Search NASA⌕ Search

SEARCH · Search NASA

Results for “Radar sensor data”

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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
NASA NTRS1978

Synthetic aperture radar operator tactical target acquisition research

A radar target acquisition research study was conducted to access the effects of two levels of 13 radar sensor, display, and mission parameters on operator tactical target acquisition. A saturated fractional-factorial screening design was employed to examine these parameters. Data analysis computed ETA squared values for main and second-order effects for the variables tested. Ranking of the research parameters in terms of importance to system design revealed four variables (radar coverage, radar resolution/multiple looks, display resolution, and display size) accounted for 50 percent of the target acquisition probability variance.

Hershberger, M. L.↗
NASA NTRS1995

Comparison of Satellite-Derived Wind Measurements with Other Wind Measurement Sensors

The purpose of this paper is to compare the good data from the Jimsphere launches with the data from the satellite system. By comparing the wind speeds from the Fixed Pedestal System 16 (FPS-16) Radar/Jimsphere Wind System and NASA's 50-MHz Radar Wind Profiler, the validation of winds from Geostationary Operational Environmental Satellite 7 (GOES-7) is performed. This study provides an in situ data quality check for the GOES-7 satellite winds. Comparison was made of the flowfields in the troposphere and the lower stratosphere of case studies of pairs of Jimsphere balloon releases and Radar Wind Profiler winds during Space Shuttle launches. The mean and standard deviation of the zonal component statistics, the meridional component statistics, and the power spectral density curves show good agreement between the two wind sensors. The standard deviation of the u and v components for the STS-37 launch (consisting of five Jimsphere/Radar Wind Profiler data sets) was 1.92 and 1.67 m/s, respectively; for the STS-43 launch (there were six Jimsphere/Wind Profiler data sets) it was 1.39 and 1.44 m/s, respectively. The overall standard deviation was 1.66 m/s for the u component and 1.55 m/s tor the v component, and a standard deviation of 2.27 m/s tor the vector wind difference. The global comparison of satellite with Jimsphere balloon vector winds shows a standard deviation of 3.15 m/s for STS-43 and 4.37 m/s for STS-37. The overall standard deviation of the vector wind was 3.76 m/s, with a root-mean-square vector difference of 4.43 m/s. These data have demonstrated that this unique comparison of the Jimsphere and satellite winds provides excellent ground truth and a frame of reference during testing and validation of satellite data

Susko, Michael↗
NASA NTRS1989

Microwave remote sensing and radar polarization signatures of natural fields

Theoretical models developed for simulation of microwave remote sensing of the Earth surface from airborne/spaceborne sensors are described. Theoretical model calculations were performed and the results were compared with data of field measurements. Data studied included polarimetric images at the frequencies of P band, L band, and C band, acquired with airborne polarimeters over a agricultural field test site. Radar polarization signatures from bare soil surfaces and from tree covered fields were obtained from the data. The models developed in this report include: (1) Small perturbation model of wave scatterings from randomly rough surfaces, (2) Physical optics model, (3) Geometrical optics model, and (4) Electromagnetic wave scattering from dielectric cylinders of finite lengths, which replace the trees and branches in the modeling of tree covered field. Additionally, a three-layer emissivity model for passive sensing of a vegetation covered soil surface is also developed. The effects of surface roughness, soil moisture contents, and tree parameters on the polarization signatures were investigated.

Mo, Tsan↗
NASA NTRS2003

Monitoring Volcanoes by Use of Air-Dropped Sensor Packages

Sensor packages that would be dropped from airplanes have been proposed for pre-eruption monitoring of physical conditions on the flanks of awakening volcanoes. The purpose of such monitoring is to gather data that could contribute to understanding and prediction of the evolution of volcanic systems. Each sensor package, denoted a volcano monitoring system (VMS), would include a housing with a parachute attached at its upper end and a crushable foam impact absorber at its lower end (see figure). The housing would contain survivable low-power instrumentation that would include a Global Positioning System (GPS) receiver, an inclinometer, a seismometer, a barometer, a thermometer, and CO2 and SO2 analyzers. The housing would also contain battery power, control, data-logging, and telecommunication subsystems. The proposal for the development of the VMS calls for the use of commercially available sensor, power, and telecommunication equipment, so that efforts could be focused on integrating all of the equipment into a system that could survive impact and operate thereafter for 30 days, transmitting data on the pre-eruptive state of a target volcano to a monitoring center. In a typical scenario, VMSs would be dropped at strategically chosen locations on the flanks of a volcano once the volcano had been identified as posing a hazard from any of a variety of observations that could include eyewitness reports, scientific observations from positions on the ground, synthetic-aperture-radar scans from aircraft, and/or remote sensing from aboard spacecraft. Once dropped, the VMSs would be operated as a network of in situ sensors that would transmit data to a local monitoring center. This network would provide observations as part of an integrated volcano-hazard assessment strategy that would involve both remote sensing and timely observations from the in situ sensors. A similar strategy that involves the use of portable sensors (but not dropping of sensors from aircraft) is already in use in the Volcano Disaster Assistance Program (VDAP), which was developed by the U.S. Geological Survey and the U.S. Office of Foreign Disaster Assistance to respond to volcanic crises around the world. The VMSs would add a greatly needed capability that would enable VDAP response teams to deploy their volcano-monitoring equipment in a more timely manner with less risk to personnel in the field.

