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At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

COMBLE Radar b1 Processing: Corrections, Calibrations, and Processing Report

The U.S. Department of Energy’s (DOE) Atmospheric Radiation Measurement (ARM) user facility recently concluded its Cold-Air Outbreaks in the Marine Boundary Layer Experiment (COMBLE), with its campaign emphasis on marine boundary-layer clouds and mixed-phase clouds during cold-air outbreaks. The COMBLE campaign featured the deployment of the first ARM Mobile Facility (AMF1) to northern Scandinavia (Andenes, Norway), including its standard complement of ARM cloud radars. In keeping with user demands stemming from the previous AMF Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign in Argentina, a post-campaign radar mentor effort was initiated for COMBLE. This activity was intended to improve the usability of the ARM cloud radar data sets in response to overall demands for calibrated, corrected data sets for downstream studies and retrieval applications. In addition to the terrain complexities previously important to CACTI data sets (e.g., clutter designation and/or removal), COMBLE presented new challenges to existing ARM radar mentor capabilities. These included the extension of existing methodologies (e.g., relative calibration adjustment [RCA] target techniques) to frozen environments and the potential issues with their applicability when considering mixed-phase precipitation conditions. As in the previous CACTI documentation (Hardin et al. 2020), the overall calibration and conditioning process in ARM nomenclature is referred to as generating a “b1” datastream. For the radars, these “b1” standards refer to a datastream that has been calibrated (and cross-calibrated), with effort to deliver the highest-quality (well-characterized) data possible. The “b1” radar mentor reporting (this current document) is intended to detail (i) the status/quality of the original “a1” (raw) data sets during the COMBLE AMF campaign, (ii) the corrections and calibrations that are applied to generate the b1 datastreams available on ARM’s Data Discovery, and (iii) the details of the applied methods, e.g., how radar offset/calibration numbers were determined.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2013

Optimized Radar Remote Sensing for Levee Health Monitoring

Radar remote sensing offers great potential for high resolution monitoring of ground surface changes over large areas at one time to detect movement on and near levees and for location of seepage through levees. Our NASA-funded projects to monitor levees in the Sacramento Delta and the Mississippi River have developed and demonstrated methods to use radar remote sensing to measure quantities relevant to levee health and of great value to emergency response. The DHS-funded project will enable us is to define how to optimally monitor levees in this new way and set the stage for transition to using satellite SAR (synthetic aperture radar) imaging for better temporal and spatial coverage at lower cost to the end users.

radar remote sensing↗
NASA NTRSDate not supplied

Simulated Vision-based Approach and Landing System for Advanced Air Mobility

Advanced Air Mobility (AAM) aircraft require precision approach and landing systems (PALS) in several environments, such as urban, suburban, and rural. It is challenging to implement current state-of-the-art methods approved for automated approach and landing for AAM operations with challenges such as GPS degradation in urban environments and visual navigation aids like the glideslope and localizer being narrow and not allowing alternative incoming landing angles at vertiports. However, existing technology and systems, i.e., the instrument landing system (ILS) with glideslope and localizer indicators that use vision, IR, radar, or GPS methods, provide baseline perception and sensing requirements for AAM aircraft approach and landing. This paper focuses on vision-based PAL and computer vision feature correspondence methods to demonstrate a baseline navigation system while adhering to the Federal Aviation Administration requirements and regulations about heliport design (FAA AC 150/5390-2C), which is one of the closest references for vertiport requirements and regulations. The coplanar pose from orthography and scaling with iterations (COPOSIT) algorithm determines pose estimation, which feeds into an Extended Kalman filter that combines IMU with vision to create a vision-based approach and landing (VAL) sensor fusion navigation solution for GPS-denied environments. The VAL navigation solution provides promising simulation results for AAM PALS with Hough circle detection and feature correspondence, which demonstrate robustness to false positives. This paper incorporates moderately high- fidelity simulations with computer graphics rendering to show a distributed sensor network to track an AAM aircraft during approach and landing to compare with the aircraft’s onboard vision-based navigation solution.

