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At least 793 records · Page 44
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NASA NTRS2019

Remote ID for Rapid Assessment of Flight and Vehicle Information

The ability to rapidly identify UAS in the field has emerged as a critical need for the integration of small UASs into the national airspace and counter-uas operations. This paper proposes an architecture for rapid retrieval of UAS information leveraging NASA's current Unmanned Aircraft System (UAS) Traffic Management (UTM) system. The proposed architecture utilizes UTM components: FIMS (Flight Information Management System), USS (UAS Service Supplier), and vehicle registration and model database in order to provide assessment of the UAS reported in the field including the ability to distinguish between participating and non- participating UTM actors. Detailed system descriptions are provided and preliminary results from field tests conducted during UTM TCL (Technical Capability Level) 3 are discussed. It is found that 94% of the remote ID look-ups were successful. The average time of a look-up is found to be 1.2 seconds. Failure cases are examined and recommendations on next steps to advance UAS remote identification are provided.

Ishihara, Abraham K.↗
NASA NTRS2019

Response Timing: Low Airspeed (Energy) Alerting

In response to NTSB Safety Recommendation A-14-043, the FAA was asked to task a panel of human factors, aviation operations, and aircraft design specialists, such as the Avionics Systems Harmonization Working Group (ASHWG), to develop design requirements for context-dependent low energy alerting systems for airplanes engaged in commercial operations. This recommendation is in association to the July 6, 2013, accident involving a Boeing 777-200ER, Korean registration HL7742, operating as Asiana Airlines flight 214, which was on approach to runway 28L when it struck a seawall at San Francisco International Airport (SFO), San Francisco, California. The FAA asked for human factor support from NASA in developing design requirements for context-dependent low energy alerting systems for airplanes engaged in commercial operations. Recently the ASHWG chair asked for continued support in examining flightcrew alert response timing and requested that NASA update the previous working paper on this subject. This product/paper will be provided to the ASHWG as part of the ongoing assignments from each of the ASHWG members in support of developing requirements and guidance for context-dependent low energy alerting systems for airplanes. The ASHWG is made up of interested parties from government and industry.

response timing↗
NASA NTRS2019

GOES-16 and GOES-17 ABI INR Assessment

The first two satellites of the US Geostationary Operational Environmental Satellite R-Series (GOES-R) were launched on November 19, 2016 and March 1, 2018 respectively. GOES-16 officially became GOES East on December 18, 2017, and the designation of GOES-17 as GOES West occurred on February 12 2019. The Advanced Baseline Imager (ABI) is the primary instrument on GOES-16 and GOES-17 for imaging Earth’s surface and atmosphere to significantly improve the detection and observation of severe environmental phenomena. The Image Navigation and Registration (INR) Performance Assessment Tool Set (IPATS) was developed to assess INR performance of GOES-R series ABI images. In this paper, we first describe the assessment of IPATS algorithm accuracy. Next, we present the relationship between view zenith angle (VZA) and the quality of the IPATS measurements. Lastly, we present GOES-16 and GOES-17 navigation (NAV) assessments results from flight data spanning from the start of INR assessment to June 2019. The results show a) IPATS “stair step” measurement error is less or equal to 0.06 ABI pixel with IPATS baseline configuration; b) VZA is an effective filter to exclude outliers of the measurements; and c) ABI INR for both satellites has improved over time as post-launch tests (PLT) were performed and corrections applied. This paper also shows that the post-launch INR tuning of GOES-17 was much shorter than GOES-16.

GOES-17↗
NASA NTRS2019

Joint 3D-Wind Retrievals with Stereoscopic Views from MODIS and GOES

Atmospheric motion vectors (AMVs), derived by tracking patterns, represent the winds in a layer characteristic of the pattern. AMV height (or pressure), important for applications in atmospheric research and operational meteorology, is usually assigned using observed IR brightness temperatures with a modeled atmosphere and can be inaccurate. Stereoscopic tracking provides a direct geometric height measurement of the pattern that an AMV represents. We extend our previous work with multi-angle imaging spectroradiometer (MISR) and GOES to moderate resolution imaging spectroradiometer (MODIS) and the GOES-R series advanced baseline imager (ABI). MISR is a unique satellite instrument for stereoscopy with nine angular views along track, but its images have a narrow (380 km) swath and no thermal IR channels. MODIS provides a much wider (2330 km) swath and eight thermal IR channels that pair well with all but two ABI channels, o e ring a rich set of potential applications. Given the similarities between MODIS and VIIRS, our methods should also yield similar performance with VIIRS. Our methods, as enabled by advanced sensors like MODIS and ABI, require high-accuracy geographic registration in both systems but no synchronization of observations. AMVs are retrieved jointly with their heights from the disparities between triplets of ABI scenes and the paired MODIS granule. We validate our retrievals against MISR-GOES retrievals, operational GOES wind products, and by tracking clear-sky terrain. We demonstrate that the 3D-wind algorithm can produce high-quality AMV and height measurements for applications from the planetary boundary layer (PBL) to the upper troposphere, including cold-air outbreaks, wildfire smoke plumes, and hurricanes.

