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A data set is described which consists of digitized synthetic aperture radar (SAR) imagery plus correlative data and some preliminary analysis results. This data set should be of value to experimenters who are interested in the SAR instrument and its application to the detection and monitoring of oil on water and other distributed targets.
Images of earth can be produced with an assumed synthetic aperture radar (SAR) on a satellite platform undergoing a nutating relative motion from geosynchronous altitude. From a 50 deg inclined circular orbit, the contiguous United States can be imaged in about 3 h of segmented operation at 100-m resolution with 4-azimuth-look averaging. The 2450-MHz transmitter radiates 1312 W of average power from a steerable 15-m-diam antenna. The SAR can image daily an area bounded longitudinally and latitudinally.
The digital processing requirements of several algorithms for extracting the spectrum of a detected synthetic aperture radar (SAR) image from the raw SAR data are described and compared. The most efficient algorithms for image spectrum extraction from raw SAR data appear to be those containing an intermediate image formation step. It is shown that a recently developed compact formulation of the image spectrum in terms of the raw data is computationally inefficient when evaluated directly, in comparison with the classical method where matched-filter image formation is an intermediate result. It is also shown that a proposed indirect procedure for digitally implementing the same compact formulation is somewhat more efficient than the classical matched-filtering approach. However, this indirect procedure includes the image formation process as part of the total algorithm. Indeed, the computational savings afforded by the indirect implementation are identical to those obtained in SAR image formation processing when the matched-filtering algorithm is replaced by the well-known 'dechirp-Fourier transform' technique. Furthermore, corrections to account for slant-to-ground range conversion, spherical earth, etc., are often best implemented in the image domain, making intermediate image formation a valuable processing feature.
An ultra-high-frequency microstrippatch antenna has been built for use in airborne synthetic-aperture radar (SAR). The antenna design satisfies requirements specific to the GeoSAR program, which is dedicated to the development of a terrain-mapping SAR system that can provide information on geology, seismicity, vegetation, and other terrain-related topics. One of the requirements is for ultra-wide-band performance: the antenna must be capable of operating with dual linear polarization in the frequency range of 350 plus or minus 80 MHz, with a peak gain of 10 dB at the middle frequency of 350 MHz and a gain of at least 8 dB at the upper and lower ends (270 and 430 MHz) of the band. Another requirement is compactness: the antenna must fit in the wingtip pod of a Gulfstream II airplane. The antenna includes a linear array of microstrip-patch radiating elements supported over square cavities. Each patch is square (except for small corner cuts) and has a small square hole at its center.
During and after flooding events, mapping the extent of floodwaters aids in the distribution of resources, recovery efforts, and damage assessment practices. Development of a land cover classification system focused on mapping inundation after major hurricane events using synthetic aperture radar (SAR) data could allow for the production of near-real-time inundation mapping, enabling government and emergency response entities to get a preliminary idea of a developing situation. Complimentary optical and SAR images from domestic and foreign entities are brought together through activations of the International Charter: Space and Major Disasters to support response efforts, from true-color, near-infrared, and thermal remote sensing data obtained by NASA, NOAA, and international satellites to the collection of high-resolution true color aerial photography by NOAA and the National Geodetic Survey. In response to Hurricane Florence of 2018, NASA JPL collected numerous swaths of quad-pol L-band SAR data with the Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) instrument observing the record-setting river stages across North and South Carolina. The resulting fully-polarized SAR images allow for mapping of inundation extent at a high spatial resolution with a unique advantage over optical imaging stemming from the sensor’s ability to penetrate cloud cover and dense vegetation. In this study, true-color NOAA aerial and commercial satellite imagery are used in conjunction with four UAVSAR data swaths centered on the Lumberton and Cape Fear River basins in southeastern North Carolina to develop a Random Forest classification model focused on mapping open water and floodwater otherwise obscured by vegetation or lingering cloud cover. Ancillary building footprint, transportation route, and population data will also be incorporated into the classification scheme to estimate the societal impacts of flooding based on the proximity of features to detected inundation. Preliminary results from the Hurricane Florence case study will be discussed in addition to the limitations of available validation data for assessment of the classifier’s accuracy.
