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Improved technique for aiming antenna of synthetic-aperture radar (SAR) operating in squint imaging mode (SIM) complements improved algorithm for processing raw SIM SAR data. Developed to reduce deleterious effects of two unique characteristics of SIM SAR: large range walk and large variation of Doppler centroid as function of range.
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.
Previous studies of synthetic aperture radar (SAR) imagery have shown qualitative relationships between radar backscatter and soil moisture. However, to be able to use these data in operational programs it will be necessary to establish quantitatively how the radar return is related to soil moisture and the effects of surface roughness, soil type, and vegetation cover and growth stage, as a function of frequency and polarization. To this end, a multi-year experiment began in 1990 as a cooperative venture amongst the Canada Center (Agriculture Canada), and the Universities of Guelph, Sherbrooke, Laval, and Waterloo. During 1990, SAR imagery was acquired during two periods (May and Jun.) to correspond to times of minimal and substantial vegetation cover. SAR data were acquired on three days in May and on four days in Jul. to cover different soil moisture conditions. This unique comprehensive data set is used to investigate the relationships between soil moisture and radar backscatter. The experiment and data collected are described, and a preliminary qualitative interpretation of the relationship between soil moisture and image tone is provided.
Multifrequency polarimetric synthetic aperture radar (SAR) images of the Walnut Gulch watershed near Tombstone, Arizona were acquired on 28 Mar. 1990 and on 1 Aug. 1990. Trihedral corner reflectors were deployed prior to both overflights to allow calibration of the two SAR data sets. During both overflights, gravimetric soil moisture and dielectric constant measurements were made. Detailed vegetation height, density, and water content measurements were made as part of the Monsoon 1990 Experiment. Preliminary results based on analysis of the multitemporal polarimetric SAR data are presented. Only the C-band data (5.7-cm wavelength) radar images show significant difference between Mar. and Aug., with the strongest difference observed in the HV images. Based on the radar data analysis and the in situ measurements, we conclude that these differences are mainly due to changes in the vegetation and not due to the soil moisture changes.
Results from the 1989 Airborne Synthetic Aperture Radar (SAR) Calibration Campaign at the DLR test site in Oberpfaffenhofen are presented. Passive corner reflectors were used to derive the receiver and transmitter distortion matrices and the absolute calibration factor of the multispectral polarimetric DC-8 SAR from the complex high resolution data. A basic requirement for cross-calibration of data from different tracks is the stability of the SAR system. The polarimetric properties of the uncalibrated data were used to describe this stability. Quality criteria for a successful polarimetric calibration were provided by the channel balance and cross-talk parameters.
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.
The paper describes the architecture of the Alaska SAR Facility (ASF) at Fairbanks, being developed to generate science data products for supporting research in sea ice motion, ice classification, sea-ice-ocean interaction, glacier behavior, ocean waves, and hydrological and geological study areas. Special attention is given to the individual substructures of the ASF: the Receiving Ground Station (RGS), the SAR Processor System, and the Interactive Image Analysis System. The SAR data will be linked to the RGS by the ESA ERS-1 and ERS-2, the Japanese ERS-1, and the Canadian Radarsat.
The SAR employed by NASA's Earth Observing System (EOS) is a multifrequency multipolarization radar which can conduct global monitoring of geophysical and biophysical parameters. The present discussion of the EOS SAR's role in global monitoring emphasizes geophysical product variables applicable to global hydrologic, biogeochemical, and energy cycle models. EOS SAR products encompass biomass, wetland areas, and phenologic and environmental states, in the field of ecosystem dynamics; soil moisture, snow moisture and extent, and glacier and ice sheet extent and velocity, in hydrologic cycle studies; surface-wave fields and sea ice properties, in ocean/atmosphere circulation; and the topography, erosion, and land forms of the solid earth.
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.
A technique for separating classes of surface roughness and vegetation in semiarid regions using polarimetric synthetic aperture radar (SAR) and Thematic Mapper data is developed. Polarimetric SAR data may be used to separate areas with less than 10 percent vegetation cover where one suite of model inversions may be applicable for derivation of surface roughness. In more vegetated regions, visible/near-infrared data provide a mechanism for determining the relative contribution of vegetation to multiple scattering in the SAR data. Thus, the synergistic use of the two data sets provides a more complete characterization of surface units and cover. This result is critical when trying to monitor dielectric constant variations related to changes in moisture content of soil and vegetation cover in arid to semiarid regions. A strategy for automating a procedure for measurement of surface roughness is proposed.