Carr, James L.↗
NASA NTRS2019

GOES-16 and GOES-17 ABI INR Assessment

The Image navigation and registration (INR) Performance Assessment Tool Set (IPATS) measurement accuracy, within 0.06 pixels, is sufficient for INR assessment. IPATS is not a static system. Additional filters and/or sub-procedures were developed when the demand emerged, e.g. the development of Short Term AbNormal Dectection (STAND) and View Zenith Angle (VZA) filters in post-launch test (PLT) of GOES-16 and GOES-17 respectively. NAV INR accuracy improved with updates and tuning in PLT. Currently, NAV errors are about 1-2 urad for all assessed channels of both ABIs. IPATS NAV assessments will continue to provide feedback for tuning the navigation algorithms and parameters in future updates and future GOES-R series ABIs.

GOES-17↗
NASA NTRS2020

Validation of SAGE III/ISS Solar Ozone Data with Correlative Satellite and Ground Based Measurements

The Stratospheric Aerosol and Gas Experiment III on the International Space Station (SAGE III/ISS) was launched on February 19, 2017 and began routine operation in June 2017. The first two years of SAGE III/ISS (v5.1) solar ozone data were evaluated by using correlative satellite and ground-based measurements. Among the three (MES, AO3, and MLR) SAGE III/ISS solar ozone products, AO3 ozone shows the best accuracy and precision, with mean biases less than 5% for altitudes ~15–55 km in the mid-latitudes and ~20–55 km in the tropics. In the lower stratosphere and upper troposphere, AO3 ozone shows high biases that increase with decreasing altitudes and reach ~10% near the tropopause. Preliminary studies indicate that those high biases primarily result from the contributions of the oxygen dimer (O4) not being appropriately removed within the ozone channel. The precision of AO3 ozone is estimated to be ~3% for altitudes between 20 and 40 km. It degrades to ~10–15% in the lower mesosphere (~55 km), and ~20–30% near the tropopause. There could be an altitude registration error of ~100 meter in the SAGE III/ISS auxiliary temperature and pressure profiles. This, however, does not affect retrieved ozone profiles in native number density on geometric altitude coordinates. In the upper stratosphere and lower mesosphere (~40–55 km) the SAGE III/ISS (and SAGE II) sunset ozone values are systematically higher than sunrise data by ~5–8% which are almost twice larger than what observed by other satellites or model predictions. This feature needs further study.

H J Wang↗
NASA NTRSDate not supplied

Integrated System for Autonomous and Adaptive Caretaking (ISAAC): Phase 1 Low-Fidelity Demo

This presentation describes the ISAAC phase 1 low-fidelity demonstration results. The demonstration satisfied the milestone from the Gateway-ISAAC Memorandum of Understanding to "Demonstrate spatial and logical data registration between robotics and spacecraft". It integrated many new ISAAC components, including a spatially linked model, Astrobee multi-sensor mapping, and an integrated data interface. It advanced ISAAC key performance parameters related to mapping, in a lab setting. Areas for phase 1 forward work include: improve maturity toward the high-fidelity demo on the ISS; demonstrate mapping with more sensor modalities; expand initial anomaly detection implementation into a flexible framework with multiple detection algorithms for different tasks; begin open source software release process for releasable ISAAC components.