Kedar, Sharon↗
DOE OSTI2021

Lightweight LSTM for CAN Signal Decoding

This paper describes an approach to identify undecoded Controller Area Network (CAN) data from one vehicle, based on the data similarity to previously decoded CAN data from another vehicle. Modern vehicles communicate data and signals from on-board sensors and controllers through the CAN bus. Networked sensors contain information such as wheel speeds, fuel gauges, turn signals, and radar signals. In the effort to use this information and make cars safer through human-in-the-loop CPS, signals on the CAN bus such as wheel speed and radar can be used to support the driver. However, data from the CAN bus are encoded and in some cases compressed, and different car manufacturers use different encoding schemes to represent data on the CAN bus. With hundreds of messages and thousands of possible encoding schemes to consider, it is laborious to identify the unique bits and encoding schemes that represent signals on each vehicle. In this study, we propose a method for training a Long Short-Term Memory (LSTM) neural network on known radar signals from one vehicle manufacturer, a Toyota, and successfully apply the network to identify the encoding for radar signals on a different vehicle, a Honda. By augmenting the training dataset with varied encoding bit boundaries, a small and lightweight LSTM network can learn to recognize radar data across different encoding schemes. The results are an improvement on exhaustive-search algorithms and other methods previously used in the search for such signals.

Ngo, Paul↗
NASA NTRS1987

Microwave and video sensor fusion for the shape extraction of 3D space objects

A new system for the fusion of optical image data and polarized radar scattering cross-sections is presented. By considering the scattering data in conjunction with image data, the problem of ambiguity can be reduced. Only a small part of the surface needs to be reconstructed from the radar cross-sections; the remaining portion is constrained by the optical image.

Shaw, Scott W.↗
NASA NTRS2021

GA-ASI Final Report and Program Wrap-up for NASA System Integration and Operationalization (SIO)

The NASA SIO demonstration flight of April 3, 2020 represents a successful culmination of 18 months of coordinated effort between GA-ASI, NASA, the FAA, Collins Aerospace, and Honeywell Aerospace to operate a Medium Altitude, Long Endurance (MALE) Unmanned Aircraft System (UAS) safely in the National Airspace System (NAS) using industry leading prototype technologies. The GA-ASI team consisted of technical experts, program managers, engineers, mechanics, flight technicians, flight crews, and numerous other subject matter experts. This final report describes the most significant and potentially impactful aspects of the planning, integration, test, and flight aspects of this effort. GA-ASI successfully integrated the key technologies needed for UAS to fly in the NAS onto our prototype SkyGuardian UAS, which was designed to meet the most stringent airworthiness standards applicable to an aircraft of its size category. A proven Detect and Avoid (DAA) system, developed by GA-ASI and utilizing Honeywell Aerospace technology was integrated onto SkyGuardian for the first time, along with datalink radios from Collins Aerospace that meet the new civil standard for Control and Non-Payload Communication (CNPC) links. GA-ASI also obtained approvals from the FAA and FCC to operate the reconfigured UAS. The SIO demonstration flight represented a commercial aerial surveying operation conducted at medium altitude (>10,000ft above mean sea level). The aircraft’s onboard sensors were used to capture photographic, infrared and radar imagery of public and commercial infrastructure and land, and to subsequently produce the types of data products that would provide business value to potential customers. These survey services would supplement or replace services currently provided by manned airplanes and helicopters, small drones or satellites. A “virtual” mission was also planned, to show what additional survey data could have been captured during the flight if additional sensors had been installed on the aircraft’s external hardpoints. This revision of the final report focuses on information of value to the wider UAS community, and avoids propriety data to facilitate broad dissemination. It also includes a description of GA-ASI’s engagement with the FAA following the SIO flight, which led to the award of an updated Special Airworthiness Certificate in the Experimental Category (SAC-EC) and a Certificate of Waiver or Authorization (COA) allowing operation of the SkyGuardian UAS using its DAA system to satisfy right-of-way rules, instead of a chase plane. The associated operational limitations are described to illustrate the further steps that would be needed to remove those limitations for unhindered commercial operations.

