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Four improved chirp scaling algorithms (CSAs) are proposed to reconstruct images from synthetic aperture radar (SAR) data received at high squint angles. The proposed methods reconstruct better SAR images with less computational load and memory than the conventional CSA.
Target segmentation of synthetic aperture radar (SAR) images is one of the challenging problems in SAR image interpretation, which often serves as a processing step for SAR target recognition. Target segmentation tries to separate the target from the background thus eliminating the interference of background noises or clutters. However, the segmentation may also discard a part of the target characteristics...
In this paper, we investigate making use of a convolutional neural network (CNN) to solve the task of identifying corresponding patches in very high resolution (VHR) optical and SAR imagery of complicated urban scenery. By doing so, the binary decision function is learnt directly from automatically generated training data and does not resort to any hand-crafted features. First evaluations show great...
In this paper we describe the method that has been implemented to derive the forest/non-forest maps from TanDEM-X interferometric synthetic aperture radar (InSAR) data, globally acquired in stripmap single polarization (HH) mode. Among the several observables systematically provided by the TanDEM-X system, the volume decorrelation contribution, derived from the interferometric coherence, shows to...
Synthetic aperture radar (SAR) data are becoming more and more accessible and have been widely used in many applications. To effectively and efficiently represent multiple SAR images, we propose the mixture of Itakura-Saito (IS) divergence for non-negative matrix factorization (NMF) to perform the dimension reduction. Our proposed method incorporates the unit-mean Gamma mixture model into the NMF...
We present a model-based approach aimed to help predicting which objects in an imaged scene will appear as persistent scatterers in Differential Synthetic Aperture Radar Interferometry (DInSAR) data, given their shapes and sizes, and given the scene background and sensor parameters. The approach consists in computing the interferometric coherence of a pair of acquisitions for a resolution cell comprising...
Synthetic aperture radar (SAR) has been widely used in remote sensing. Feature extraction is a crucial step in SAR automatic target recognition (ATR). In this paper, Kernel Marginal Sample Discriminant Embedding (KMSDE) is proposed, which is based on kernel trick and manifold learning theory. In feature extraction via KMSDE, the original dataset is mapped to high dimensional space and manifold learning...
Soil moisture radar retrieval algorithms generally utilize substantial ancillary data to parametrize complex electromagnetic models. In this work, we utilize an existing empirical approach as an alternative; it describes radar backscatter of a vegetated scene as a linear function of soil moisture, hence reducing dependence on ancillary data. We use 2.5 years of L-band Aquarius radar and radiometer...
This paper displays a case study which accomplishes crop classification of simulated compact polarimetric (CP) SAR and fully polarimetric (FP) SAR images with Random Forest. Since the potential of CP SAR in classification has been illustrated by various researches, we intend to find out which of the polarimetric features are more superior in crop classification, through the importance rank of Random...
This paper presents a ship-detection study with Synthetic Aperture Radar (SAR) images acquired at two different frequencies: X- and C-band. The detection procedure relies on a novel algorithm based on the likelihood functions of both canonical ship target and sea clutter. Spaceborne images were acquired over the same area in the Solent Channel in UK at approximately the same time on the 7th June 2016...
The objectives of this research are to (1) address remote sensing strategies and requirements for estimating snow depth and snow water equivalent (SWE) using existing L-Band interferometric data sets in coordination with field-based observations and modeling frameworks and, with this information, (2) inform the Next Generation Cold Land Processes Experiment (SnowEx) toward articulating the appropriate...
Mapping iceberg locations and geometrical parameters is important for marine operational applications and climate science. The innovative TanDEM-X mission (TDM) was used for 3D mapping of icebergs in sea ice with the single-pass SAR interferometry (InSAR) method. The extracted digital elevation model (DEM) from TDM InSAR data over icebergs in sea ice was compared to a DEM generated from very-high-resolution...
Polarimetric SAR interferometry has been recently applied with TanDEM-X data to the retrieval of vegetation height in rice fields, which constitutes the first demonstration of this technique applied to agricultural crops with satellite data [1]. In this work we extend that study by including an analysis of the effect of incidence angle and baseline on the retrieval of height. The study is based on...
Ship classification with spaceborne high resolution synthetic aperture radar (SAR) has wide applications in maritime traffic monitoring, fishing law-enforcement operation, marine security, etc. Deep learning, which has the ability of learning features itself, is successfully used in computer vision and artificial intelligence, and introduced into remote sensing field in recent years. In this study,...
This paper compares different similarity measures for the matching of very-high-resolution SAR and optical images over urban areas. It is meant to provide guidance about the performance of both signal-based and descriptor-based similarity measures in the context of this non-trivial case of multi-sensor correspondence matching. Using an automatically generated training dataset, thresholds for the distinction...
In this paper, we summarize challenges, proposed solutions and recent trends in the field of SAR-optical remote sensing data fusion. Although being a pre-processing step before the actual fusion-by-estimation, it is shown that matching and coregistration is one of the core challenges in that regard, which is mainly due to the strongly different geometric and radiometric properties of the two observation...
TanDEM-X is a single-pass radar interferometric mission, which is comprised of two formation flying satellites, with the primary goal of generating a global Digital Elevation Model (DEM) of unprecedented accuracy. Between December 2010 and early 2015 all land surfaces have been acquired at least twice, difficult terrain up to seven or eight times and as of September 2016 the final TanDEM-X DEM dataset...
We present a new Synthetic Aperture Radar (SAR) raw signal simulator, which is able to simultaneously generate the raw signals of the different polarimetric channels of a polarimetric SAR system in such a way that the correct covariance matrix is obtained for the final images. Extended natural scenes, dominated by surface scattering, are considered. A fast Fourier-domain approach is used for the generation...
This paper outlines the development of a new SIR-C processor to replace the original processing system, which is no longer functional. It is important to be able to process raw SIR-C data, because there are several applications for which these data can be used. Two exemplary applications are provided in this paper. First, SIR-C data received with two along-track antennas are used to validate the so-called...
With more degrees of freedom in the along-track axis, multichannel SAR systems are widely investigated for the purpose of ground moving target indication and motion parameter estimation. However, since conventional multichannel SAR system usually works at the side-looking mode and only the radial velocity is considered, it fails to detect targets only moving in azimuth. In this paper, the variable-boresight...
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