robotics↗
NASA NTRSDate not supplied

Overview of NASA's Break the Ice Lunar Challenge

The goal of NASA’s Artemis program is to return to the Moon and put in place a sustainable infrastructure that will enable permanent presence on the Moon. In-Situ Resource Utilization (ISRU) is critical in making the permanent presence on the Moon possible. One of the most important of these resources is water. On the Moon, water is trapped in icy regolith at the lunar poles, including inside permanently dark and cold craters. Excavating icy regolith and extracting water from it needs development of technologies that can operate reliably in the extreme lunar environmental conditions. Prize competitions are a well-known way of accelerating the development of new technologies and have been successfully used throughout the history. NASA’s Centennial Challenges Program(CCP) has been developing and executing prize competitions for past 15 years. Several of these competitions resulted in breakthrough technologies for in-space and terrestrial applications. In 2019, NASA Space Technology Mission Directorate (STMD) tasked CCP to develop a challenge to address the technology gaps in the areas of Lunar Excavation, Manufacturing, and Construction. This paper provides the background, status and ongoing plans by CCP in developing “Break the Ice Lunar Challenge”. The challenge is scheduled to open for registration in late 2020. This challenge will enable the development of excavation technologies that can operate in the extreme conditions on the Moon.

centennial challenges↗
NASA NTRSDate not supplied

Twenty Years of Terra MODIS Spatial Performance Using the Spectro-Radiometric Calibration Assembly

The Moderate Resolution Imaging Spectroradiometer (MODIS) instrument on-board the NASA’s Earth Observing System Terra satellite has continued successful Earth-sensing operations for over 20 years. To aid in its mission in providing calibrated science data to the worldwide user community, the MODIS instrument is equipped with several on-board calibrators designed to measure changes in the instrument response over time. One such calibrator is the Spectro-Radiometric Calibration Assembly (SRCA), which can provide a source signal for radiometric, spectral, or spatial characterization. When commanded into its spatial calibration mode, the SRCA is able to produce light across the MODIS band spectral range (0.412μm to 14.2μm) at a variety of signal levels thanks to several internal halogen lamps, an IR glow bar, and a neutral density filter. This signal, used in combination with commanded sub-sample measurements of the MODIS detectors, provides a basis for determining changes in the spatial performance of the MODIS spectral bands. This work summarizes the spatial calibration process using the SRCA and presents 20 years of Terra MODIS spatial performance characterized through co-registration between MODIS bands, detectors, and focal plane assemblies. Results from pre-launch testing using the Integration and Alignment Collimator and the SRCA are incorporated in the history of the Terra MODIS mission-long spatial performance. We also note modifications to the spatial characterization methodology brought on by changes to the SRCA’s operational configuration and changes to the MODIS spectral band performance, particularly after the recovery from the safe-mode event in February 2016. Results are compared against the MODIS design specifications.

MODIS↗
NASA NTRSDate not supplied

Latest Progress and Results in LEO-GEO and GEO-GEO Stereo AMVs

Atmospheric motion vectors (AMVs), derived by tracking patterns, represent the winds in a layer characteristic of the pattern. AMV height (or pressure), important for applications in atmospheric research and operational meteorology, is usually assigned using observed IR brightness temperatures with a modeled atmosphere and can be inaccurate. Stereoscopic tracking provides a direct geometric height measurement of the pattern that an AMV represents. We extend our previous work with multi-angle imaging spectro–radiometer (MISR) and GOES to moderate resolution imaging spectroradiometer (MODIS) and the GOES-R series advanced baseline imager (ABI). MISR is a unique satellite instrument for stereoscopy with nine angular views along track, but its images have a narrow (380 km) swath and no thermal IR channels. MODIS provides a much wider (2330 km) swath and eight thermal IR channels that pair well with all but two ABI channels, offering a rich set of potential applications. Given the similarities between MODIS and VIIRS, our methods should also yield similar performance with VIIRS. Our methods, as enabled by advanced sensors like MODIS and ABI, require high-accuracy geographic registration in both systems but no synchronization of observations. AMVs are retrieved jointly with their heights from the disparities between triplets of ABI scenes and the paired MODIS granule. We validate our retrievals against MISR-GOES retrievals, operational GOES wind products, and by tracking clear-sky terrain. We demonstrate that the 3D-wind algorithm can produce high-quality AMV and height measurements for applications from the planetary boundary layer (PBL) to the upper troposphere, including cold-air outbreaks, wildfire smoke plumes, and hurricanes.

