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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.

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At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

The Sensor Dilemma in Intelligent Transportation Systems: Evaluating Radar, Lidar and Camera: Preprint

Intelligent transportation systems (ITS) are at the forefront in advancing the way we interact with and perceive the transportation network. This revolution is fueled by the significant advancement in sensor perception technologies such as radar, lidar, and video imaging, which are the most popular modalities for ITS. Real-time perception data from these sensors allow intelligent infrastructure-side decision-making to improve the energy, efficiency, and safety at traffic intersections. As traffic departments across the United States transition from traditional loop detectors and emulators and embrace newer technologies, they are often left with a dilemma in choosing a sensor technology for infrastructure-based perception that is reliable, inexpensive, and easy to set up and that has robust performance in varying weather conditions. However, choosing a sensor that checks all these boxes is not straightforward, as every sensor type has unique benefits and drawbacks. Radar is excellent at detecting long-range vehicles and weather resistance but lacks high resolution. Lidar is expensive and weather-sensitive, while cameras provide rich visual data at a low cost but are constrained by lighting and visibility. This study examines radar, lidar, and camera sensor capabilities to ascertain whether any of these qualifies as the "best" sensor for ITS perception. While no single sensor can meet all the demands of ITS, a hybrid approach combining multiple sensor modalities like radar, lidar, and cameras offers the most robust solution for enhancing the safety and efficiency of ITS. Through this evaluation, we hope to draw attention to the necessity of the National Renewable Energy Laboratory's infrastructure perception and control framework, which presents a multisensor track data fusion engine to assimilate multiple data streams in order to provide robust and reliable perception.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRSDate not supplied

The Benefit of NASA's Atmosphere Observing System (AOS) Mission Lidar and Polarimeter Observations for Health and Air Quality Applications

The Atmosphere Observing System (AOS) seeks to explore fundamental questions of how interconnections between aerosols, clouds and precipitation impact our weather and climate, addressing real-world challenges to benefit society. AOS will provide key information to enhance the communities’ ability to improve weather and air quality forecasting today, seasonal to sub-seasonal changes in the near future, and societal challenges resulting from climate change in the decades to come. A fundamental component of the AOS mission is ensuring that health and air quality applications are considered to the greatest extent possible in mission design. As a result, the Applications Impact Team (AIT) was implemented to address this objective. The overarching goal of the AIT is to help improve the capacity for transitioning science to applications to make it possible to more quickly and effectively inform decisions that will directly benefit society. We seek to maximize AOS benefit to impact decisions through early engagement in the mission development phase in order to prepare stakeholders to apply observations as soon as AOS mission data becomes available. To support these efforts, we leverage existing and near future mission applications activities and initiatives, such as the NASA CALIPSO, MAIA, TEMPO, and PACE missions to form a framework to enhance health and air quality applications for AOS. The unique synergy between lidar and polarimeter instruments onboard the AOS constellation, as well as diurnally varying observations of aerosol profiles, will provide new opportunities to engage health and air quality stakeholders for forecasting, monitoring, and warning of hazardous events (e.g., wildfire smoke, volcanic ash) that impact human health. Engaging with existing missions helps identify and understand data needs, gaps and opportunities for current and future stakeholders, determine what aerosol data products are of highest value and use, and helps connect stakeholders with current mission data that can serve as AOS proxy data, among others. In this presentation, we provide an overview of AOS aerosol observations relevant for health and air quality applications, AIT activities and initiatives and how existing aerosol satellite missions and their applications activities can play a critical role in AOS applications development during mission design.

