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Synthetic aperture time (SAT) is a crucial component for acquiring high-quality synthetic aperture radar images with an excellent target cross-range resolution. SAT is analyzed using the range and Doppler cone angle at the center ...
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Synthetic aperture time (SAT) is a crucial component for acquiring high-quality synthetic aperture radar images with an excellent target cross-range resolution. SAT is analyzed using the range and Doppler cone angle at the center of the synthetic aperture length (SAL). However, in a real flight mission setting, only the range and Doppler cone angle at the SAL’s starting point are determined. Therefore, we present a method for estimating the range and Doppler cone angle at the center of the SAL to calculate an accurate SAT that is suitable for the spatial resolution of the assigned mission. We performed an iterative analysis of SAT at the range and Doppler cone angle at the starting point of the SAL (original SAT) and at the center of the SAL (proposed SAT). Consequently, the proposed SAT decreased by 0.69%–16.14% compared to the original SAT at a resolution of 0.1–3.0 m.
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NEC has developed an advanced airborne real-time synthetic aperture radar (SAR) system. The system has already been delivered to some customers and is in operation. By implementing all necessary processing functions by software, s...
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NEC has developed an advanced airborne real-time synthetic aperture radar (SAR) system. The system has already been delivered to some customers and is in operation. By implementing all necessary processing functions by software, such as yaw-steering compensation and multi-resolution mode with pre-summing, we have been able to eliminate several important hardware components such as mechanical yaw steering system and data reduction filters. This fully digitized and software oriented SAR architecture gives significant flexibility to the system, without compromising its performance. This radar system consists of SAR antenna equipment, an RF rack, and a control parts rack.
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We demonstrate scanning synthetic aperture radar (ScanSAR) advanced radar interferometry processing for surface deformation time series analysis. We apply the small baseline subsets (SBAS) technique to ScanSAR data synthesized fro...
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We demonstrate scanning synthetic aperture radar (ScanSAR) advanced radar interferometry processing for surface deformation time series analysis. We apply the small baseline subsets (SBAS) technique to ScanSAR data synthesized from 40 ERS-1 and ERS-2 stripmap SAR images over known deformation in Phoenix, Arizona. The strategy is to construct a burst pattern similar to Envisat ScanSAR data for two scenarios, namely, an idealized 100% burst overlap case and a realistic variable-burst synchronization case in which any image pair has at least 50% burst overlap. We find this latter scenario to be reasonable based on an assessment of the effect of burst overlap on Phoenix interferometric phase coherence. The differences between the variable burst overlap ScanSAR and stripmap SAR SBAS-derived pixel velocities have a mean of 0.02 cm/year and a standard deviation of 0.02 cm/year. It is noted that one can expect SBAS velocity and displacement one-sigma errors of 0.1 cm/year and 0.5 cm, respectively, from multilooked stripmap data. We observe that 96% and 99% of the variable burst overlap ScanSAR pixel velocities are within $pm$0.1 and $pm$ 0.2 cm/year (one- and two-sigma), respectively, of our stripmap SAR pixel velocities. These results are similar to those reported for SBAS analysis applied to low-resolution multilook interferograms derived from coherence-preserving downsampling of stripmap data. We also find that the rms deviations between variable burst overlap ScanSAR and stripmap SBAS displacement estimates are 0.40 $pm$ 0.30 cm. 68% and 94% of the variable burst overlap ScanSAR pixel displacements are within $pm$0.5 and $pm$ 1.0 cm, respec tively, of the stripmap displacements.
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Synthetic aperture radar (SAR) single-aperture systems are designed to image fixed scenes. Dual-antenna along-track interferometric (ATI) SAR systems are designed to detect moving targets and estimate their motion parameters. Alth...
