Search NASA⌕ Search

SEARCH · Search NASA

Results for “RADAR method”

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 811 records · Page 45

Calibration of a polarimetric imaging SAR

Calibration of polarimetric imaging Synthetic Aperture Radars (SAR's) using point calibration targets is discussed. The four-port network calibration technique is used to describe the radar error model. The polarimetric ambiguity function of the SAR is then found using a single point target, namely a trihedral corner reflector. Based on this, an estimate for the backscattering coefficient of the terrain is found by a deconvolution process. A radar image taken by the JPL Airborne SAR (AIRSAR) is used for verification of the deconvolution calibration method. The calibrated responses of point targets in the image are compared both with theory and the POLCAL technique. Also, response of a distributed target are compared using the deconvolution and POLCAL techniques.

Sarabandi, K.↗

Calibration of a polarimetric imaging SAR

Calibration of polarimetric imaging Synthetic Aperture Radars (SAR's) using point calibration targets is discussed. The four-port network calibration techniques is used to describe the radar error model. The polarimetric ambiguity function of the SAR is then found using a single point target, namely a trihedral corner reflector. Based on this, an estimate for the backscattering coefficient of the terrain is found by a deconvolution process. A radar image taken by the JPL Airborne SAR (AIRSAR) is used for verification of the deconvolution calibration method. The calibrated responses of point targets in the image are compared both with theory and the POLCAL technique. Also, response of a distributed target are compared using the deconvolution and POLCAL techniques.

Sarabandi, Kamal↗

Electromagnetic Scattering from Realistic Targets

The general goal of the project is to develop computational tools for calculating radar signature of realistic targets. A hybrid technique that combines the shooting-and-bouncing-ray (SBR) method and the finite-element method (FEM) for the radiation characterization of microstrip patch antennas in a complex geometry was developed. In addition, a hybridization procedure to combine moment method (MoM) solution and the SBR method to treat the scattering of waveguide slot arrays on an aircraft was developed. A list of journal articles and conference papers is included.

Lee, Shung- Wu↗

Characterizing the Space Debris Environment with a Variety of SSA Sensors

Damaging space debris spans a wide range of sizes and altitudes. Therefore no single method or sensor can fully characterize the space debris environment. Space debris researchers use a variety of radars and optical telescopes to characterize the space debris environment in terms of number, altitude, and inclination distributions. Some sensors, such as phased array radars, are designed to search a large volume of the sky and can be instrumental in detecting new breakups and cataloging and precise tracking of relatively large debris. For smaller debris sizes more sensitivity is needed which can be provided, in part, by large antenna gains. Larger antenna gains, however, produce smaller fields of view. Statistical measurements of the debris environment with less precise orbital parameters result. At higher altitudes, optical telescopes become the more sensitive instrument and present their own measurement difficulties. Space Situational Awareness, or SSA, is concerned with more than the number and orbits of satellites. SSA also seeks to understand such parameters as the function, shape, and composition of operational satellites. Similarly, debris researchers are seeking to characterize similar parameters for space debris to improve our knowledge of the risks debris poses to operational satellites as well as determine sources of debris for future mitigation. This paper will discuss different sensor and sensor types and the role that each plays in fully characterizing the space debris environment.

Stansbery, Eugene G.↗

Using the Hottest Particles in the Universe to Probe Icy Solar System Worlds

We present results of our Phase 1 NIAC Study to determine the feasibility of developing a competitive, low cost, low power, low mass passive instrument to measure ice depth on outer planet ice moons, such as Europa, Ganymede, Callisto, and Enceladus. Indirect measurements indicate that liquid water oceans are likely present beneath the icy shells of such moons (see e.g.,the JPL press release "The Solar System and Beyond is Awash in Water"), which has important astrobiological implications. Determining the thickness of these ice shells is challenging given spacecraft SWaP (Size, Weight and Power) resources. The current approach uses a suite of instruments, including a high power, massive ice penetrating radar. The instrument under study, called PRIDE (Passive Radio Ice Depth Experiment) exploits a remarkable confluence between methods from the high energy particle physics and the search for extraterrestrial life within the solar system. PRIDE is a passive receiver of a naturally occurring radio frequency (RF) signal generated by interactions of deep penetrating Extremely High Energy (> 10^18 eV) cosmic ray neutrinos. It could measure ice thickness directly, and at a significant savings to spacecraft resources. At RF frequencies the transparency of modeled Europan ice is up to many km, so an RF sensor in orbit can observe neutrino interactions to great depths, and thereby probe the thickness of the ice layer.