Flight demonstration↗
NASA NTRS2022

DataSet: Aerial Object Trajectory Classification by Training on Flight Controller Data and Testing on RADAR Generated

Onboard collision avoidance is needed to enable safe, autonomous flight operations for NASA projects such as Advanced Air Mobility (AAM), as well as many commercial applications. Real-time aerial object classification will improve onboard collision avoidance algorithm decision making and may reduce unnecessary activation of avoidance systems. This work trains an aircraft trajectory classifier using trajectories from flight controller logs and tests the classifier using RADAR collected trajectories during air to air experiments and ground to air experiments. In contrast to RADAR data, these flight controller logs are relatively abundant, which makes the possibility of substituting flight data for RADAR data an attractive, cost-effective option. The SVM model developed in this work achieved a 79.7% classification accuracy on the first second of radar trajectories of GA, multirotor sUAS, and fixed wing sUAS. Findings from this e that it is feasible to classify sensor collected trajectories using a classifier trained flight controller data.

Chester V Dolph↗
NASA NTRS1982

Analysis of geologic terrain models for determination of optimum SAR sensor configuration and optimum information extraction for exploration of global non-renewable resources. Pilot study: Arkansas Remote Sensing Laboratory, part 1, part 2, and part 3

Computer-generated radar simulations and mathematical geologic terrain models were used to establish the optimum radar sensor operating parameters for geologic research. An initial set of mathematical geologic terrain models was created for three basic landforms and families of simulated radar images were prepared from these models for numerous interacting sensor, platform, and terrain variables. The tradeoffs between the various sensor parameters and the quantity and quality of the extractable geologic data were investigated as well as the development of automated techniques of digital SAR image analysis. Initial work on a texture analysis of SEASAT SAR imagery is reported. Computer-generated radar simulations are shown for combinations of two geologic models and three SAR angles of incidence.

Kaupp, V. H.↗
NASA NTRS1972

A combined radar-radiometer with variable polarization

An instrument is described that provides both radar and radiometer data at the same time. The antenna and receiver are time shared for the two sensor functions. The antenna polarization can be electronically scanned at rates up to 5000 changes for both the transmit and receive signal paths. This equipment is to investigate target signatures for remote sensing applications. The function of the equipment is described and the results for observations of asphalt, grass, and gravel surfaces are presented.

Martin, D. P.↗
NASA NTRS1991

The EOSDIS Version 0 Distributed Active Archive Center for physical oceanography and air-sea interaction

The Distributed Active Archive Center (DAAC) at the Jet Propulsion Laboratory will support scientists specializing in physical oceanography and air-sea interaction. As part of the NASA Earth Observing System Data and Information System Version 0 the DAAC will build on existing capabilities to provide services for data product generation, archiving, distribution and management of information about data. To meet scientist's immediate needs for data, existing data sets from missions such as Seasat, Geosat, the NOAA series of satellites and the Global Positioning Satellite system will be distributed to investigators upon request. In 1992, ocean topography, wave and surface roughness data from the Topex/Poseidon radar altimeter mission will be archived and distributed. New data products will be derived from Topex/Poseidon and other sensor systems based on recommendations of the science community. In 1995, ocean wind field measurements from the NASA Scatterometer will be supported by the DAAC.

