Large Synthetic Aperture Radar Research Articles

Integration of SAR Data Into Monitoring of the 2014–2015 Holuhraun Eruption, Iceland: Contribution of the Icelandic Volcanoes Supersite and the FutureVolc Projects

We report how data from satellite and aerial synthetic aperture radar (SAR) observations were integrated into monitoring of the 2014-2015 Holuhraun eruption in the Barðarbunga volcanic system, the largest effusive eruption in Iceland since the 1783-84 Laki eruption. A lava field formed in one of the most remote areas in Iceland, after the propagation of a ~50 km-long dyke beneath the Vatnajokull ice cap, where the Barðarbunga caldera is located. Due to the 6 month duration of the eruption, mainly in wintertime, daily monitoring was particularly challenging. During the eruption, the European volcanological project FutureVolc was ongoing, allowing collaboration of many European experts on volcano monitoring activities. Icelandic volcanoes are also a permanent Supersite within the Geohazard Supersites and Natural Laboratories (GSNL) initiative, with support from the Committee on Earth Observation Satellite (CEOS) in the form of a large collection of SAR images. SAR data were acquired by Cosmo-SkyMed (CSK) and TerraSAR-X (TSX) satellites and complemented by aerial SAR images. The large set of SAR satellite data significantly contributed to the daily monitoring during the unrest at Barðarbunga caldera, the Holuhraun eruption and the year following the eruption. Detection of surface changes using both SAR amplitude and phase information was conducted throughout the whole duration of the volcano-tectonic event, and in the following months, to quantify and track the evolution of volcanic processes at Holuhraun and geothermal activity at Barðarbunga volcano. Combination of SAR data with other data sets, e.g. satellite optical images and geodetic Global Positioning System (GPS) measurements, was essential for the evaluation of the volcanic hazard in the whole area. International collaboration within the Futurevolc project formed the basis for successful analyses and interpretation of the large SAR data set. Information was provided at Scientific Advisory Board meetings of the Icelandic Civil Protection and used in decision-making, as well as for supporting field-deployment and air-based surveys.

Least-Square-Based Nonuniform Borehole SAR Imaging for Subsurface Sensing

This paper presents the least-square-based nonuniform borehole synthetic aperture radar (SAR) imaging method with cosine accuracy factor for subsurface sensing. Based on the Stolt migration, the frequency-wavenumber spectrum of nonuniform data is efficiently approximated in the least-square-sense for the target space generation. The nonuniform power exponent basis is interpolated into several uniform power exponent bases with cosine accuracy factors, and then a virtual uniform sample set with a larger scale is generated for frequency-wavenumber spectrum approximation and imaging process. The proposed method can give accurate subsurface image result with nonuniform data at a greatly reduced computational cost. The approximation error and computational cost of the proposed method are analyzed and compared with those of Gaussian nonuniform imaging method. The imaging capabilities of the proposed method are theoretically simulated and experimentally demonstrated for distributed targets. The results show that the normalized mean square error and normalized maximum error of the proposed method are at least 8.07 dB and 4.29 dB, respectively, lower than those of conventional Stolt migration method. The imaging properties of this proposed method are shown to be superior to the conventional Stolt migration method, Gaussian nonuniform imaging method and Kirchhoff migration method, which is suitable for large nonuniform SAR imaging applications.

Large areas surface deformation analysis through a cloud computing P-SBAS approach for massive processing of DInSAR time series

We present in this work a methodology for computing surface deformation time series and mean velocity maps of large areas. Our approach relies on the availability of a multi-temporal set of synthetic aperture radar (SAR) data collected from ascending and descending orbits over an area of interest, and also permits us to estimate the vertical and horizontal (East-West) components of the Earth's surface deformation. The adopted methodology is based on an advanced cloud computing implementation of the differential SAR interferometry (DInSAR) Parallel Small Baseline Subset (P-SBAS) processing chain which allows the unsupervised processing of large SAR data volumes, from the raw data (level-0) imagery up to the generation of the corresponding DInSAR time series and maps. The solution presented, which is highly scalable, has been tested on ascending and descending ENVISAT SAR archives comprising approximately 400GB of data, which have been acquired over a large area of southern California (US) that extends over about 90,000km2. Such an input dataset has been processed in parallel by exploiting 280 computing nodes of the Amazon Web Services Cloud environment. The overall processing lasted about 8h and cost approximately $1900 USD. Moreover, to produce the final mean deformation velocity maps of the vertical and horizontal (East-West) displacement components of the whole investigated area, we also took advantage of the information available from external GPS measurements that permit us to account for possible regional trends not easily detectable by DInSAR and to refer the P-SBAS measurements to an external geodetic datum.The results presented clearly demonstrate the effectiveness of the proposed approach that paves the way to the extensive use of the available ERS-1/2 and ENVISAT SAR data archives. Furthermore, the proposed methodology can be particularly suitable to deal with the very large data flow provided by the Sentinel-1 constellation, thus permitting the extension of the DInSAR analyses at a nearly global scale.