Melanie Follette-Cook↗
DOE OSTI2020

November 2019 Initial Deployment of LiDAR in the H-Canyon Exhaust Tunnel

The H-Canyon Exhaust Tunnel (CAEX) structure is periodically inspected under the Structural Integrity Program using camera equipped crawlers or poles to remotely perform visual inspections. To explore the use of enhanced inspection methods a “Proof of Concept” using the Light Detection and Ranging (LiDAR) technology was performed over a 2-day period in November 2019. The purpose of the “Proof of Concept” deployment was to confirm whether a commercially available LiDAR unit could successfully operate and remotely transmit data from the tunnel CAEX environment and whether the data would provide quantitative information to establish baseline measurements. The LiDAR performance requirement was a measurement accuracy of ± 0.25-inches over a 30-foot distance. This report documents the work activities leading to the deployment, the deployment and processing of data, lessons learned from the deployment and the post data processing methods that will be applied to future deployments.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS1986

Lidar observations of the decline of the El Chichon stratospheric load

The eruption of the Mexican volcano El Chichon in Apr. 1982 enhanced the stratospheric aerosol load to a level which so far has not been observed by remote sensing techniques. The ruby lidar system at Garmisch-Partenkirchen recorded an increase of about two orders of magnitude above the background level of the years 1977/78. At northern midlatitudes backscattering was peaking in Jan./Feb. 1983, as illustrated. The decline of the El Chichon stratospheric perturbation is discussed. The decay of the El Chichon stratospheric cloud is characterized by an overall 1/e lifetime of about 12 months. The El Chichon decay is further characterized by seasonal variations of the integral backscattering coefficient, which exhibit a winter maximum and a summer minimum. These variations are inversely correlated with the seasonal mean movement of the tropopause height indicating transport processes.

Jaeger, H.↗
DOE OSTI2020

Mapping Vegetation at Species Level with High-Resolution Multispectral and Lidar Data Over a Large Spatial Area: A Case Study with Kudzu

Mapping vegetation species is critical to facilitate related quantitative assessment, and mapping invasive plants is important to enhance monitoring and management activities. Integrating high-resolution multispectral remote-sensing (RS) images and lidar (light detection and ranging) point clouds can provide robust features for vegetation mapping. However, using multiple sources of high-resolution RS data for vegetation mapping on a large spatial scale can be both computationally and sampling intensive. Here, we designed a two-step classification workflow to potentially decrease computational cost and sampling effort and to increase classification accuracy by integrating multispectral and lidar data in order to derive spectral, textural, and structural features for mapping target vegetation species. We used this workflow to classify kudzu, an aggressive invasive vine, in the entire Knox County (1362 km2) of Tennessee (U.S.). Object-based image analysis was conducted in the workflow. The first-step classification used 320 kudzu samples and extensive, coarsely labeled samples (based on national land cover) to generate an overprediction map of kudzu using random forest (RF). For the second step, 350 samples were randomly extracted from the overpredicted kudzu and labeled manually for the final prediction using RF and support vector machine (SVM). Computationally intensive features were only used for the second-step classification. SVM had constantly better accuracy than RF, and the producer’s accuracy, user’s accuracy, and Kappa for the SVM model on kudzu were 0.94, 0.96, and 0.90, respectively. SVM predicted 1010 kudzu patches covering 1.29 km2 in Knox County. We found the sample size of kudzu used for algorithm training impacted the accuracy and number of kudzu predicted. The proposed workflow could also improve sampling efficiency and specificity. Our workflow had much higher accuracy than the traditional method conducted in this research, and could be easily implemented to map kudzu in other regions as well as map other vegetation species.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1989

Coherent Doppler lidar for measurements of wind fields

The signal-processing techniques for obtaining the velocity estimates and the fundamental factors that influence coherent lidar performance are considered. The similarities and distinctions between Doppler lidar and Doppler radars are discussed. The capability of coherent Doppler lidars for mapping wind fields over selected regions in the lower atmosphere and greatly enhancing the capability to visualize flow patterns in real time is discussed, and examples are given. Salient features of a concept for an earth-orbiting Doppler lidar to be launched in the late 1990s are examined.