The Earth Observing System (EOS) synthetic aperture radar (SAR) is a multifrequency, multipolarization radar which will be capable of the global monitoring of key quantitative measurements of geophysical and biophysical parameters. Scheduled to fly on its own dedicated spacecraft, it is one of three platforms that will make up the space-based component to EOS. The role of the SAR in the EOS mission is discussed, wtih emphasis on the geophysical product variables which will be generated with the SAR and used in global hydrologic, biogeochemical and energy cycle models. The latest concepts for processing the data, including calibration and geophysical processing strategies, are presented.
The paper describes a number of improvements in calibration of NASA/JPL DC-8 SAR (synthetic aperture radar) data, intended to make calibrated data from the system available to the majority of the investigators. The improvements include a move to a better site for calibration of the system at the start of each campaign season, the release of software to allow users to calibrate their data, the supply of trihedral corner reflectors and instructions on how to deploy them, and the setting up of an archive of calibrated data. Analysis of the calibration performance of the DC-8 SAR over a number of sites during 1990 suggests that the system is sufficiently stable to allow calibration of the standard data products without the presence of calibration devices within the scene. The limiting factor on DC-8 SAR data calibration would now appear to be the knowledge of the altitude of the aircraft, which determines the relationship between the measured slant range coordinates and the antenna pattern in elevation.
Previous research studies have focused on producing algorithms for extracting geophysical information from passive microwave data regarding ice floe size, sea ice concentration, open water lead locations, and sea ice extent. These studies have resulted in four separate algorithms for extracting these geophysical parameters. Sea ice concentration estimates generated from each of these algorithms (i.e., NASA/Team, NASA/Comiso, AES/York, and Navy) are compared to ice concentration estimates produced from coincident high-resolution synthetic aperture radar (SAR) data. The SAR concentration estimates are produced from data collected in both the Beaufort Sea and the Greenland Sea in March 1988 and March 1989, respectively. The SAR data are coincident to the passive microwave data generated by the Special Sensor Microwave/Imager (SSM/I).
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.
It is well established that interferometric synthetic aperture radar (SAR) images can be inverted to perform surface elevation mapping. Among the factors critical to the mapping accuracy are registration of the interfering SAR images and phase unwrapping. A novel registration algorithm is presented that determines the registration parameters through optimization. A new figure of merit is proposed that evaluates the registration result during the optimization. The phase unwrapping problem is approached through a new method involving fringe line detection. The algorithms are tested with two SEASAT SAR images of terrain near Yellowstone National Park. These images were collected on Seasat orbits 1334 and 1420, which were very close together in space, i.e., less than 100 m. The resultant elevation map is compared with the USGS digital terrain elevation model.
Semiautomated technique intended primarily to facilitate registration of polarimetric synthetic-aperture-radar (SAR) images with other images of same or partly overlapping terrain while preserving polarization information conveyed by SAR data. Technique generally applicable in sense one or both of images to be registered with each other generated by polarimetric or nonpolarimetric SAR, infrared radiometry, conventional photography, or any other applicable sensing method.
Segmentation of multifrequency, multilook synthetic-aperture radar (SAR) image intensity data into regions, within each of which backscattering characteristics of target scene considered homogeneous, enhanced by use of two statistical models. One represents statistics of multifrequency, multilook speckled intensities of SAR picture elements; other represents statistics of labels applied to regions into which picture elements grouped. Each region represents different type of terrain, terrain cover, or other surface; e.g., forest, agricultural land, sea ice, or water. Segmentation of image into regions of neighboring picture elements accomplished by method similar to that described in "Algorithms For Segmentation Of Complex-Amplitude SAR Data" (NPO-18524).
Multifrequency polarimetric synthetic aperture radar (SAR) images of the Walnut Gulch watershed near Tombstone, Arizona were acquired on 28 Mar. 1990 and on 1 Aug. 1990. Trihedral corner reflectors were deployed prior to both overflights to allow calibration of the two SAR data sets. During both overflights, gravimetric soil moisture and dielectric constant measurements were made. Detailed vegetation height, density, and water content measurements were made as part of the Monsoon 1990 Experiment. Preliminary results based on analysis of the multitemporal polarimetric SAR data are presented. Only the C-band data (5.7-cm wavelength) radar images show significant difference between Mar. and Aug., with the strongest difference observed in the HV images. Based on the radar data analysis and the in situ measurements, we conclude that these differences are mainly due to changes in the vegetation and not due to the soil moisture changes.