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Synthetic aperture radar (SAR) single-aperture systems are designed to image fixed scenes. Dual-antenna along-track interferometric (ATI) SAR systems are designed to detect moving targets and estimate their motion parameters. Although SAR systems are not designed to characterize moving targets, for localized targets, such as vehicles or ships, this problem has been addressed in the literature with some success. Distributed moving targets are hard to characterize, even for ATI systems. Estimating surface water speeds is an ideal example of this since the water returns are generated from weak returns randomly distributed in both time and space. The question asked here is can one measure surface water speeds with a single-phase center SAR system? The answer presented is a qualified yes, with the aid of an upper bound on the water speed, but not with the same accuracy as an ATI system. This upper bound and the collection geometry provide design criteria for the filtering of the phase information. Time–frequency (TF) methods provide another speed estimate as well as a rough profile of the speed across the water channel. A robust nonparametric TF method was developed and applied to estimate the speed. Comparisons between the ATI estimate and single-phase estimates are made using data from an X-band ATI-SAR system.
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As the number of satelliteborne SAR systems increases, both the availability and the length of multitemporal (MT) sequences of SAR images have also increased. Reported research with MT SAR sequences suggests that they increase the...
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As the number of satelliteborne SAR systems increases, both the availability and the length of multitemporal (MT) sequences of SAR images have also increased. Reported research with MT SAR sequences suggests that they increase the classification accuracy for all applications over single-date images. The length of the MT SAR sequences reported in the literature is still quite modest: on the order of six images. As the length of a sequence increases, the selection of images to use in a classification becomes important. The current practice is to add scenes chronologically, and some researchers have suggested that image selection does not affect classification accuracy. Our research explored the problem of image selection in MT SAR classification. We compared the chronological selection scheme with two feature selection algorithms: a very simple algorithm and a more complex class-based algorithm. We found that, while the simple feature selection algorithm was more efficient than chronological selection, yielding peak accuracy with few features, it saturated at the same accuracy as chronological selection. The more complex algorithm was significantly more accurate than chronological selection, even with just two features. Our results suggest that the use of a feature selection algorithm produces more efficient and more accurate classification results than chronological selection.
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This paper proposes a novel algorithm for estimating the fractal dimension of sea synthetic aperture radar (SAR) images. The algorithm is based on the variation method, and it is suitably designed for the analysis of sea SAR image...
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This paper proposes a novel algorithm for estimating the fractal dimension of sea synthetic aperture radar (SAR) images. The algorithm is based on the variation method, and it is suitably designed for the analysis of sea SAR images. The SAR image fractal dimension is a feature that provides a measure of the image roughness. Such a feature can play an important role in the classification process for recognizing the presence of anomalies on the sea surface. The innovation aspects of this paper are listed as follows: 1) an extension of the variation method, which was proposed for the fractal analysis of one-dimensional signals, to the case of two-dimensional (2-D) functions; 2) a numerical formulation of the variation method, which is suitable for processing 2-D discrete signals; and 3) an optimization of the algorithm for sea SAR image analysis. The algorithm is tested and validated both on simulated and real ERS-1/2 Precision Image sea SAR images and compared with the classical estimation algorithm based on spectral analysis.
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Continuity of the European Remote Sensing Satellite Synthetic Aperture Radar (ERS SAR) archive by means of Envisat Advanced SAR (ASAR) data acquired from March 2002 has introduced the problem of the coherent combination of images ...
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Continuity of the European Remote Sensing Satellite Synthetic Aperture Radar (ERS SAR) archive by means of Envisat Advanced SAR (ASAR) data acquired from March 2002 has introduced the problem of the coherent combination of images coming from sensors with slightly different frequencies. The spectral shift principle states that in case of extended distributed targets, the frequency shift is equivalent to a change of looking angle. In this paper, the same principle is exploited to analyze the behavior of permanent scatterers (PSs) with an extension that is smaller than the ground resolution cell. The conditions under which the PSs identified by ERS can be continued by Envisat are then theoretically determined and experimentally validated. Moreover, this analysis shows that acquisitions characterized by different frequencies can be used to identify the slant-range position of scatterers with high subcell accuracy (tens of centimeters). From the processing side, a very precise images coregistration step is required to get the results described in this paper.
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In this paper, we introduce a finite-difference time-domain simulator that accurately models the interaction of microwaves with realistic soils, specifically from spaceborne interferometric synthetic aperture radar (InSAR). The m...