distributed sensing↗
NASA NTRS1982

A model for radar images and its application to adaptive digital filtering of multiplicative noise

Standard image processing techniques which are used to enhance noncoherent optically produced images are not applicable to radar images due to the coherent nature of the radar imaging process. A model for the radar imaging process is derived in this paper and a method for smoothing noisy radar images is also presented. The imaging model shows that the radar image is corrupted by multiplicative noise. The model leads to the functional form of an optimum (minimum MSE) filter for smoothing radar images. By using locally estimated parameter values the filter is made adaptive so that it provides minimum MSE estimates inside homogeneous areas of an image while preserving the edge structure. It is shown that the filter can be easily implemented in the spatial domain and is computationally efficient. The performance of the adaptive filter is compared (qualitatively and quantitatively) with several standard filters using real and simulated radar images.

Frost, V. S.↗
NASA NTRS1989

Comparison of rainfall profiles retrieved from dual-frequency radar and from combined radar and passive microwave radiometric measurements

Precipitation profiles retrieved from a dual frequency X- and Ka-band radar and from an X-band radiometer are analyzed. Profiles from combined radar and microwave radiometer measurements are compared to those from dual frequency radar measurements to study the performance of the combined radar-radiometer retrievals. A method for the retrieval of rainfall rate profiles from attenuated radar returns and passive radiometric data is presented. The results suggest that the operation of a single frequency radar with multifrequency passive radiometers may provide cost-effective spaceborne measurements of global tropical rainfall distributions. The possible use of this methodology for the Tropical Rainfall Measuring Mission is considered.

Weinman, J. A.↗
NASA NTRS1991

High-frequency techniques for RCS prediction of plate geometries

Several different high-frequency methods for modeling the radar cross sections (RCSs) of plate geometries are examined. The Method of Equivalent Currents and a numerically derived corner diffraction coefficient are used to model the RCS of a rectangular, perfectly conducting plate in nonprincipal planes. The Uniform Theory of Diffraction is used to model the RCS of a rectangular, perfectly conducting plate in principal planes. For the soft polarization case, first-order and slope-diffraction terms are included. For the hard polarization case, up to four orders of diffraction are included. Finally, the Uniform Theory of Diffraction for impedance wedges and the Impedance Boundary Condition are used to model the RCS of a coated, rectangular plate in principal planes. In most of the cases considered, comparisons are made between theoretical and experimental results.

Balanis, Constantine A.↗
NASA NTRS2002

A Stochastic Model of Space-Time Variability of Tropical Rainfall: I. Statistics of Spatial Averages

Global maps of rainfall are of great importance in connection with modeling of the earth s climate. Comparison between the maps of rainfall predicted by computer-generated climate models with observation provides a sensitive test for these models. To make such a comparison, one typically needs the total precipitation amount over a large area, which could be hundreds of kilometers in size over extended periods of time of order days or months. This presents a difficult problem since rain varies greatly from place to place as well as in time. Remote sensing methods using ground radar or satellites detect rain over a large area by essentially taking a series of snapshots at infrequent intervals and indirectly deriving the average rain intensity within a collection of pixels , usually several kilometers in size. They measure area average of rain at a particular instant. Rain gauges, on the other hand, record rain accumulation continuously in time but only over a very small area tens of centimeters across, say, the size of a dinner plate. They measure only a time average at a single location. In making use of either method one needs to fill in the gaps in the observation - either the gaps in the area covered or the gaps in time of observation. This involves using statistical models to obtain information about the rain that is missed from what is actually detected. This paper investigates such a statistical model and validates it with rain data collected over the tropical Western Pacific from ship borne radars during TOGA COARE (Tropical Oceans Global Atmosphere Coupled Ocean-Atmosphere Response Experiment). The model incorporates a number of commonly observed features of rain. While rain varies rapidly with location and time, the variability diminishes when averaged over larger areas or longer periods of time. Moreover, rain is patchy in nature - at any instant on the average only a certain fraction of the observed pixels contain rain. The fraction of area covered by rain decreases, as the size of a pixel becomes smaller. This means that within what looks like a patch of rainy area in a coarse resolution view with larger pixel size, one finds clusters of rainy and dry patches when viewed on a finer scale. The model makes definite predictions about how these and other related statistics depend on the pixel size. These predictions were found to agree well with data. In a subsequent second part of the work we plan to test the model with rain gauge data collected during the TRMM (Tropical Rainfall Measuring Mission) ground validation campaign.

