for light detection and ranging, represents a class of instruments that utilize lasers to send probe beams into the atmosphere or onto the surface of the Earth and detect the backscattered return in order to measure properties of the atmosphere or surface. The associated technology has matured to the point where two lidar facilities, Geodynamics Laser Ranging System (GLRS), and Laser Atmospheric Wind Sensor (LAWS) were accepted for Phase 2 studies for Eos. A third lidar facility Laser Atmospheric Sounder and Altimeter (LASA), with the lidar experiment EAGLE (Eos Atmospheric Global Lidar Experiment) was proposed for Eos. The generic lidar system has a number of components. They include controlling electronics, laser transmitters, collimating optics, a receiving telescope, spectral filters, detectors, signal chain electronics, and a data system. Lidar systems that measure atmospheric constituents or meteorological parameters record the signal versus time as the beam propagates through the atmosphere. The backscatter arises from molecular (Rayleigh) and aerosol (Mie) scattering, while attenuation arises from molecular and aerosol scattering and absorption. Lidar systems that measure distance to the Earth's surface or retroreflectors in a ranging mode record signals with high temporal resolution over a short time period. The overall characteristics and measurements objectives of the three lidar systems proposed for Eos are given.

Grant, William B.↗

A Tool for the Automated Collection of Space Utilization Data: Three Dimensional Space Utilization Monitor

Space Human Factors and Habitability (SHFH) Element within the Human Research Program (HRP), in collaboration with the Behavioral Health and Performance (BHP) Element, is conducting research regarding Net Habitable Volume (NHV), the internal volume within a spacecraft or habitat that is available to crew for required activities, as well as layout and accommodations within that volume. NASA is looking for innovative methods to unobtrusively collect NHV data without impacting crew time. Data required includes metrics such as location and orientation of crew, volume used to complete tasks, internal translation paths, flow of work, and task completion times. In less constrained environments methods for collecting such data exist yet many are obtrusive and require significant post‐processing. Example technologies used in terrestrial settings include infrared (IR) retro‐reflective marker based motion capture, GPS sensor tracking, inertial tracking, and multiple camera filmography. However due to constraints of space operations many such methods are infeasible, such as inertial tracking systems which typically rely upon a gravity vector to normalize sensor readings, and traditional IR systems which are large and require extensive calibration. However multiple technologies have not yet been applied to space operations for these explicit purposes. Two of these include 3‐Dimensional Radio Frequency Identification Real‐Time Localization Systems (3D RFID‐RTLS) and depth imaging systems which allow for 3D motion capture and volumetric scanning (such as those using IR‐depth cameras like the Microsoft Kinect or Light Detection and Ranging / Light‐Radar systems, referred to as LIDAR).

Vos, Gordon A.↗

A Tool for the Automated Collection of Space Utilization Data: Three Dimensional Space Utilization Monitor

Space Human Factors and Habitability (SHFH) Element within the Human Research Program (HRP) and the Behavioral Health and Performance (BHP) Element are conducting research regarding Net Habitable Volume (NHV), the internal volume within a spacecraft or habitat that is available to crew for required activities, as well as layout and accommodations within the volume. NASA needs methods to unobtrusively collect NHV data without impacting crew time. Data required includes metrics such as location and orientation of crew, volume used to complete tasks, internal translation paths, flow of work, and task completion times. In less constrained environments methods exist yet many are obtrusive and require significant post-processing. Examplesused in terrestrial settings include infrared (IR) retro-reflective marker based motion capture, GPS sensor tracking, inertial tracking, and multi-camera methods Due to constraints of space operations many such methods are infeasible. Inertial tracking systems typically rely upon a gravity vector to normalize sensor readings,and traditional IR systems are large and require extensive calibration. However, multiple technologies have not been applied to space operations for these purposes. Two of these include: 3D Radio Frequency Identification Real-Time Localization Systems (3D RFID-RTLS) Depth imaging systems which allow for 3D motion capture and volumetric scanning (such as those using IR-depth cameras like the Microsoft Kinect or Light Detection and Ranging / Light-Radar systems, referred to as LIDAR)

Vos, Gordon A.↗

Remote Detection of Biological Particles and Chemical Plumes Using UV Fluorescence Lidar