Menzies, Robert T.↗
NASA NTRS2016

Aerosol Meteorology of the Maritime Continent for the 2012 7SEAS Southwest Monsoon Intensive Study - Part 1: Regional-scale Phenomena

The largest 7 Southeast Asian Studies (7SEAS) operation period within the Maritime Continent (MC) occurred in the August-September 2012 biomass burning season. Included was an enhanced deployment of Aerosol Robotic Network (AERONET) sun photometers, multiple lidars, and field measurements to observe transported smoke and pollution as it left the MC and entered the southwest monsoon trough. Here we describe the nature of the overall 2012 southwest monsoon (SWM) and biomass burning season to give context to the 2012 deployment. The MC in 2012 was in a slightly warm El Nino Southern Oscillation (ENSO) phase and with spatially typical burning activity. However, overall fire counts for 2012 were 10 lower than the Reid et al. (2012) baseline, with regions of significant departures from this norm, ranging from southern Sumatra (+30) to southern Kalimantan (42). Fire activity and monsoonal flows for the dominant burning regions were modulated by a series of intraseasonal oscillation events (e.g., Madden-Julian Oscillation, or MJO, and boreal summer intraseasonal oscillation, or BSISO). As is typical, fire activity systematically progressed eastward over time, starting with central Sumatran fire activity in June related to a moderately strong MJO event which brought drier air from the Indian Ocean aloft and enhanced monsoonal flow. Further burning in Sumatra and Kalimantan Borneo occurred in a series of significant events from early August to a peak in the first week of October, ending when the monsoon started to migrate back to its wintertime northeastern flow conditions in mid-October. Significant monsoonal enhancements and flow reversals collinear with tropical cyclone (TC) activity and easterly waves were also observed. Islands of the eastern MC, including Sulawesi, Java, and Timor, showed less sensitivity to monsoonal variation, with slowly increasing fire activity that also peaked in early October but lingered into November. Interestingly, even though fire counts were middling, resultant AERONET 500nm aerosol optical thickness (AOT) from fire activity was high, with maximums of 3.6 and 5.6 in the Sumatra and Kalimantan source regions at the end of the burning season and an average of approximately 1. AOTs could also be high at receptor sites, with a mean and maximum of 0.57 and 1.24 in Singapore and 0.61 and 0.8 in Kuching Sarawak. Ultimately, outside of the extreme 2015 El Nino event, average AERONET AOT values were higher than any other time since sites were established. Thus, while satellite fire data, models, and AERONET all qualitatively agree on the nature of smoke production and transport, the MC's complex environment resulted in clear differences in quantitative interpretation of these datasets.

Reid, Jeffrey S.↗
NASA NTRS1985

UV lidar measurements of the stratospheric aerosol layer and comparison with other optical data

After the violent volcanic eruptions of El Chichon in Mexico (17.33 deg. N, 93.20 deg. W) in late March and early April 1982, enhanced stratospheric aerosols have been monitored by ruby (lasing wavelength lambda=694.3 nm) or Nd:YAG lidars (lambda=1064 or 532 nm). By these lidars, visible or near-infrared optical informations of stratospheric aerosols and their space-time variations can be obtained. It is usually difficult to measure the background level of stratospheric aerosols by an ultraviolet (UV) lidar, since Rayleigh scattering prevails over Mie scattering in the stratosphere. However, after the large volcanic eruptions, UV lidar measurements of stratospheric aerosols are possible. In order to obtain UV optical properties of stratospheric aerosols, measurements have been made at Fukuoka (33.65 deg. N, 130.35 deg. E) by a p-terphenyl dye laser at a wavelength of 340.5 nm. Observational results during October 1982, through May 1983, are shown and are compared with the results obtained by a ruby lidar at Tsukuba (36.05 deg. N, 140.13 deg. E).