Kundu, Prasun K.↗
DOE OSTI2025

Mesoscale Cellular Convection Detection and Classification Using Convolutional Neural Networks: Insights From Long-Term Observations at ARM Eastern North Atlantic Site

Marine boundary layer clouds are crucial in Earth's climate system. They frequently manifest as closed or open cell mesoscale cellular convection (MCC). MCC clouds are challenging to represent accurately in current climate models, highlighting the need for detailed observational data sets and in-depth analyses. This study utilizes over 8 years of observations from the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) User Facility Eastern North Atlantic (ENA) site at Graciosa Island, Azores, to investigate these clouds. We first apply a convolutional neural network with a U-Net architecture to classify open and closed cells, marking the first application of such an approach for automatically detecting MCC patterns from ground-based radar measurements. This method addresses some observational gaps in satellite data related to low temporal resolution, nighttime challenges, and limited vertical structure capture. The analysis of the MCC cases shows clear differences between closed and open MCCs: Closed MCC clouds are characterized by lower cloud tops and bases, shallower cloud geometrical depth, weaker horizontal wind speeds, stronger atmospheric stability, and a more homogeneous liquid water path than open MCCs. Finally, we demonstrate two potential applications of our radar-based MCC classifications: (a) facilitating the investigation of aerosol-cloud interactions and (b) exploring meteorological factors along with MCC's evolution by integrating satellite imagery and back-trajectory analysis. The identified MCC cases offer a valuable resource for the scientific community to study MCC processes further and improve climate model accuracy.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1973

Venus - Radar determination of gravity potential.

We describe a method for the determination of the gravity potential of Venus from multiple-frequency radar measurements. The method is based on the strong frequency dependence of the absorption of radio waves in Venus' atmosphere. Comparison of the differing radar reflection intensities at several frequencies yields the height of the surface relative to a reference pressure contour; combination with measurements of round-trip echo delays allows the pressure, and hence the gravity potential contour, to be mapped relative to the mean planet radius. Since calibration data from other frequencies are unavailable, the absorption-sensitive Haystack Observatory data have been analyzed under the assumption of uniform surface reflectivity to yield a gravity equipotential contour for the equatorial region and a tentative upper bound of .0006 on the fractional difference of Venus' principal equatorial moments of inertia.

