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The present status of the applications of Synthetic Aperture Radars (SARs) is reviewed, and the technology state-of-the art as represented by the Seasat-A and SIR-A SARs examined. The potential of SAR applications, and the near- and longer-term technology trends are assessed.
The relationship between synthetic aperture radar (SAR) imagery of ocean waves and the ocean surface structure is discussed. The effects of ocean surface motion on SAR images is given. A generalization of conventional SAR correlation techniques is developed to provide imagery with the minimum possible degradation and distortion. The modeling of such imagery is discussed and an analytically tractable example given. Ongoing work towards the determination of the relevant components of surface microstructure is described. The future use of SAR phase information to supplement information obtainable from SAR imagery is suggested.
The SEASAT Synthetic-Aperture Radar (SAR) system, the data processors, the extent of the image data set, and the means by which a user obtains this data are described and the data quality is evaluated. The user is alerted to some potential problems with the existing volume of SEASAT SAR image data, and allows him to modify his use of that data accordingly. Secondly, the manual focuses on the ultimate focuses on the ultimate capabilities of the raw data set and evaluates the potential of this data for processing into accurately located, amplitude-calibrated imagery of high resolution. This allows the user to decide whether his needs require special-purpose data processing of the SAR raw data.
Nonlinearities within a synthetic aperture radar (SAR) present significant obstacles to the calibration of the output imagery. The problem of calibrating a SAR is considerably more involved than that of calibrating a real aperture radar (RAR) or scatterometer, since the SAR relies heavily on the principle of superposition, which fails in nonlinear systems. It is shown in this paper that non-linearities can distort SAR imagery to such an extent that two areas of equal backscatter on the ground can be imaged to have significantly different intensities in the image.
A review of various spaceborne synthetic aperture radar (SAR) processing algorithms and their associated real-time SAR processor architectures is given in this paper. The processing complexity for each real-time SAR processor is presented next. A complexity comparison is then given based on the Seasat SAR parameters. It is shown that the frequency/time domain hybrid fast correlation and the two-stage fast Fourier transform (FET) approaches are the two most cost-effective choices for real-time spaceborne SAR processing. Finally, a discussion on future development trends in real-time spaceborne SAR processing is given.
Information extraction and transmission techniques for synthetic aperture radar (SAR) imagery were investigated. Four interrelated problems were addressed. An optimal tonal SAR image classification algorithm was developed and evaluated. A data compression technique was developed for SAR imagery which is simple and provides a 5:1 compression with acceptable image quality. An optimal textural edge detector was developed. Several SAR image enhancement algorithms have been proposed. The effectiveness of each algorithm was compared quantitatively.
Adaptive quantizer for burst-mode synthetic-aperture radar reduces data rate of return signal. Device, called block floating-point quantizer (BFPQ) basically analog-to-digital converter that covers wide dynamic range and discards appropriate lower order bits. BFPQ is, in effect, digital approximator with automatic gain control. Moves floatingpoint marker binary representation of signal data in accordance with perceived dynamic range. Available step sizes thus limited to multiples of underlying smallest quantization step (represented by lowest order bit). Retains only first K most significant bits of signal; (L,K) BFPQ is one that does K-bit quantization of signal originally quantized to L bits. Quantization error simply difference between actual signal level and its binary approximation. Other potential applications for BFPQ include speech compression and picture data compression.
Report discusses performances of spaceborne interferometric synthetic-aperture radar systems in terms of utility of SAR echo data in generation of topographic maps.
An increasing challenge for P-band Synthetic Aperture Radar (SAR) is Radio Frequency Interference (RFI). RFI results in image distortions and degrades the derived science products. This makes it critical to apply RFI removal techniques to restore the image quality. New advanced techniques can be achieved with Digital Beamforming (DBF) radars such as EcoSAR. In this paper, we present a Range-Dependent Time Minimum Variance Distortionless Response (RDTMVDR) Beamformer and apply it to EcoSAR flight data during post-processing. The antenna pattern (AP) is adaptively changed for each range line which increases the RFI suppression compared to a fixed AP for each pulse. The interferometric image quality is assessed before and after RFI suppression.
We use the interferometric correlation from Envisat synthetic aperture radar (SAR) images to map the details of the surface ruptures related to the 26 December 2003 earthquake that devastated Bam, Iran. The main strike-slip fault rupture south of the city of Bam has a series of four segments with left steps shown by a narrow line of low correlation in the coseismic interferogram. This also has a clear expression in the field because of the net extension across the fault. Just south of the city limits, the surface strain becomes distributed over a width of about 500 m, probably because of a thicker layer of soft sedimentary material.