A lidar system based on ultraviolet (UV) laser induced fluorescence (LIF) was developed for the remote detection of atmospherically dispersed biological particles and chemical vapors. This UV fluorescence lidar has many potential applications for monitoring environmental pollution, industrial waste emission, agricultural insect control, illicit chemical processing, and military defense operations. The general goal of this work is to investigate the research issues associated with the long range detection and identification of chemicals, e.g. aromatic solvents and chemical precursors, and biological materials, e.g. bacillus thuringiensis (BT) and bacillus globiggi (BG). In the detection of biological particulates, we are particularly interested in extending the detection range of an existing solar-blind 248-nm lidar system. We are investigating the use of longer excitation laser wavelengths (i.e. lambda greater than 280-nm to have more favorable atmospheric light transmission characteristics) for improving detection range to better than 10 km. In the detection of chemical plumes, our main research objectives are to determine how accurately and sensitively a chemical plume can be located at range, and how well spectrally the chemical species can be measured to allow their identification.

J J Tiee↗

Enclosure for light detection and ranging unit and related methods

This disclosure provides systems, methods, and apparatus related to light detection and ranging. In one aspect, a method comprises providing an apparatus. The apparatus comprises a LiDAR unit and a LiDAR enclosure. The LiDAR enclosure comprises a four-sided container having a square or rectangular cross-section with a first open end and a second open end comprising two opposite ends of the four-sided container. The LiDAR unit is attached to a mounting area inside the four-sided container. A reflective material is disposed on an interior of a second side and a third side of the four-sided container. Laser light is generated with the LiDAR unit. The laser light that has interacted with environment surrounding the LiDAR enclosure and that has been reflected back to the LiDAR unit is detected. The detected laser light is processed to construct an image of the environment surrounding the LiDAR enclosure.

Bandstra, Mark S.↗

Development of a Photon Counting System for Differential Lidar Signal Detection

Photon counting has been chosen as a means to extend the detection range of current airborne DIAL ozone measurements. Lidar backscattered return signals from the on and off-line lasers experience a significant exponential decay. To extract further data from the decaying ozone return signals, photon counting will be used to measure the low light levels, thus extending the detection range. In this application, photon counting will extend signal measurement where the analog return signal is too weak. The current analog measurement range is limited to approximately 25 kilometers from an aircraft flying at 12 kilometers. Photon counting will be able to exceed the current measurement range so as to follow the mid-latitude model of ozone density as a function of height. This report describes the development of a photon counting system. The initial development phase begins with detailed evaluation of individual photomultiplier tubes. The PMT qualities investigated are noise count rates, single electron response peaks, voltage versus gain values, saturation effects, and output signal linearity. These evaluations are followed by analysis of two distinctive tube base gating schemes. The next phase is to construct and operate a photon counting system in a laboratory environment. The laboratory counting simulations are used to determine optimum discriminator setpoints and to continue further evaluations of PMT properties. The final step in the photon counting system evaluation process is the compiling of photon counting measurements on the existing ozone DIAL laser system.

Elsayed-Ali, Hani↗

Htrl Apr 2023 Presentation

This project will produce a 3D lidar system (engineering unit) to greatly expand rover navigation capability, including hazard detection range, field of view and light condition sensitivity. Provide required science data products and terrain mapping capabilities.

Nathaniel Gill↗

Evaluating the WFIP2 updates to the HRRR model using scanning Doppler lidar measurements in the complex terrain of the Columbia River Basin