Exploration↗

Storm Chasing from Space: Detecting severe weather phenomena from satellite platforms

Severe weather is an awe-inspiring phenomenon that affects the entire globe. Lightning, hail, damaging wind and tornadoes pose threats to society and challenges to the scientific community. Severe weather is annually responsible for tens of billions of dollars in insured losses to property, infrastructure, and agriculture. Satellite platforms offer a globally uniform approach to observing weather phenomena in remote or data-sparse regions and over the oceans. Severe convection exhibits distinct signatures in spaceborne datasets that we use to analyze severe storms. We leverage these signatures create climatologies, improve prediction, and provide a method of detection around the globe where traditional ground-based data (such as ground-based radar or human-spotter reports) are inconsistent or unavailable. Satellites in low-earth, sun-synchronous, and geostationary orbit provide a consistent, global view of severe weather from which we can examine the current global distribution, frequency, and severity of severe storms and establish a baseline to assess their future trend in a changing Earth system.

Sarah D. Bang↗

Storm Chasing from Space: Detecting Severe Weather Phenomena from Satellite Platforms

Severe weather is an awe-inspiring phenomenon that affects the entire globe. Lightning, hail, damaging wind and tornadoes pose threats to society and challenges to the scientific community. Severe weather is annually responsible for tens of billions of dollars in insured losses to property, infrastructure, and agriculture. Satellite platforms offer a globally uniform approach to observing weather phenomena in remote or data-sparse regions and over the oceans. Severe convection exhibits distinct signatures in spaceborne datasets that we use to analyze severe storms. We leverage these signatures create climatologies, improve prediction, and provide a method of detection around the globe where traditional ground-based data (such as ground-based radar or human-spotter reports) are inconsistent or unavailable. Satellites in low-earth, sun-synchronous, and geostationary orbit provide a consistent, global view of severe weather from which we can examine the current global distribution, frequency, and severity of severe storms and establish a baseline to assess their future trend in a changing Earth system.

Sarah D Bang↗

Target Tracking with Distributed Sensing and Optimal Data Migration

The paper presents an Extended Kalman Filter based framework for airborne target tracking using adaptive information fusion from multi-modal multi-rate distributed sensors network. First, the tracking algorithm execution location is determined using an optimal data migration strategy, which also computes the associated delays for each sensor data to arrive at the computing location. Next, the fast (zero-delay) sensors information is dynamically fused in the filter correction procedure at the arrival instance of each valid sensor reading. Finally, the target estimation is updated based on the valid slow (delayed) data, which are grouped according to the delay-time steps before application of the Larsen's method. This approach is applied to the synthetic sensor data generated by means of the ground based radar and camera models for the simulated target flight in Reflection simulation environment.

Distributed sensing↗

Target Tracking with Distributed Sensing and Optimal Data Migration

The paper presents an Extended Kalman Filter based framework for airborne target tracking using adaptive information fusion from multi-modal multi-rate distributed sensors network. First, the tracking algorithm execution location is determined using an optimal data migration strategy, which also computes the associated delays for each sensor data to arrive at the computing location. Next, the fast (zero-delay) sensors information is dynamically fused in the filter correction procedure at the arrival instance of each valid sensor reading. Finally, the target estimation is updated based on the valid slow (delayed) data, which are grouped according to the delay-time steps before application of the Larsen's method. This approach is applied to the synthetic sensor data generated by means of the ground based radar and camera models for the simulated target flight in Reflection simulation environment.

Distributed sensing↗

Clutter identification based on kernel density estimation and sparse recovery

A cognitive radar framework is being developed to dynamically detect changes in the clutter characteristics, and to adapt to these changes by identifying the new clutter distribution. In our previous work, we have presented a sparse-recovery based clutter identification technique. In this technique, each column of the dictionary represents a specific distribution. More specifically, calibration radar clutter data corresponding to a specific distribution is transformed into a distribution through kernel density estimation. When the new batch of radar data arrives, the new data is transformed to a distribution through the same kernel density estimation method and its distribution characteristics is identified through sparse-recovery. In this paper, we extend our previous work to consider different kernels and kernel parameters for sparse-recovery-based clutter identification and the numerical results are presented as well. The impact of different kernels and kernel parameters are analyzed by comparing the identification accuracy of each scenario.

Wang, Haokun↗

Quantifying and Understanding Effects from Wildlife, Radar, and Public Engagement on Future Wind Deployment

This presentation provides an overview of findings from a report published in 2016 by researchers at the National Renewable Energy Laboratory, An Initial Evaluation of Siting Considerations on Current and Future Wind Deployment. The presentation covers the background for research, the Energy Department's Wind Vision, research methods, siting considerations, the wind project deployment process, and costs associated with siting considerations.

17 WIND ENERGY↗

Radar image processing for rock-type discrimination

Image processing and enhancement techniques for improving the geologic utility of digital satellite radar images are reviewed. Preprocessing techniques such as mean and variance correction on a range or azimuth line by line basis to provide uniformly illuminated swaths, median value filtering for four-look imagery to eliminate speckle, and geometric rectification using a priori elevation data. Examples are presented of application of preprocessing methods to Seasat and Landsat data, and Seasat SAR imagery was coregistered with Landsat imagery to form composite scenes. A polynomial was developed to distort the radar picture to fit the Landsat image of a 90 x 90 km sq grid, using Landsat color ratios with Seasat intensities. Subsequent linear discrimination analysis was employed to discriminate rock types from known areas. Seasat additions to the Landsat data improved rock identification by 7%.

