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Recent progress towards a synthetic aperture radar (SAR) based system for determining forest ecosystem attributes is discussed. Our SAR data processing and analysis sequence, from calibration through classification, is described. In addition, the usefulness of SAR image data for identifying ecosystem classes is discussed.
This paper examines the mass storage systems that are currently in place at the Alaska SAR Facility (SAF). The architecture of the facility will be presented including specifications of the mass storage media that are currently used and the performances that we have realized from the various media. The distribution formats and media are also discussed. Because the facility is expected to service future sensors, the new requirements and possible solutions to these requirements are also discussed.
This paper examines the mass storage systems that are currently in place at the Alaska SAR facility (ASF). The architecture of the facility will be presented including specifications of the mass storage media that are currently used and the performances that we have realized from the various media. The distribution formats and media will also to be discussed. Because the facility is expected to survice future sensors, the new requriements and possible solutions to these requriements will also be discussed.
A post-processing system was developed to georeference and geocode airborne synthetic aperture radar (SAR) data collected by the JPL-Airborne SAR (AIRSAR) System over hilly terrain during the 1990 MAESTRO1 campaign. Georectification relates image coordinates and object coordinates while the geocoding involves resampling. The georectification method uses a hybrid method based upon a number of navigational parameters and minimal two ground-control points which are referenced in both image and map space. The calculation of the intersection of the SAR signal wavefront and a digital elevation model allowed, within certain error bounds, acquisition of the object-to-image and image-to-object relationships.
This paper summarizes the investigation of SAR image data compression for an on-line archive data distribution system. This system is planned for the ground processing system of Alaska SAR Facility (ASF) and Shuttle Imaging Radar (SIR-C). The objective of the SAR image data compression is to enable the data archive system to provide the remote users a large data base with good image quality, short response time, low transfer cost, and minimal decoding complexity. The requirements and limitations of the on-line archive data distribution system are presented. The effects of SAR image data characteristics on data compression are addressed. The users' survey results suggest that compression ratios between 10:1 and 20:1 appear suitable. Based on the algorithm evaluation results, the two-level tree-searched vector quantization technique has been recommended as the SAR image data compression algorithm for the on-line archive data distribution system.
The Shuttle Imaging Radar-C and X-Band Synthetic Aperture Radar (SIR-C/X-SAR) is a cooperative experiment between the National Aeronautics and Space Administration (NASA), the German Space Agency (DARA), and the Italian Space Agency (ASI). The experiment is the next evolutionary step in NASA's Spaceborne Imaging Radar (SIR) program that began with the Seasat SAR in 1978, and continued with SAR -A in 1981 and SAR-B in 1984. The program will eventually lead to the Earth Observing System (EOS) SAR later in this decade. SIR-C will provide increased capability over Seasat, SIR-A, and SIR-B by acquiring polarimetric images simultaneously at two microwave frequencies: L-band (wavelength 24 cm) and C-band (wavelength 6 cm). X-SAR will operate at X-band (wavelength 3 cm) with VV polarization, resulting in a three-frequency capability. Because radar backscatter is most strongly influenced by objects comparable in size to the radar wavelength, this multifrequency capability will provide information about the Earth's surface over a wide range of scales not discernable with single-frequency experiments. The polarimetric data will yield quantitative information about the surface geometric structure, vegetation dielectric properties, and surface discontinuities. The first SIR-C/X-SAR flight is planned for early in 1994, with two subsequent flights in different seasons to enable data aquisition under different environmental conditions. SIR-C/X-SAR will collect data for a period of 6 to 9 days during each flight. The instrument will be flown in a 57(deg) inclination orbit with a nomimal orbit altitude of 215 km. This altitude will result in a slightly drifting orbit. The latest status of the SIR-C/X-SAR mission and instrument design, science activities, and expected results will be presented.
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Two simple scattering mechanisms are fitted to polarimetric synthetic aperture radar (SAR) observations of forests. The mechanisms are canopy scatter from a reciprocal medium with azimuthal symmetry and a ground scatter term that can represent double-bounce scatter from a pair of orthogonal surfaces with different dielectric constants or Bragg scatter from a moderately rough surface, which is seen through a layer of vertically oriented scatterers. The model is shown to represent the behavior of polarimetric backscatter from a tropical forest and two temperate forest sites by applying it to data from the National Aeronautic and Space Agency/Jet Propulsion Laboratory's Airborne SAR (AIRSAR) system. Scattering contributions from the two basic scattering mechanisms are estimated for clusters of pixels in polarimetric SAR images. The solution involves the estimation of four parameters from four separate equations. This model fit approach is justified as a simplification of more complicated scattering models, which require many inputs to solve the forward scattering problem. The model is used to develop an understanding of the ground-trunk double-bounce scattering that is present in the data, which is seen to vary considerably as a function of incidence angle. Two parameters in the model fit appear to exhibit sensitivity to vegetation canopy structure, which is worth further exploration. Results from the model fit for the ground scattering term are compared with estimates from a forward model and shown to be in good agreement. The behavior of the scattering from the ground-trunk interaction is consistent with the presence of a pseudo-Brewster angle effect for the air-trunk scattering interface. If the Brewster angle is known, it is possible to directly estimate the real part of the dielectric constant of the trunks, a key variable in forward modeling of backscatter from forests. It is also shown how, with a priori knowledge of the forest height, an estimate for the attenuation coefficient of the canopy can be obtained directly from the multi-incidence-angle polarimetric observations. This attenuation coefficient is another key variable in forward models and is generally related to the canopy density.