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In this paper, we introduce a finite-difference time-domain simulator that accurately models the interaction of microwaves with realistic soils, specifically from spaceborne interferometric synthetic aperture radar (InSAR). The modeled soils are characterized by surface roughness, correlation length, bulk moisture content, vertical moisture gradient, and small air-filled-void content. Simulation results include both backscatter and interferometric phase, and we are particularly interested in assessing the potential of the latter as a proxy for soil moisture. We find that differences in homogeneous bulk moisture result in only small phase differences $(C; 5^{circ})$. In contrast, combinations of vertical moisture gradients and small air-filled voids, which may typically exist in more realistic soils, can produce phase changes $> 30^{circ}$ for HH and $> 50^{circ}$ for VV when the soil moisture is varied from 3% to 30% in the uppermost 2 cm of the soil. Phase changes of this magnitude are easily detectable by spaceborne InSAR techniques. While a strong phase response to a change in mean bulk moisture is common to vertical moisture gradient and small air-filled-void cases, their corresponding backscatter responses are very different. A vertical moisture gradient makes the backscatter response dramatically flatter compared with the case of uniform moisture; in contrast, the introduction of air-filled voids barely alters the backscatter. Thus, it may be possible to infer near-surface soil-structure parameters such as vertical gradients or fractions of voids and inhomogeneities from combined SAR phase and backscatter data. Future SAR sensors could be optimized for this purpose. Prior theoretical work based on the assumption of vertically unifor-
m soil-moisture distributions may need to be adjusted, and the lack of a theory that accommodates more complex soil structures may explain why backscatter inversions have yet to result in a viable operational system.
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Wetlands are highly productive and support a wide variety of ecosystem goods and services. Monitoring wetland is essential and potential. Because of the repeat-pass nature of satellite orbit and airborne, time-series of remote sen...
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Wetlands are highly productive and support a wide variety of ecosystem goods and services. Monitoring wetland is essential and potential. Because of the repeat-pass nature of satellite orbit and airborne, time-series of remote sensing data can be obtained to monitor wetland. UAVSAR is a NASA L-band synthetic aperture radar (SAR) sensor compact pod-mounted polarimetric instrument for interferometric repeat-track observations. Moreover, UAVSAR images can accurately map crustal deformations associated with natural hazards, such as volcanoes and earthquakes. And its polarization agility facilitates terrain and land-use classification and change detection. In this paper, the multi-temporal UAVSAR data are applied for monitoring the wetland change. Using the multi-temporal polarimetric SAR (PolSAR) data, the change detection maps are obtained by unsupervised and supervised method. And the coherence is extracted from the interfometric SAR (InSAR) data to verify the accuracy of change detection map. The experimental results show that the multi-temporal UAVSAR data is fit for wetland monitor.
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This paper proposes a polarimetric homogeneity measurement and applies it to the speckle filtering of polarimetric synthetic aperture radar (PolSAR) data. First, a line-and-edge (LAE) detector that can detect both the lines and ed...
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This paper proposes a polarimetric homogeneity measurement and applies it to the speckle filtering of polarimetric synthetic aperture radar (PolSAR) data. First, a line-and-edge (LAE) detector that can detect both the lines and edges in one scan is developed based on the traditional edge detector. A polarimetric homogeneity measurement is then derived by combining the equivalent number of looks and the LAE maps and is used to distinguish the homogeneous and heterogeneous regions. Finally, a new adaptive-window PolSAR filtering algorithm based on the LAE detector and the polarimetric homogeneity measurement is proposed. The proposed speckle filter adjusts the filtering windows in both shape and size, based on the homogeneity and gradient information. Consequently, it uses small and nonsquare windows in heterogeneous regions to preserve the detail information and uses large and square windows in homogeneous regions to maximize the suppression of speckle noise. EMISAR and ESAR L-band PolSAR data were used to demonstrate the effectiveness of the proposed filter in speckle suppression, detail preservation, and polarimetric information preservation.
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