A computer simulation program that is used to study the effects of digitization in spaceborne synthetic aperture radar systems is described. An analytical study of the distortion noise introduced by the digitization process at various gain settings, sampling rates and bit error rates is presented and the results agree well with those obtained from the simulation program. The simulation program is also used to study the spatial frequency response of hard-limiting (quantizing to 1-bit) synthetic aperture radar systems. The implications of these results on synthetic aperture radar system design are discussed.
Simultaneous synthetic aperture radar (SAR) and cloud photographic observations of the Atlantic Ocean off the coast of Florida were made from a high-altitude aircraft when there was an unstable marine boundary layer. The synthetic aperture radar images show unusual kilometer-sized features on the ocean surface which are related to clouds. The ocean near shore was cloud-free and had no radar features, while from 30 to 330 km offshore there were clouds and prominent kilometer-sized features in the SAR image. These radar features are most prominent when the radar was looking upwind, are less prominent when the radar was looking downwind, and disappear entirely when the radar was looking crosswind. Since ocean radar echo strengths are believed to be controlled primarily by ocean waves satisfying the Bragg relation, these radar features most likely resulted from local enhancements of short gravity waves with 17- to 34-cm wavelengths, which in turn are surface expressions of roll convections in a kilometer-thick unstable marine boundary layer.
Digitally processed SEASAT synthetic aperture raar (SAR) imagery of the Denver, Colorado urban area was examined to explore the potential of SAR data for mapping urban land cover and the compatability of SAR derived land cover classes with the United States Geological Survey classification system. The imagery is examined at three different scales to determine the effect of image enlargement on accuracy and level of detail extractable. At each scale the value of employing a simplistic preprocessing smoothing algorithm to improve image interpretation is addressed. A visual interpretation approach and an automated machine/visual approach are employed to evaluate the feasibility of producing a semiautomated land cover classification from SAR data. Confusion matrices of omission and commission errors are employed to define classification accuracies for each interpretation approach and image scale.
The data handling and processing in using synthetic aperture radar as a satellite-borne earth resources remote sensor is considered. The discussion covers the nature of the problem, the theory, both conventional and potential advanced processing techniques, and a complete computer simulation. It is shown that digital processing is a real possibility and suggests some future directions for research.
The characteristics and capabilities of synthetic aperture radar are discussed so as to identify those features particularly unique to SAR. The SAR and Optical images were compared. The SAR is an example of radar that provides more information about a target than simply its location. It is the spatial resolution and imaging capability of SAR that has made its application of interest, especially from spaceborne platforms. However, for maximum utility to remote sensing, it was proposed that other information be extracted from SAR data, such as the cross section with frequency and polarization.
A single-frequency multibeam synthetic aperture radar concept for large swath imaging desired for global oceanography is evaluated. Each beam iilluminates a separate range and azimuth interval, and images for different beams may be separated on the basis of the Doppler spectrum of the beams or their spatial azimuth separation in the image plane of the radar processor. The azimuth resolution of the radar system is selected so that the Doppler spectrum of each beam does not interfere with the Doppler foldover due to the finite pulse repetition frequency of the radar system.
The paper discusses the Seasat-A synthetic aperture radar system (SAR). The objective of this system was to detect ocean waves from orbital altitudes. A SAR system operating at 1275 MHz was designed to meet this objective; the choice of wavelength resulted from the imagery obtained by aircraft during 1972 to 1974 and the ease of implementation. The Seasat-A SAR system was turned-on in orbit on July 4, 1978, and gathered imagery until the spacecraft bus failed in orbit in Oct. 1978. The hardware including the antenna, the radar sensor, and data-link subsystem, and the SAR data processing subsystem are described; the radar performance including the SAR system error budget and various SAR imageries are presented, concluding that the performance of the Seasat-A SAR system met all of its parameters on at least some of the imagery.
Synthetic aperture radar images of ocean waves were obtained in conjunction with reference wave data near Marineland, Florida, December 14, 1975. Each of the various types of measurements were processed into a form that allowed direct comparisons with the others. Maxima of radar spectra occurred at the same frequencies as the maxima of reference wave height spectra. In a comparison of a radar spectrum with observed spectra of wave height, wave orbital velocity, and surface slope the high-frequency portion of the radar spectrum lay near and between the wave height and the orbital velocity spectra but differed significantly from the surface slope spectrum. The radar-derived mean directions and model-fitted directional spreads of wave energy were close to the values from a directional wave buoy and indicated the accuracy of radar measurements of wave direction. However, a directional plot of a radar spectrum near shore at the frequency of the maximum showed a sharper peak than such a plot of a fitted spectrum derived from reference data.