Uchino, O.↗
NASA NTRS2014

2-Micron Coherent Doppler Lidar Instrument Advancements for Tropospheric Wind Measurement

Knowledge derived from global tropospheric wind measurement is an important constituent of our overall understanding of climate behavior [1]. Accurate weather prediction saves lives and protects properties from destructions. High-energy 2-micron laser is the transmitter of choice for coherent Doppler wind detection. In addition to the eye-safety, the wavelength of the transmitter suitably matches the aerosol size in the lower troposphere. Although the technology of the 2-micron laser has been maturing steadily, lidar derived wind data is still a void in the global weather database. In the last decade, researchers at NASA Langley Research Center (LaRC) have been engaged in this endeavor, contributing to the scientific database of 2-micron lidar transmitters. As part of this effort, an in depth analysis of the physics involved in the workings of the Ho: Tm laser systems have been published. In the last few years, we have demonstrated lidar transmitter with over1Joule output energy. In addition, a large body of work has been done in characterizing new laser materials and unique crystal configurations to enhance the efficiency and output energy of the 2-micron laser systems. At present 2-micron lidar systems are measuring wind from both ground and airborne platforms. This paper will provide an overview of the advancements made in recent years and the technology maturity levels attained.

Petros, Mulugeta↗
NASA NTRS1985

Numerical simulation of El Chichon volcanic cloud

The stratospheric volcanic cloud from the eruption of El Chichon, Mexico, on April 4, 1982 was observed routinely by a Nd:YAG lidar system from April 18, 1982 at Kyushu University. There were two phenomena detected by lidar observation of the El Chichon volcanic cloud: (1) The main enhanced layer was formed in the summer easterly wind region over Fukuoka (33.5 deg N, 130.4 deg E). The layer had two high gradient top and bottom boundaries. The layer width slowly broadened until September 1982, when the easterly wind changed to the westerly wind. A similar phenomenon was observed after the eruption of Mt. St. Helens in May 1980. (2) The stratospheric integrated backscattering coefficient (IBC) reached a peak value on May 3, 1982. It then gradually decreased until August, but reincreased significantly from September to December 1982. After January 1983, IBC decreased slowly. This remarkable reincrease had not been seen in past increases which had been observed by lidar at Kyushu University. These phenomena are briefly discussed.

Shibata, T.↗
NASA NTRSDate not supplied

Application of Lidar-Radar Combined Data Products during the IMPACTS 2020 Field Campaign

The Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) is a three-year field campaign investigating the formation and lifecycle of banded, precipitation structures within intense wintertime cyclones impacting the highly-populated northeast United States. Unlike previous campaigns in the region, IMPACTS mission scientists have access to and coordinate the NASA ER-2 and P-3 aircraft to collect observations from both a remote sensing and in-situ perspective, respectively. For IMPACTS, the ER-2 aircraft was equipped with lidar (CPL), radar (CRS, HIWRAP, EXRAD), microwave radiometer (CoSMIR, AMPR) instruments, each with their own unique capabilities and limitations. Our on-going work effort aims to develop IMPACTS lidar and radar merged data products, which can be used to supplement the raw data sources, tease out additional aspects of the mechanisms underpinning wintertime cyclones, and enhance our understanding of microphysical properties in sensor overlap regions. Preliminary merged data products combine CPL lidar with any one of the NASA High Altitude Radar (HAR) radar products (CRS, HIWRAP, EXRAD) and represent these data as both normalized values and translated to reflectivity signal (dB). Continuing work will further refine our merged data product algorithm to provide additional information on hydrometeor species identification, ice crystal habit, and ice-water content, which will help IMPACTS achieve its mission goal of improving microphysical properties retrievals from both airborne and spaceborne platforms.

Stephen D. Nicholls↗
NASA NTRS2017

Large-scale product of forest height using a new approach from spaceborne repeat-pass SAR interferometry and LIDAR

Spaceborne SAR interferometry (InSAR) has the potential of mapping the forest height on a global scale and a monthly/weekly basis under all weather conditions, which can improve our understanding of the global carbon dynamics. In previous work, repeatpass SAR interferometry from spaceborne sensors is utilized to create large-scale forest height maps (that are particularly interested for large-scale ecological research) based on a newly developed approach. This paper thus serves as a summary paper and also sheds light on the future directions with improved results. In particular, it will be shown that repeat-pass SAR interferometry is able to create a large-scale forest height mosaic product with RMSE 4 m for forest stands on the order of 20 hectares through using the past spaceborne repeat-pass InSAR observations (i.e. JAXA’s ALOS-1 and ALOS-2) combined with sparse airborne lidar training samples over the forested areas in New England, US. Moreover, the results and performance of this approach can be remarkably improved with several enhancement techniques that can be easily satisfied with use of future spaceborne repeat-pass InSAR and lidar missions (e.g. NASA-ISRO’s NISAR and NASA’s GEDI). The methodology described in this paper can be considered as a complimentary tool to the existing PolInSAR technique and also serves as an observing prototype for the future spaceborne missions of repeatpass InSAR in fusion with lidar (e.g. NISAR and GEDI).