A preliminary assessment has been made of the capability of the Seasat synthetic aperture radar to detect ocean waves. Comparison with surface and aircraft measurements from five passes of the satellite over the Gulf of Alaska indicates agreement to within about 15 percent in wavelength and about 25 deg in wave direction. These results apply to waves 100 to 250 meters in length, propagating in a direction predominantly across the satellite track, in sea states with significant wave height in a range of 2 to 3.5 meters.
A program initiated by NASA was formed to address some key earth resources synthetic aperture radar (SAR) needs. Major steps in the SAR system development are summarized, and the objective of the advanced SAR (ASAR) program is defined. The program rationale and specific objectives are discussed, including system calibration, wide-band technique evaluation, a system resolution of 10 m or better at 45 deg, and an airborne system to cover four bands within 1 to 10 GHz. The ASAR conceptual system design, consisting of a modulator, transmitter, antenna, receiver, calibrator, and data system modules is also presented, and ASAR capability expansions are discussed. The program, scheduled for 1983, will provide a data source which is not available to applications investigations at this time, and will produce design approaches that are flexible and multimission to the maximum extent for application to a Shuttle or a freeflyer system.
The imagery obtained with the aid of synthetic aperture radars (SAR) has been applied to several remote sensing disciplines such as geologic feature mapping, oceanic phenomena studies, and land use and urban morphology studies. The successful SAR experiment on Seasat and the Shuttle demonstrated the feasibility of global radar mapping at relatively high resolution from a spaceborn platform. The present investigation is concerned with the requirements of and the tradeoffs among several SAR image quality parameters. The results are presented from a survey study concerning the interpretability of a set of SAR images. The data used to generate these images were obtained by the Seasat SAR experiments. Attention is given to image scenes and the simulation experiment, image interpretation survey results, multiple-looks, the number of looks vs resolution, and number of bits vs resolution.
The physical mechanism for the synthetic Aperture Radar (SAR) imaging of ocean waves is investigated through the use of analytical models. The models are tested by comparison with data sets from the SEASAT mission and airborne SAR's. Dominant ocean wavelengths from SAR estimates are biased towards longer wavelengths. The quasispecular scattering mechanism agrees with experimental data. The Doppler shift for ship wakes is that of the mean sea surface.
Data acquired by synthetic aperture radar (SAR) and LANDSAT multispectral scanner (MSS) were processed and analyzed to derive forest-related resources inventory information. The SAR data were acquired by using the NASA aircraft X-band SAR with linear (HH, VV) and cross (HV, VH) polarizations and the SEASAT L-band SAR. After data processing and data quality examination, the three polarization (HH, HV, and VV) data from the aircraft X-band SAR were used in conjunction with LANDSAT MSS for multisensor data classification. The results of accuracy evaluation for the SAR, MSS and SAR/MSS data using supervised classification show that the SAR-only data set contains low classification accuracy for several land cover classes. However, the SAR/MSS data show that significant improvement in classification accuracy is obtained for all eight land cover classes. These results suggest the usefulness of using combined SAR/MSS data for forest-related cover mapping. The SAR data also detect several small special surface features that are not detectable by MSS data.
A polarization filter can maximize the signal-to-noise ratio of a polarimetric synthetic aperture radar (SAR) and help discriminate between targets or enhance image features, e.g., enhance contrast between different types of target. The method disclosed is based on the Stokes matrix/ Stokes vector representation, so the targets of interest can be extended targets, and the method can also be applied to the case of bistatic polarimetric radars.