Hilland, Jeffrey E.↗
NASA NTRS2002

Ship Radar Observations of a Developing Hurricane in the East Pacific

During the recently completed East Pacific Investigation of Climate Processes in the Coupled Ocean-Atmosphere System (EPIC) field program, the NOAA research vessel Ronald H. Brown (RHB) was deployed in the east Pacific Inter Tropical Convergence Zone (ITCZ) for approximately 3 weeks near 10 deg. N, 95 deg. W. One of the principal objectives of the EPIC-ITCZ program was to observe the modulation of convection by synoptic-scale easterly waves and the air-sea coupling process in this poorly sampled region of the east Pacific. Data from the experiment will be used as validation to improve forecast models. The RHB carried a variety of platforms during EPIC to sample atmospheric and oceanic phenomena, including a scanning C-band Doppler radar, radiation flux instrumentation, air-sea flux system, Doppler lidar, 35 GHz cloud radar, UHF wind profiler, sea surface temperature (SST) sensors, as well as standard surface meteorological instrumentation and a suite of rain gauges. This presentation will focus on the analysis of C-band radar data that was collected on 10 September, 2001 as the ship passed through an easterly wave which later developed into hurricane Ivo. The ship captured approximately 12 hours of convection associated with the tropical disturbance. During this period, the domain sampled by the radar (approximately 71,000 sq km) contained a significant number of echo features. Specifically, the fraction of the domain containing radar echo above 10 dBZ reached 80% for over 2 hours and remained near 60% for a continuous six hour period. Animation of radar images showed distinct rotation in echo features associated with the easterly wave passage. Despite an approximate 4 C drop in surface air temperature and sustained winds approaching 20 m/ s, the SST remained nearly constant throughout the observation period (approx. 29.5 C). Peak values of latent and sensible heat flux exceeded 400 and 100 W /sq m, respectively. The radar documented the change in precipitation vertical structure as the ship passed through regions of significant convection with echo tops approaching 14 km and 30 dBZ echo tops extending to near 9 km embedded in regions that were predominantly stratiform in nature. Single Doppler retrievals (Extended Velocity Azimuth Display) were conducted continuously at 10-minute resolution for approximately 4 hours in the latter part of the observation period, and documented the transition from convection (low-level convergence, upper level divergence) to stratiform (mid-level convergence sandwiched between upper and lower level divergence) kinematic structure.

Cifelli, Robert↗
NASA NTRSDate not supplied

Comparing Tropopause-Penetrating Convection Identifications Derived from NEXRAD and GOES over the Contiguous United States

Overshooting cloud tops (OTs) are a result of powerful updrafts that rapidly transport air from the troposphere to the lower stratosphere. Aside from the well-known relationships between strong updrafts and severe weather, the boundaries of updrafts, including the OT, are turbulent, which leads to irreversible mixing of air between the stratosphere and troposphere, altering the composition of both layers. In order to better understand the impact of OTs, knowing precisely when and where they occur is vital. Within the last decade remote-sensing observations from satellites and radars have been used to identify OTs, but the results thus far have not been entirely consistent due to challenges with accurately identifying OTs with these sensor datasets. This study compares OTs identified using NEXRAD reflectivity data from the GridRad dataset with an approach that uses GOES infrared (IR) data. The GridRad method estimates the altitude of echo tops directly from the radar pointing geometry, merging a combination of radars that enables products every 5 mins, with 2 km spatial and 1 km vertical grid spacing. The GOES satellite method uses spatial patterns in tropopause-relative IR brightness temperature to derive an OT likelihood. The study region covers a large part of the contiguous United States during selected active convection dates in 2017 and includes data from GOES-13/16. A large sample of OTs observed by NEXRAD and GOES-13/16 satellites are analyzed to better understand NEXRAD and IR observations of OTs, quantify agreement between the OT detection methods, and demonstrate how the 4x increase in spatial resolution from GOES-13 to GOES-16 impacts OT algorithm detection performance. The results show that for nearly time-matched scenes, with many severe storms, GOES-13 and -16 detection accuracy is quite comparable; however, some missed detections are attributed to poorer GOES-13 image resolution. It was found that GOES-13 OT regions are ~2 K warmer than GOES-16 on average, but such differences exceed 5 K for the most intense OT regions. It is found that false GOES IR-based detections are unavoidable, given that cold cloud pixels significantly colder than the tropopause from nearby or recently decayed OTs can persist within anvils for 15 minutes or more.