The wind-energy (WE) industry relies on numerical weather prediction (NWP) forecast models as foundational or base models for many purposes, including wind-resource assessment and wind-power forecasting. During the Second Wind Forecast Improvement Project (WFIP2) in the Columbia River Basin of Oregon and Washington, a significant effort was made to improve NWP forecasts through focused model development, to include experimental refinements to the High Resolution Rapid Refresh (HRRR) model physics and horizontal grid spacing. In this study, the performance of an experimental version of HRRR that includes these refinements is tested against a control version, which corresponds to that of the operational HRRR run by National Oceanic and Atmospheric Administration/National Centers for Environmental Protection at the outset of WFIP2. Furthermore, the effects of horizontal grid resolution were also tested by comparing wind forecasts from the HRRR (with 3-km grid spacing) with those from a finer-resolution HRRR nest with 750-m grid spacing. Model forecasts are validated against accurate wind-profile measurements by three scanning, pulsed Doppler lidars at sites separated by a total distance of 71 km. Model skill and improvements in model skill, attributable to physics refinements and improved horizontal grid resolution, varied by season, by site, and during periods of atmospheric phenomena relevant to WE. In general, model errors were the largest below 150 m above ground level (AGL). Experimental HRRR refinements tended to reduce the mean absolute error (MAE) and other error metrics for many conditions, but degradation in skill (increased MAE) was noted below 150 m AGL at the two lowest-elevation sites at night. Finer resolution was found to produce the most significant reductions in the error metrics.

17 WIND ENERGY↗

GN and C Subsystem Concept for Safe Precision Landing of the Proposed Lunar MARE Robotic Science Mission

The Lunar MARE (Moon Age and Regolith Explorer) Discovery Mission concept targets delivery of a science payload to the lunar surface for sample collection and dating. The mission science is within a 100-meter radius region of smooth lunar maria terrain near Aristarchus crater. The location has several small, sharp craters and rocks that present landing hazards to the spacecraft. For successful delivery of the science payload to the surface, the vehicle Guidance, Navigation and Control (GN&C) subsystem requires safe and precise landing capability, so design infuses the NASA Autonomous precision Landing and Hazard Avoidance Technology (ALHAT) and a gimbaled, throttleable LOX/LCH4 main engine. The ALHAT system implemented for Lunar MARE is a specialization of prototype technologies in work within NASA for the past two decades, including a passive optical Terrain Relative Navigation (TRN) sensor, a Navigation Doppler Lidar (NDL) velocity and range sensor, and a Lidar-based Hazard Detection (HD) sensor. The landing descent profile is from a retrograde orbit over lighted terrain with landing near lunar dawn. The GN&C subsystem with ALHAT capabilities will deliver the science payload to the lunar surface within a 20-meter landing ellipse of the target location and at a site having greater than 99% safety probability, which minimizes risk to safe landing and delivery of the MARE science payload to the intended terrain region.

MARE (Moon Age and Regolith Explorer)↗

Preparation and Integration of ALHAT Precision Landing Technology for Morpheus Flight Testing

The Autonomous precision Landing and Hazard Avoidance Technology (ALHAT) project has developed a suite of prototype sensors for enabling autonomous and safe precision land- ing of robotic or crewed vehicles on solid solar bodies under varying terrain lighting condi- tions. The sensors include a Lidar-based Hazard Detection System (HDS), a multipurpose Navigation Doppler Lidar (NDL), and a long-range Laser Altimeter (LAlt). Preparation for terrestrial ight testing of ALHAT onboard the Morpheus free- ying, rocket-propelled ight test vehicle has been in progress since 2012, with ight tests over a lunar-like ter- rain eld occurring in Spring 2014. Signi cant work e orts within both the ALHAT and Morpheus projects has been required in the preparation of the sensors, vehicle, and test facilities for interfacing, integrating and verifying overall system performance to ensure readiness for ight testing. The ALHAT sensors have undergone numerous stand-alone sensor tests, simulations, and calibrations, along with integrated-system tests in special- ized gantries, trucks, helicopters and xed-wing aircraft. A lunar-like terrain environment was constructed for ALHAT system testing during Morpheus ights, and vibration and thermal testing of the ALHAT sensors was performed based on Morpheus ights prior to ALHAT integration. High- delity simulations were implemented to gain insight into integrated ALHAT sensors and Morpheus GN&C system performance, and command and telemetry interfacing and functional testing was conducted once the ALHAT sensors and electronics were integrated onto Morpheus. This paper captures some of the details and lessons learned in the planning, preparation and integration of the individual ALHAT sen- sors, the vehicle, and the test environment that led up to the joint ight tests.