Atmospheric motion vectors↗
NASA NTRS2018

Fusion of Multiple Low-Resolution NASA Airborne Snow Observatory (ASO) Lidar Data for Forest Vegetation Structure Characterization

Airborne lidar provides timely updated maps for monitoring forest change at high resolution but it has been little used for that purpose due to the scarcity of long-term time-series over a common area. The NASA Jet Propulsion Laboratory Airborne Snow Observatory (ASO) is a landscape-level monitoring system that provides ongoing multi-year remote sensing measurements over mountainous ecosystems to primary quantify snow volume and dynamics. It collects low-resolution lidar data (~1.5 pt/m2) with a nominal weekly frequency up to 12 times a year with measurements that span 2013-2017 over 12 mountain watersheds across the western US that currently face ecological threads. In this work, we present a method to automatically register ASO weekly low-resolution lidar point clouds in order to calculate spatially consistent datasets (~12 pt/m2) adapted to fine scale forestry studies. We test the method using 12 lidar datasets acquired over the Tuolumne River Basin (Sierra Nevada, California) in the spring and summer of 2014. On average, the ASO lidar system provides accurate measurements in terms of geolocation (0.38m and 0.12m for the horizontal and vertical dimension, respectively) but some datasets are biased up to 1.38m and 0.53m, respectively. Our registration method successfully corrected for systematic bias improving the 3D geometry of forest point clouds.

Painter, Thomas H.↗
NASA NTRS2018

Augmented Reality Data Generation for Training Deep Learning Neural Network

One of the major challenges in deep learning is retrieving sufficiently large labeled training datasets, which can become expensive and time consuming to collect. A unique approach to training segmentation is to use Deep Neural Network (DNN) models with a minimal amount of initial labeled training samples. The procedure involves creating synthetic data and using image registration to calculate affine transformations to apply to the synthetic data. The method takes a small dataset and generates a highquality augmented reality synthetic dataset with strong variance while maintaining consistency with real cases. Results illustrate segmentation improvements in various target features and increased average target confidence.

Torres, Gil↗
NASA NTRS2019

Lunar calibration and performance assessments of the NOAA-20 VIIRS reflective solar bands

The Moon has played a vital role in the radiometric stability monitoring of NASAs Earth Observing System sensors, such as MODIS on the Terra and Aqua spacecrafts. The lunar calibration methodologies developed for the two MODIS instruments were later extended to apply to the VIIRS instrument on the Suomi-NPP spacecraft. The follow-on VIIRS instrument on the NOAA-20 (N20) spacecraft (previously JPSS-1) has been successfully operating since its launch in November 2017. Fifteen VIIRS spectral bands are in the reflective solar spectral region, covering wavelengths from 0.4 to 2.3 μm. Similar to the previous MODIS and VIIRS instruments, the N20 VIIRS views the Moon via a spacecraft roll maneuver on a near-monthly basis at a confined phase angle range (-51.5° to -50.5°) to facilitate radiometric stability monitoring with reduced uncertainties. In this paper, we briefly present the lunar calibration methodology and also report the derived instrument gain parameters from the regularly scheduled lunar calibrations. The USGS Robotic Lunar Observatory (ROLO) model is used to provide the predicted lunar irradiance for each lunar measurement to account for the variation in the observation geometry. The spatial characterization algorithms using the Moon, previously developed for MODIS and SNPP VIIRS, have also been extended to N20 VIIRS to track its on-orbit band-to-band registration (BBR).

VIIRS↗
NASA NTRS2021

Residual Temperature Bias Effects in Stratospheric Species Distributions from LIMS

The Nimbus 7 Limb Infrared Monitor of theStratosphere (LIMS) instrument operated from 25 Octo-ber 1978 through 28 May 1979. Its version 6 (V6) profileswere processed and archived in 2002. We present severaldiagnostic examples of the quality of the V6 stratospheric species distributions based on their level 3 zonal Fourier co-efficient products. In particular, we show that there are smalldifferences in the ascending (A) minus descending (D) or-bital temperature–pressure orT(p) profiles (theirA−Dval-ues) that affect (A−D) species values. SystematicA−Dbi-ases inT(p) can arise from small radiance biases and/or fromviewing anomalies along orbits. There can also be (A−D)differences inT(p) due to not resolving and correcting forall of the atmospheric temperature gradient along LIMS tan-gent view-paths. An error inT(p) affects species retrievalsthrough (1) the Planck blackbody function in forward calcu-lations of limb radiance that are part of the iterative retrievalalgorithm of LIMS, and (2) the registration of the measuredLIMS species radiance profiles in pressure altitude, mainlyfor the lower stratosphere. There are clearA−Ddifferencesfor ozone, H2O, and HNO3but not for NO2. Percentage differences are larger in the lower stratosphere for ozone andH2O because those species are optically thick. We evaluateV6 ozone profile biases in the upper stratosphere with the aid of comparisons against a monthly climatology of UV–ozone soundings from rocketsondes. We also provide resultsof time series analyses of V6 ozone, H2O, and potential vor-ticity for the middle stratosphere to show that their average(A+D) V6 level 3 products provide a clear picture of the evolution of those tracers during Northern Hemisphere win-ter. We recommend that researchers use the average V6 level3 product for their science studies of stratospheric ozone andH2O, while keeping in mind that there are uncorrected non-local thermodynamic equilibrium effects in daytime ozone inthe lower mesosphere and in daytime H2O in the uppermoststratosphere. We also point out that the present-day Soundingof the Atmosphere using Broadband Emission Radiometry(SABER) experiment provides measurements and retrievalsof temperature and ozone that are nearly free of anomalousdiurnal variations and of effects from gradients at low and middle latitudes.