John W. Cooney↗
NASA NTRS2007

Simulation Studies of Forest Structure using 3D Lidar and Radar Models

The use of lidars and radars to measure forest structure attributes such as height and biomass are being considered for future Earth Observation missions. Large footprint lidar makes a direct measurement of the heights of scatterers in the illuminated footprint and can yield information about the vertical profile of the canopy. Synthetic Aperture Radar (SAR) is known to sense the canopy volume, especially at longer wavelengths and is useful for estimating biomass. Interferometric SAR (InSAR) has been shown to yield forest canopy height information. For example, the height of scattering phase retrieved from InSAR data is considered to be correlated with the three height and the spatial structure of the forest stand. There is much interest in exploiting these technologies separately and together to get important information for carbon cycle and ecosystem science. More detailed information of the electromagnetic radiation interactions within forest canopies is needed. And backscattering models can be of much utility here. As part of a NASA funded project to explore data fusion, a three-dimensional (3D) coherent radar backscattering model and a 3D lidar backscatter models were used to investigate the use of large footprint lidar, SAR and InSAR for characterizing realistic forest scenes. For this paper, we use stem maps and other forest measurements to develop a realistic spatial structure of a spruce-hemlock forest canopy found in Maine, USA. The radar and lidar models used measurements of the 3D forest scene as input and simulated the coherent radar backscattering signature and 1064nm energy backscatter, respectively. The relationships of backscatter derived forest structure were compared with field measurements. In addition, we also had detailed airborne lidar (Laser Imaging Vegetation Sensor, LVIS) data available over the stem map sites that was used to study the accuracies of tree height derived from modeled SAR backscatter and the scattering phase center retrieved from the simulated InSAR data will be compared with the height indices, or other structure parameters derived from the lidar data. These results will address the possible synergies between lidar and radar in data in terms of forest structural information.

Sun, Guoqing↗
NASA NTRS2011

UAVSAR Instrument: Current Operations and Planned Upgrades

The Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) instrument is a pod-based Lband polarimetric synthetic aperture radar (SAR), specifically designed to acquire airborne repeat track SAR data for differential interferometric measurements. This instrument is currently installed on the NASA Gulfstream- III (G-III) aircraft with precision real-time Global Positioning System (GPS) and a sensor-controlled flight management system for precision repeat-pass data acquisitions. UAVSAR has conducted engineering and preliminary science data flights since October 2007 on the G-III. We are porting the radar to the Global Hawk Unmanned Airborne Vehicle (UAV) to enable long duration/long range data campaigns. We plan to install two radar pods (each with its own active array antenna) under the wings of the Global Hawk to enable the generation of precision topographic maps and single pass polarimetric-interferometry (SPI) providing vertical structure of ice and vegetation. Global Hawk's range of ~ 8000 nm will enable regional surveys with far fewer sorties as well as measurements of remote locations without the need for long and complicated deployments. We are also developing P-band polarimetry and Ka-band single-pass interferometry capabilities on UAVSAR by replacing the radar antenna and front-end electronics to operate at these

Uninhabited Airborne Vehicle Synthetic Aperture Ra↗
NASA NTRS1982

Shuttle Imaging Radar-A (SIR-A) experiment

The SIR-A experiment was conducted in order to acquire radar data over a variety of regions to further understanding of the radar signatures of various geologic features. The capability of the Shuttle as a scientific platform for observation of the Earth's resources was assessed. The SIR-A sensor operated nominally and the full data acquisition capacity of the optical recorder was used.

Elachi, C.↗
NASA NTRSDate not supplied

Aerial Object Trajectory Classification by Training on Flight Controller Data and Testing on RADAR Generated Tracks

Onboard collision avoidance is needed to enable safe, autonomous flight operations for NASA projects such as Advanced Air Mobility (AAM), as well as many commercial applications. Real-time aerial object classification will improve onboard collision avoidance algorithm decision making and may reduce unnecessary activation of avoidance systems. This work trains an aircraft trajectory classifier using trajectories from flight controller logs and tests the classifier using RADAR collected trajectories during air to air experiments and ground to air experiments. In contrast to RADAR data, these flight controller logs are relatively abundant, which makes the possibility of substituting flight data for RADAR data an attractive, cost-effective option. The SVM model developed in this work achieved a 79.7% classification accuracy on the first second of radar trajectories of GA, multirotor sUAS, and fixed wing sUAS. Findings from this work indicate that it is feasible to classify sensor collected trajectories using a classifier trained on flight controller data.

Henry Holbrook↗
NASA NTRS1986

The role of space borne imaging radars in environmental monitoring: Some shuttle imaging radar results in Asia

The synoptic view afforded by orbiting Earth sensors can be extremely valuable for resource evaluation, environmental monitoring and development planning. For many regions of the world, however, cloud cover has prevented the acquisition of remotely sensed data during the most environmentally stressful periods of the year. How synthetic aperture imaging radar can be used to provide valuable data about the condition of the Earth's surface during periods of bad weather is discussed. Examples are given of applications using data from the Shuttle Imaging Radars (SIR) A and B for agricultural land use and crop condition assessment, monsoon flood boundary and flood damage assessment, water resource monitoring and terrain modeling, coastal forest mapping and vegetation penetration, and coastal development monitoring. Recent SIR-B results in Bangladesh are emphasized, radar system basics are reviewed and future SAR systems are discussed.

Imhoff, Marc L.↗