Blom, R. G.↗

Digital processing of orbital radar data to enhance geologic structure - Examples from the Canadian Shield

Various digital enhancement techniques for SAR are compared using SIR-B and Seasat images of the Canadian Shield. The three best methods for enhancing geological structure were found to be: (1) a simple linear contrast stretch; (2) a mean or median low-pass filter to reduce speckle prior to edge enhancement or a K nearest-neighbor average to cosmetically reduce speckle; and (3) a modification of the Moore-Waltz (1983) technique. Three look directions were coregistered and several means of data display were investigated as means of compensating for radar azimuth biasing.

Masuoka, Penny M.↗

Precipitation measurements from space - Workshop summary 28 April-1 May 1981, Greenbelt, MD

The goals and methods for global precipitation measurements from space are examined. Records currently exist only for visible and IR scans of cloud properties, and are applied from GEO for detecting diurnal variations in precipitation. Microwave radiometry is noted to be a suitable method for supplementing the visible and IR data for measuring stratiform oceanic precipitation, and when used at up to 3 microns can detect areas, if not amounts, of precipitation from GEO. Applications of radar altimeters are proposed in terms of modifications to the Seasat-type 2.2 cm radar, the use of surface target attentuation radar, of frequency agile rain radar, or of adaptive pointing radar. Soil moisture sensing is available with passive microwave radiometry in the 20-50 cm bands, or active sensing in the 5-8 cm bands. The utilization of GARP ground truth data is explored, along with statistical methods for treating the data samples.

Atlas, D.↗

Phi-s correlation and dynamic time warping - Two methods for tracking ice floes in SAR images

The authors present two algorithms for performing shape matching on ice floe boundaries in SAR (synthetic aperture radar) images. These algorithms quickly produce a set of ice motion and rotation vectors that can be used to guide a pixel value correlator. The algorithms match a shape descriptor known as the Phi-s curve. The first algorithm uses normalized correlation to match the Phi-s curves, while the second uses dynamic programming to compute an elastic match that better accommodates ice floe deformation. Some empirical data on the performance of the algorithms on Seasat SAR images are presented.

Mcconnell, Ross↗

NASADEM Global Elevation Model: Methods and Progress

NASADEM (NASA Digital Elevation Model) is a near-global elevation model that is being produced primarily by completely reprocessing the Shuttle Radar Topography Mission (SRTM) radar data and then merging it with refined ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) GDEM (Global Digital Elevation Model) elevations. The new and improved SRTM elevations in NASADEM result from better vertical control of each SRTM data swath via reference to ICESat (Ice, Cloud, and land Elevation Satellite) elevations and from SRTM void reductions using advanced interferometric unwrapping algorithms. Remnant voids will be filled primarily by GDEM3, but with reduction of GDEM glitches (mostly related to clouds) and therefore with only minor need for secondary sources of fill.

GDEM↗

Phase calibration of polarimetric radar images

The problem of phase calibration between polarization channels of an imaging radar is studied. The causes of various types of phase errors due to the radar system architecture and system imperfections are examined. A simple model is introduced to explain the spatial variation in phase error as being due to a displacement between the phase centers of the vertical and horizontal antennas. It is also shown that channel leakage can cause a spatial variation in phase error. Phase calibration using both point and distributed ground targets is discussed and a method for calibrating phase using only distributed target is verified, subject to certain constraints. Experimental measurements using the NADC/ERIM P-3 synthetic-aperture radar (SAR) system and NASA/JPL DC-8 SAR, which operates at C-, L-, and P-bands, are presented. Both of these systems are multifrequency, polarimetric, airborne, SAR systems.

Sheen, Dan R.↗

An Orbital Meteoroid Stream Survey Using the Southern Argentina Agile Meteor Radar (SAAMER) Based on a Wavelet Approach

Over a million individually measured meteoroid orbits were collected with the Southern Argentina Agile MEteor Radar (SAAMER) between 2012-2015. This provides a robust statistical database to perform an initial orbital survey of meteor showers in the Southern Hemisphere via the application of a 3D wavelet transform. The method results in a composite year from all 4 years of data, enabling us to obtain an undisturbed year of meteor activity with more than one thousand meteors per day. Our automated meteor shower search methodology identified 58 showers. Of these showers, 24 were associated with previously reported showers from the IAU catalogue while 34 showers are new and not listed in the catalogue. Our searching method combined with our large data sample provides unprecedented accuracy in measuring meteor shower activity and description of shower characteristics in the Southern Hemisphere. Using simple modeling and clustering methods we also propose potential parent bodies for the newly discovered showers.

Meteor showers↗