Ellis Remsberg↗
NASA NTRSDate not supplied

Ground control points refresh for MODIS and VIIRS geolocation monitoring

The Control Point Matching (CPM) program and a set of over 1200 globally distributed ground control points (GCPs ) have been successfully used to develop more than 20 years of MODIS geolocation products. In this research, we refresh current GCP library with more than 2500 new GCPs using the latest Landsat 8 Collection 2 images. The refreshed GCPs are distributed from 56 S to 80 N latitude, with more than 2000 shoreline and 500 inland GCP chips. The size of these GCPs are extended from800*800 to 1400*1400 Landsat pixels and the CPM program correspondingly increase s t h e searching distance from 0.8 pixels to 2.5 pixels, which also extends the geolocation error measurement from +/-45 to the edge of scan at +/-55 degree in scan angle. This will allow the algorithm to catch geolocation errors that are larger than one MODIS pixel. The geolocation errors measured with the refreshed GCP library are comparable to the previous results, yet with 2-3more times of matched GCPs. The daytime Aqua ascending orbits and Terra descending orbits enable us to identify a few GCP outliers which might be due to the quality of the original Landsat images. Most importantly, the refreshed GCP library will include images from both Landsat band 4 to match with VIIRS I1, and Landsat band 6 to match with VIIRS I3. This will allow us to measure and correct on orbit band-to-band registration at both track and scan directions, which will help understanding and improving future JPSS mission’s prelaunch geometric performance.

VIIRS↗
NASA NTRS2022

Surface Corrected Lunar MTF Measurements in MODIS and VIIRS Using the SP Model

Lunar observations have been used for sensor performance assessments for a number of Earth-observing instruments, including the Moderate Resolution Imaging Spectroradiometer (MODIS) on board Terra and Aqua and the Visible Infrared Imaging Radiometer Suite (VIIRS) on board Suomi-NPP (SNPP) and NOAA-20 (N20). While the primary purpose of lunar observations in MODIS and VIIRS is radiometric calibration, these observations have been leveraged for other sensor performance assessments such as spatial registration and deriving the modulation transfer function (MTF). In this work, we will derive the lunar MTF using a knife edge approach similar to previous work. However, to further isolate the edge of the lunar disk when deriving the edge spread function (ESF), we will apply a lunar surface variation correction using a model based on data obtained by the Spectral Profiler (SP) on board the SELENE spacecraft. This model was provided to us by AIST in Japan. To align the measured and modeled data, we developed techniques for projecting the measured lunar surface pixels onto the radiance maps produced by the SP model. We correct the lunar surface variation while preserving the signal of the lunar disk edge in the ESF, and then calculate the MTF results using standard techniques. These results are in good agreement with previously published results from both Moon-based observations in MODIS and VIIRS and from the spectroradiometric calibration assembly (SRCA) on MODIS. With the exception of MODIS bands 1 and 2, the MTF is stable on orbit for the reflective bands in both instruments.

MODIS↗
NASA NTRS2020

Residual Motion Estimation for Multi-Squint Airborne SAR

Airborne SAR data are often challenging to analyze due tothe limited accuracy of the platform motion measurements.In interferometric scenarios, even small residual motion er-rors cause undesirable artifacts in the interferometric phaseand geometric registration of image pairs. Various calibrationtechniques have been developed, often exploiting spectral di-versity in some way. The UAVSAR L-band system has imple-mented a new operating mode where multiple images are ac-quired simultaneously at different azimuth squint angles, pro-viding enhanced opportunities for motion calibration. Thispaper describes this imaging mode and the residual motioncalibration technique developed for these special data sets.

Hawkins, Brian↗