Shapiro, I. I.↗
NASA NTRS2007

Proceedings of the 20th International Symposium on Space Flight Dynamics

Topics include: Measuring Image Navigation and Registration Performance at the 3-Sigma Level Using Platinum Quality Landmarks; Flight Dynamics Performances of the MetOp A Satellite during the First Months of Operations; Visual Navigation - SARE Mission; Determining a Method of Enabling and Disabling the Integral Torque in the SDO Science and Inertial Mode Controllers; Guaranteeing Pointing Performance of the SDO Sun-Pointing Controllers in Light of Nonlinear Effects; SDO Delta H Mode Design and Analysis; Observing Mode Attitude Controller for the Lunar Reconnaissance Orbiter; Broken-Plane Maneuver Applications for Earth to Mars Trajectories; ExoMars Mission Analysis and Design - Launch, Cruise and Arrival Analyses; Mars Reconnaissance Orbiter Aerobraking Daily Operations and Collision Avoidance; Mars Reconnaissance Orbiter Interplanetary Cruise Navigation; Motion Parameters Determination of the SC and Phobos in the Project Phobos-Grunt; GRAS NRT Precise Orbit Determination: Operational Experience; Orbit Determination of LEO Satellites for a Single Pass through a Radar: Comparison of Methods; Orbit Determination System for Low Earth Orbit Satellites; Precise Orbit Determination for ALOS; Anti-Collision Function Design and Performances of the CNES Formation Flying Experiment on the PRISMA Mission; CNES Approaching Guidance Experiment within FFIORD; Maneuver Recovery Analysis for the Magnetospheric Multiscale Mission; SIMBOL-X: A Formation Flying Mission on HEO for Exploring the Universe; Spaceborne Autonomous and Ground Based Relative Orbit Control for the TerraSAR-X/TanDEM-X Formation; First In-Orbit Experience of TerraSAR-X Flight Dynamics Operations; Automated Target Planning for FUSE Using the SOVA Algorithm; Space Technology 5 Post-Launch Ground Attitude Estimation Experience; Standardizing Navigation Data: A Status Update; and A Study into the Method of Precise Orbit Determination of a HEO Orbiter by GPS and Accelerometer.

Woodard, Mark↗
NASA NTRS2012

Using Polarimetric SAR Data to Infer Soil Moisture from Surfaces with Varying Subsurface Moisture Profiles

A time-series approach is used to estimate the moisture content-based on polarimetric SAR data. It is found that under the assumption of constant soil moisture, empirically observed relationships between radar backscatter and moisture are only half as sensitive to moisture as compared to actual radar data. A numerical finite element method is used to calculate the radar backscatter for rough soils with arbitrarily varying soil moisture as a function of depth. Several instance of drying and wetting moisture profiles are considered and the radar backscatter is calculated in each case. Radar backscatter is found to crucially depend on the soil moisture variation in the top half wavelength of soil.

subsurface sensing↗
NASA NTRS2012

Momentum Flux Determination Using the Multi-beam Poker Flat Incoherent Scatter Radar

In this paper, we develop an estimator for the vertical flux of horizontal momentum with arbitrary beam pointing, applicable to the case of arbitrary but fixed beam pointing with systems such as the Poker Flat Incoherent Scatter Radar (PFISR). This method uses information from all available beams to resolve the variances of the wind field in addition to the vertical flux of both meridional and zonal momentum, targeted for high-frequency wave motions. The estimator utilises the full covariance of the distributed measurements, which provides a significant reduction in errors over the direct extension of previously developed techniques and allows for the calculation of an error covariance matrix of the estimated quantities. We find that for the PFISR experiment, we can construct an unbiased and robust estimator of the momentum flux if sufficient and proper beam orientations are chosen, which can in the future be optimized for the expected frequency distribution of momentum-containing scales. However, there is a potential trade-off between biases and standard errors introduced with the new approach, which must be taken into account when assessing the momentum fluxes. We apply the estimator to PFISR measurements on 23 April 2008 and 21 December 2007, from 60-85 km altitude, and show expected results as compared to mean winds and in relation to the measured vertical velocity variances.

Momentum flux↗
NASA NTRS1976

Surface slope probabilities from the spectra of weak radar echoes - Application to Mars

A method is described for stabilizing the inversion of the power spectra of comparatively weak radar echoes from Mars. It is noted that such stabilization is necessary for echoes with S/N power-spectral densities of order unity as well as for those with broad spectral distributions. The method is applied to the Martian surface, using two data sets obtained with radars of approximately 12.5-cm wavelength. The resulting slope probabilities are interpreted in terms of diffuse and quasi-specular scatter, and values of rms slope are calculated. The results for a sample of Martian locations clearly indicate extreme variations in the local nature of the surface and yield evidence for an apparent planetwide distribution of roughness that may be due to extreme slopes, surface or subsurface rock populations, or a combination of these.