We present nearly coincident observations of backscattering from the Earth Remote-Sensing Satellite (ERS) 1 synthetic aperture radar (SAR) and of near-surface temperature from six drifting buoys in the Beaufort Sea, showing that the onset of melting in snow on multiyear sea ice is clearly detectable in the SAR data. Melt onset is marked by a clean, steep decrease in the backscattering cross section of multiyear ice at 5.3 GHz and VV polarization. We investigate the scattering physics responsible for the signature change and find that the cross section decrease is due solely to the appearance of liquid water in the snow cover overlying the ice. A thin layer of moist snow is sufficient to cause the observed decrease. We present a prototype algorithm to estimate the date of melt onset using the ERS 1 SAR and apply the algorithm first to the SAR data for which we have corresponding buoy temperatures. The melt onset dates estimated by the SAR algorithm agree with those obtained independently from the temperature data to within 4 days or less, with the exception of one case in which temperatures oscillated about 0 C for several weeks. Lastly, we apply the algorithm to the entire ERS 1 SAR data record acquired by the Alaska SAR Facility for the Beaufort Sea north of 73 deg N during the spring of 1992, to produce a map of the dates of melt onset over an area roughly 1000 km on a side. The progression of melt onset is primarily poleward but shows a weak meridional dependence at latitudes of approximately 76 deg-77 deg N. Melting begins in the southern part of the study region on June 13 and by June 20 has progressed to the northermost part of the region.
A study is made of the effects of quantization of the radar returns transmitted from aircraft or spacecraft employing a synthetic aperture radar system. The study is based on the output images obtained after one-bit, two-bit, and eight-bit quantizations and comparing the results to ground truth. In this way the degradation resulting from data or bandwidth reduction is determined. Quantization is evaluated in terms of crater scene, number of looks, and transmission error rate. It is found that two-bit quantization of raw radar data from homogeneous scenes processed to 32 looks yields nearly all the details of the original. One-bit quantization of raw radar data from homogeneous scenes processed to 32 looks yields a good visual representation of the scene but some fine detail is lost and the absolute reflectivity level is not reliable. Image quality is observed to improve with more looks and video and intermediate frequency quantization are not distinguishable even for one-bit quantizations. Image quality is not influenced by bit error rates less than about 2 to the -7th power.
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None given. (From introduction): ...we will briefly describe the instrument characteristics, the evolution of the various radar modes, the instrument performance and improvement in the knowledge of the positioning and attitude information of the radar. In addition, we will summarize the [rogress of the data processing effort, especially in the interferometry processing. Finally, we will address the issue of processing and calibrating the cross-track interferometry (XTI) data.
Ocean waves measured offshore of Marineland, Florida, by the synthetic aperture radar (SAR) are compared with the surface truth data. The Fourier transform of SAR imageries are taken and the corrections of the wave directions and wave lengths due to the relative velocities between SAR and waves are considered. Favorable comparisons are obtained for the peak frequencies, wave directions, and directional distributions. However, the one-dimensional SAR spectra are quite different from the surface truth wave height spectra.
A method has been developed for precise sensor platform attitude determination which exploits the availability of synthetic aperture radar (SAR) sensors on future planned NASA earth orbiting spacecraft. Using the ephemeris along with data on planet shape and rotation, the relative motion between sensor and target area and therefore the Doppler frequency shift in the returned echo data is determined. Equations have been developed that relate the Doppler shift to the antenna attitude. The method is tested by comparing attitude predictions from SEASAT SAR digital echo data with available conventionally determined SEASAT attitude information.
A method is developed for estimating the sea surface height using the complex imagery from synthetic aperture radar (SAR). Algorithms are developed for the envelope and phase demodulation, regression, and filtering of the SAR complex imagery and are applied to simulated and actual satellite radar SEASAT-SAR data. A simulation of a simplified stationary scene is utilized in order to establish tentative sufficient conditions on large-scale SAR and sampling parameters for the accurate estimation of the scale structure's height. It is shown that the algorithm accurately estimated a long wavelength low-amplitude sea height structure present in the SEASAT-SAR data, which was determined to be consistent with observations.