In this work, we present a supercomputer-driven pipeline for in silico drug discovery using enhanced sampling molecular dynamics (MD) and ensemble docking. Ensemble docking makes use of MD results by docking compound databases into representative protein binding-site conformations, thus taking into account the dynamic properties of the binding sites. We also describe preliminary results obtained for 24 systems involving eight proteins of the proteome of SARS-CoV-2. The MD involves temperature replica exchange enhanced sampling, making use of massively parallel supercomputing to quickly sample the configurational space of protein drug targets. Using the Summit supercomputer at the Oak Ridge National Laboratory, more than 1 ms of enhanced sampling MD can be generated per day. We have ensemble docked repurposing databases to 10 configurations of each of the 24 SARS-CoV-2 systems using AutoDock Vina. Comparison to experiment demonstrates remarkably high hit rates for the top scoring tranches of compounds identified by our ensemble approach. We also demonstrate that, using Autodock-GPU on Summit, it is possible to perform exhaustive docking of one billion compounds in under 24 h. Finally, we discuss preliminary results and planned improvements to the pipeline, including the use of quantum mechanical (QM), machine learning, and artificial intelligence (AI) methods to cluster MD trajectories and rescore docking poses.
The SAR (synthetic-aperture radar) data-processing algorithm to be used for the Magellan mission is described. Radar system design, SAR data characteristics, and hardware (H/W) constraints, which are critical to the processing algorithm design, are highlighted. Data flow and the H/W architecture are given to show the real-time data processing capability. Simulation results obtained from processing the synthetic point-target echos are presented to demonstrate the performance of the processing algorithm.
The EOS SAR mission under consideration as one element of the mission to planet earth, which will provide a long duration radar observing system with multipolarization and multifrequency capability, is presented. The payload consists of three synthetic aperture radar systems; a C-band radar with dual polarization, an L-band radar with quadruple polarization, and an X-band radar with dual polarization. Each radar system will be of the phased-array type, will have variable resolutions and swath widths and will be capable of steering the beam electronically in elevation.
The authors describe the evolution of the spaceborne imaging radar starting with the Seasat SAR, through the SIR-A, SIR-B, and SIR-C/X-SAR missions, to the Earth Observing System (EOS) SAR which is scheduled for launch as part of EOS in the late 1990s. A summary of the planned international missions, which may produce a permanent active microwave capability in space starting as early as 1991, is also presented, along with a description of the airborne systems which will be essential to the algorithm development and long-term calibration of the spaceborne data. A brief summary of the planetary missions utilizing SAR and a comparison of their imaging capabilities with those available on Earth are presented.
The Alaska Synthetic Aperture Radar (SAR) Facility Mission Planning Subsystem is an interactive mission planning software system on the VAXStation 2000. This system has the capability to generate satellite ephemerides and mission parameters related to synthetic aperture radar missions. The mission data can be viewed as overlays on the world map in various projections and zooms. The system also provides schedule planning capabilities, using the INGRES DBMS to keep track of the various plans and schedules generated by the mission planner.
In this paper we will briefly describe the instrument characteristics, the evolution of various radar modes, the instrument performance and improvement in the knowledge of the positioning and attitude information of the NASA/JPL airborne synthetic aperture radar (SAR). This system operates in the fully polarimetric mode in the P, L, and C band simultaneously or in the interferometric mode in both the L and C band simultaneously. We also summarize the progress of the data processing effort, especially in the interferometry processing and we address the issue of processing and calibrating the cross-track interferometry data.
This paper examines the JPL/Caltech parallel processing system designed for rapid processing and transfer of large quantities of data from remote sensing instruments flown on NASA missions. Two remote sensing analysis applications that use this processing system are described: (1) an analysis system for retrieval of atmospheric parameters (such as species abundance, atmospheric temperature, and water vapor profiles) from data obtained by a Fourier transform IR spectrometer and (2) a prototype airborne SAR processing system. It is shown that a parallel processing system such as the JPL/Caltech system can offer supercomputer computational capability and high-volume data throughput and still be cost-effective.
The individual sensor system design elements which are the priori components in the registration and rectification process, and the potential impact of error budgets on multitemporal registration and side-lap registration are analyzed. The properties of scanner, MLA, and SAR imaging systems are reviewed. Each sensor displays internal distortion properties which to varying degrees make it difficult to generate on orthophoto projection of the data acceptable for multiple pass registration or meeting national map accuracy standards and is also affected to varying degrees by relief displacements in moderate to hilly terrain. Nonsensor related distortions, associated with the accuracy of ephemeris determination and platform stability, have a major impact on local geometric distortions. Platform stability improvements expected from the new multi mission spacecraft series and improved ephemeris and ground control point determination from the NAVSTAR/global positioning satellite systems are reviewed.
The processing of synthetic aperture radar (SAR) signals using the massively parallel processor (MPP) is discussed. The fast Fourier transform convolution procedures employed in the algorithms are described. The MPP architecture comprises an array unit (ARU) which processes arrays of data; an array control unit which controls the operation of the ARU and performs scalar arithmetic; a program and data management unit which controls the flow of data; and a unique staging memory (SM) which buffers and permutes data. The ARU contains a 128 by 128 array of bit-serial processing elements (PE). Two-by-four surarrays of PE's are packaged in a custom VLSI HCMOS chip. The staging memory is a large multidimensional-access memory which buffers and permutes data flowing with the system. Efficient SAR processing is achieved via ARU communication paths and SM data manipulation. Real time processing capability can be realized via a multiple ARU, multiple SM configuration.
A real-time high-performance and fault-tolerant FPGA-based hardware architecture for the processing of synthetic aperture radar (SAR) images has been developed for advanced spaceborne radar imaging systems. In this paper, we present the integrated design approach, from top-level algorithm specifications, system architectures, design methodology, functional verification, performance validation, down to hardware design and implementation.