Treuhaft, Robert↗
NASA NTRSDate not supplied

The Kinematic Navigation and Cartography Knapsack (KNaCK) LiDAR System: Overview and Applications.

Improved terrain characterization and navigation sensors and methods are needed to enhance crew safety, ISRU return, and scientific understanding of future landing sites. Specific to the Artemis Program and sustained exploration at the lunar South Pole, extreme low-angle solar illumination conditions pose significant challenges to existing photogrammetry-based robotic navigation. Additionally, a major challenge for navigation on the Moon and other planetary surfaces is the lack of Global Positioning and Navigation Systems (GPS or GNSS). Thus, there is a need for an alternative to image-based navigation that allow for precise and accurate mapping in GPS-denied environments on any planetary body. Here, we describe the Kinematic Navigation and Cartography Knapsack (KNaCK) LiDAR system; a backpack-mounted, mobile navigation and terrain mapping system that uses a velocity-sensing coherent light detection and ranging (LiDAR) system based on a frequency modulated continuous wave (FMCW) technique, contains minimal moving parts, and employs sophisticated positioning algorithms. During a traverse, this instrument emits light pulses to continually scan a scene to build a three-dimensional point cloud representation of topography. A measure of the Doppler-velocity at each of millions of range points sampled per second allows for a 6 degree of freedom (6- DoF) estimate of the sensor’s position and the development of novel position-from-velocity mapping and positioning algorithms for loop-closure in GPS denied environments. Included with paper is the video presentation for the Figure 2: FMCW-LiDAR sensor on Kinematic Navigation and Cartography Knapsack (KNaCK) (Aeva Aeries 1)

M. Zanetti↗
DOE OSTI2020

Shallow cumuli cover and its uncertainties from ground-based lidar–radar data and sky images

Cloud cover estimates of single-layer shallow cumuli obtained from narrow field-of-view (FOV) lidar–radar and wide-FOV total sky imager (TSI) data are compared over an extended period (2000–2017 summers) at the established United States Atmospheric Radiation Measurement mid-continental Southern Great Plains site. We quantify the impacts of two factors on hourly and sub-hourly cloud cover estimates: (1) instrument-dependent cloud detection and data merging criteria and (2) FOV configuration. Enhanced observations at this site combine the advantages of the ceilometer, micropulse lidar (MPL) and cloud radar in merged data products. Data collected by these three instruments are used to calculate narrow-FOV cloud fraction (CF) as a temporal fraction of cloudy returns within a given period. Sky images provided by TSI are used to calculate the wide-FOV fractional sky cover (FSC) as a fraction of cloudy pixels within a given image. To assess the impact of the first factor on CF obtained from the merged data products, we consider two additional subperiods (2000–2010 and 2011–2017 summers) that mark significant instrumentation and algorithmic advances in the cloud detection and data merging. We demonstrate that CF obtained from ceilometer data alone and FSC obtained from sky images provide the most similar and consistent cloud cover estimates; hourly bias and root-mean-square difference (RMSD) are within 0.04 and 0.12, respectively. However, CF from merged MPL–ceilometer data provides the largest estimates of the multiyear mean cloud cover, about 0.12 (35 %) and 0.08 (24 %) greater than FSC for the first and second subperiods, respectively. CF from merged ceilometer–MPL–radar data has the strongest subperiod dependence with a bias of 0.08 (24 %) compared to FSC for the first subperiod and shows no bias for the second subperiod. The strong period dependence of CF obtained from the combined ceilometer–MPL–radar data is likely results from a change in what sensors are relied on to detect clouds below 3 km. After 2011, the MPL stopped being used for cloud top height detection below 3 km, leaving the radar as the only sensor used in cloud top height retrievals. To quantify the FOV impact, a narrow-FOV FSC is derived from the TSI images. We demonstrate that FOV configuration does not modify the bias but impacts the RMSD (0.1 hourly, 0.15 sub-hourly). In particular, the FOV impact is significant for sub-hourly observations, where 41 % of narrow- and wide-FOV FSC differ by more than 0.1. A new “quick-look” tool is introduced to visualize impacts of these two factors through integration of CF and FSC data with novel TSI-based images of the spatial variability in cloud cover. The influence of cloud field organization, such cloud streets parallel to the wind direction, on narrow- and wide-FOV cloud cover estimates can be visually assessed.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1981