Lipa, B.↗
NASA NTRS2017

A Method for Estimating Meteorite Fall Mass from Weather Radar Data

Techniques such as weather RADAR, seismometers, and all-sky cameras allow new insights concerning the physics of meteorite fall dynamics and fragmentation during "dark flight", the period of time between the end of the meteor's luminous flight and the concluding impact on the Earth's surface. Understanding dark flight dynamics enables us to rapidly analyze the characteristics of new meteorite falls. This analysis will provide essential information to meteorite hunters to optimize recovery, increasing the frequency and total mass of scientifically important freshly-fallen meteorites available to the scientific community. We have developed a mathematical method to estimate meteorite fall mass using reflectivity data as recorded by National Oceanic and Atmospheric Administration (NOAA) Next Generation RADAR (NEXRAD) stations. This study analyzed eleven official and one unofficial meteorite falls in the United States and Canada to achieve this purpose.

Laird, C.↗
DOE OSTI2020

The Heavy Rainfall Mechanism Revealed by a Terrain-Resolving 4DVar Data Assimilation System—A Case Study

In this study, a newly developed terrain-resolving four-dimensional variational (4DVar)-based data assimilation system, Immersed Boundary Method_Variational Doppler Radar Analysis System (IBM_VDRAS), is applied to investigate the mechanisms leading to a heavy precipitation event that occurred in Taiwan during the Southwesterly Monsoon Experiment (SoWMEX) conducted in 2008. The multivariate analyses using IBM_VDRAS and surface observations reveal that the warm and moist southwesterly flow from the ocean decelerates after making landfall, forming a surface convergence zone along the coast, which is further strengthened during the passage of a prefrontal rainband. The flow ascends as it advances inland until reaching the mountains, producing persistent precipitation and the enhancement of evaporative cooling as well as a widespread high pressure zone. A very shallow (<0.4 km) layer of offshore flow can be identified over the southwestern plain, which helps to generate a quasi-stationary convergence zone near the coast. Furthermore, sensitivity studies are carried out to quantify the relative importance of the contributions made by topographic blockage, evaporative cooling, and their nonlinear interaction, to the evolution of this type of convective system. The influence of the topography is identified as the dominant factor in modulating the flow structure of the rainfall system. However, it is the nonlinear interaction between terrain and evaporation that determines the distribution of the temperature and pressure fields.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Cross Validation of the Network of Ground-Based Radar with GPM during the Remote Sensing of Electrification, Lightning, And Mesoscale/Microscale Processes with Adaptive Ground Observations (RELAMPAGO) Field Campaign

The cross-validation of radars in a network is important in making consistent retrievals across the domain and assuring the product quality. During the RELAMPAGO field campaign, two C-band radars, namely the Colorado State University C-band Hydrological Instrument for Volumetric Observations ( CSU-CHIVO) and the C-band Scanning ARM Precipitation Radar (CSAPR-2), were deployed near the Sierras de Cordoba in Argentina, a region known for having some of the most intense severe weather in the world. In addition to these two radars, the operational radar of the Cordoba City, the Radar Meteorologico Argentino 1 (RMA-1), adds another instrument to the RELAMPAGO network. This study presents an intercomparison between the RELAMPAGO C-band radars using the GPM spaceborne radar as a common reference ..A method to bring ground-based radars into better agreement is also proposed. Moreover, the attenuation correction for the C-band radar is studied in the context of intercomparing two radars. The attenuation coefficients are computed for the RELAMPAGO domain using the local disdrometers deployed. during the campaign. After the attenuation correction, CSU-CHIVO, CSAPR-2, and RMA-1 compare well with GPM-DPR with a high correlation and bias less than 1 dB.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1970

Phenomenological approach to scatterometer data interpretation

A graphic method of analyzing radar scatterometer sea clutter data leading to linear relations between scattering cross sections and tan angle of incidence of the radiation is proposed. This relation permits formulation of simple analytic relations without reference to the ocean surface spectrum. Parameters introduced depend on the wavelength of the incident radiation and its polarization, and on wind and sea states. The simplicity of the expressions derived suggests a corresponding simplicity in the physical mechanism of radar sea clutter return.

Alzofon, F. E.↗