Carson, John M., III↗

An Automatic Light Rain Detection Algorithm on NASA MPLNET Lidar Observations in the Frame of WMO GALION Project

The water cycle strongly influences life on Earth. In particular, the precipitation modifies the atmospheric column thermodynamics through the process of evaporation and serves as a proxy for latent heat modulation. For this reason, a correct precipitation parameterization (especially low-intensity precipitation) at global scale, bedsides improving our understanding of the hydrological cycle, it is crucial to reduce the associated uncertainty of the global climate models to correctly forecast future scenarios, i.e. to apply fast mitigation strategies. In this study we developed an algorithm to automatically detect precipitation from lidar measurements obtained by the National and Aeronautics Space Administration (NASA) Micropulse lidar network (MPLNET) permanent observational site in Goddard. The algorithm, once full operational, will deliver in Near Real Time (latency 1.5h) a new rain mask product that will be publicly available on MPLNET website as part of the new Version 3 Level 1.5 data. The methodology, based on an image processing technique, can detect only light precipitation events (defined by intensity and duration) as the morphological filters used through the detection process are applied on the lidar volume depolarization ratio range corrected composite images, i.e. heavy rain events are unusable as the lidar signal is completely extinguished after few meters in the precipitation or no signal detected because of the water accumulated on the receiver optics. Results from the algorithm, besides filling a gap in precipitation and virga detection by radars, are of particular interest for the scientific community because will help to better understand long-term aerosol-cloud interactions and aerosol atmospheric removal (scavenging effect) by rain as multi-year database being available for several MPLNET permanent observational sites across the globe. Moreover, we developed the automatic algorithm at Universitat Politecnica de Catalunya (UPC) Barcelona, the unique permanent observation station member of MPLNET and the European Aerosol Lidar Network (EARLINET) In the future the algorithm can be then easily applied to any other lidar and/or ceilometer network infrastructure in the frame of World Meteorological Organization (WMO) Global Aerosol Watch (GAW) aerosol lidar observation network (GALION)

Simone Lolli↗

Features and Characteristics of the New NASA MicroPuLse NETwork (MPLNET) Automatic Rain Detection Algorithm

The water cycle strongly influences life on Earth. In particular, the precipitation modifies the atmospheric column thermodynamics through the process of evaporation and serves as a proxy for latent heat modulation. For this reason, a correct precipitation parameterization (especially low-intensity precipitation) at global scale, bedsides improving our understanding of the hydrological cycle, it is crucial to reduce the associated uncertainty of the global climate models to correctly forecast future scenarios, i.e. to apply fast mitigation strategies. In this study we developed an algorithm to automatically detect precipitation from lidar measurements obtained by the National and Aeronautics Space Administration (NASA) Micropulse lidar network (MPLNET) permanent observational site in Goddard. The algorithm, once full operational, will deliver in Near Real Time (latency 1.5h) a new rain mask product that will be publicly available on MPLNET website as part of the new Version 3 Level 1.5 data. The methodology, based on an image processing technique, can detect only light precipitation events (defined by intensity and duration) as the morphological filters used through the detection process are applied on the lidar volume depolarization ratio range corrected composite images, i.e. heavy rain events are unusable as the lidar signal is completely extinguished after few meters in the precipitation or no signal detected because of the water accumulated on the receiver optics.

S. Lolli↗

Coherent Doppler Wind Lidar Technology for Space Based Wind Measurements Including SPARCLE

It has been over 30 years since coherent lidar systems first measured wind velocity, and over 20 years since the "ultimate application" of measuring Earth's winds from space was conceived. Coherent or heterodyne optical detection involves the combination (or mixing) of the returned optical field with a local oscillator (LO) laser's optical field on the optical detector. This detection technique yields the benefits of dramatically improved signal-to-noise ratios; insensitivity to detector noise, background light and multiply scattered light; reduction of the returned signal's dynamic range; and preservation of the optical signal spectrum for electronic and computer processing. (Note that lidar systems are also referred to as optical radar, laser radar, and LADAR systems.) Many individuals, agencies, and countries have pursued the goal of space-based wind measurements through technology development, experiments, field campaigns and studies.

Kavaya, Michael J.↗

Pulse spreading and range correction analysis for satellite laser ranging

The pulse spreading resulting from light detection and ranging measurements of the range to earth-orbiting satellites is described. An analysis quantifying this pulse spreading and the calculation of corrections to be applied to the lidar range determination of satellites is detailed.

Schwartz, Jon A.↗