Spatial and temporal filtering technique for processing lidar photocount data

Shot noise places a practical limit on the spatial and temporal resolution of lidar photocount data. A 2-D signal-processing technique that utilizes spatial and temporal filtering to reduce shot noise and increase resolution is described. The technique is applied to sodium lidar data collected during the fall of 1979 over Urbana, Illinois. Temporal filtering is shown to enhance the spatial resolution of the sodium profiles significantly by reducing shot noise by more than 10 dB. The signal-processing technique is applicable to a wide variety of lidar data.

Gardner, C. S.↗
NASA NTRS1975

A comparison of dustsonde and LIDAR measurements of stratospheric aerosols

This paper describes the results and analysis of an experiment to compare the stratospheric aerosol profiles as measured by a balloon-borne in situ particle counter and by the backscattered light from a ground-based laser radar (LIDAR) operating at a wavelength of 6943 A. The profile comparison agrees within the experimental errors for particles with radii greater than 0.25 micrometer and for altitudes between 15 and 28 kilometers. Following the calibration tests, the LIDAR was used to monitor the stratospheric aerosols at Hampton, Virginia. Enhanced backscatter appeared sporadically in November and December of 1974 over Hampton; scattering ratios averaged over altitude increments of 450 meters range from 1.10 at 20 kilometers in early November to 3.3 at 17 kilometers on December 18. The source of this enhanced backscattering is attributed to the aerosols associated with the eruption of the Fuego volcano in Guatemala in mid-October.

Remsberg, E. E.↗
NASA NTRS1985

Coherent Doppler lidars: Current US 9-11 micrometer systems

To gain a proper perspective of the potential of coherent Doppler lidars for global wind sensing sometime in the future, we need to examine where we are, how we got here, and the expectations for future lidar system development. First we give a brief review of lidar developments leading to our present technology. Next we survey present U.S. infrared systems with particular attention to the pulsed systems since they are the ones that will have sufficient range to operate from satellites. Finally we comment on trends and probable future developments. Only unclassified lidars are considered. The considerable DoD support for classified applications certainly enhances future developments in components and subsystems.

Hall, Freeman F., Jr.↗
NASA NTRS1999

Cloud Liquid Water, Mean Droplet Radius and Number Density Measurements Using a Raman Lidar

A new technique for measuring cloud liquid water, mean droplet radius and droplet number density is outlined. The technique is based on simultaneously measuring Raman and Mie scattering from cloud liquid droplets using a Raman lidar. Laboratory experiments on liquid micro-spheres have shown that the intensity of Raman scattering is proportional to the amount of liquid present in the spheres. This fact is used as a constraint on calculated Mie intensity assuming a gamma function particle size distribution. The resulting retrieval technique is shown to give stable solutions with no false minima. It is tested using Raman lidar data where the liquid water signal was seen as an enhancement to the water vapor signal. The general relationship of retrieved average radius and number density is consistent with traditional cloud physics models. Sensitivity to the assumed maximum cloud liquid water amount and the water vapor mixing ratio calibration are tested. Improvements to the technique are suggested.

Whiteman, David N.↗