TANDEM-X MISSION STATUS

Abstract. TanDEM-X (TerraSAR-X add-on for Digital Elevation Measurements) is an innovative formation flying radar mission that opens a new era in spaceborne radar remote sensing. Its primary objective is the acquisition of a global Digital Elevation Model (DEM) with unprecedented accuracy (12 m horizontal resolution and 2 m relative height accuracy). This goal is achieved by extending the TerraSAR-X synthetic aperture radar (SAR) mission by a second TerraSAR-X like satellite, TanDEM-X (TDX). Both satellites fly in close orbit formation of a few hundred meters distance, and the resulting large single-pass SAR interferometer features flexible baseline selection enabling the acquisition of highly accurate cross-track interferograms not impacted by temporal decorrelation and atmospheric disturbances. Beyond the global DEM, several secondary mission objectives based on along-track interferometry as well as new bistatic and multistatic SAR techniques have been defined. Since 2010 both satellites have been operated in close formation to map all land surfaces at least twice and difficult terrain even up to four times. While data acquisition for the DEM generation will be concluded by the end of 2014 it is expected to complete the processing of the global DEM in the second half of 2016.

An automatic method for mapping inland surface waterbodies with Radarsat-2 imagery

The use of synthetic aperture radar (SAR) imagery is generally considered to be an effective method for detecting surface water. Among various supervised/unsupervised classification methods, a SAR-intensity-based histogram thresholding method is widely used to distinguish waterbodies from land. A SAR texture-based automatic thresholding method is presented in this article. The use of texture images substantially enhances the contrast between water and land in intensity images. It also makes the method less sensitive to incidence angles than intensity-based methods. A modified Otsu thresholding algorithm is applied to selected sub-images to determine the optimal threshold value. The sub-images were selected using k-means results to ensure a sufficient number of pixels for both water and land classes. This is critical for the Otsu algorithm being able to detect an optimal threshold for a SAR image. The method is completely unsupervised and is suitable for large SAR image scenes. Tests of this method on a Radasat-2 image mosaicked from 8 QuadPol scenes covering the Spritiwood valley in Manitoba, Canada, show a substantial increase in land–water classification accuracy over the commonly used SAR intensity thresholding method (kappa indices are 0.89 vs. 0.79). The method is less computationally intensive and requires less user interaction. It is therefore well suited for detecting waterbodies and monitoring their dynamic changes from a large SAR image scene in a near-real time environment).

TanDEM-X: The New Global DEM Takes Shape

Abstract-TanDEM-X (TerraSAR-X add-on for Digital Elevation Measurements) is an innovative formation flying radar mission that opens a new era in spaceborne radar remote sensing. The primary objective is the acquisition of a global Digital Elevation Model (DEM) with unprecedented accuracy (12 m horizontal resolution and 2 m relative height accuracy). This goal is achieved by extending the TerraSAR-X synthetic aperture radar (SAR) mission by a second, TerraSAR-X like satellite TanDEM-X (TDX) flying in close formation with TerraSAR-X (TSX). The resulting large single-pass SAR interferometer features flexible baseline selection enabling the acquisition of highly accurate cross-track interferograms not impacted by temporal decorrelation and atmospheric disturbances. Beyond the global DEM, several secondary mission objectives based on alongtrack interferometry as well as new bistatic and multistatic SAR techniques have been defined.

TanDEM-X: A radar interferometer with two formation-flying satellites

TanDEM-X (TerraSAR-X add-on for Digital Elevation Measurements) is an innovative formation-flying radar mission that opens a new era in spaceborne radar remote sensing. The primary objective is the acquisition of a global digital elevation model (DEM) with unprecedented accuracy (12m horizontal resolution and 2m relative height accuracy). This goal is achieved by extending the TerraSAR-X synthetic aperture radar (SAR) mission by a second, TerraSAR-X like satellite (TDX) flying in close formation with TerraSAR-X (TSX). Both satellites form together a large single-pass SAR interferometer with the opportunity for flexible baseline selection. This enables the acquisition of highly accurate cross-track interferograms without the inherent accuracy limitations imposed by repeat-pass interferometry due to temporal decorrelation and atmospheric disturbances. Besides the primary goal of the mission, several secondary mission objectives based on along-track interferometry as well as new bistatic and multistatic SAR techniques have been defined, representing an important and innovative asset of the TanDEM-X mission. TanDEM-X is implemented in the framework of a public–private partnership between the German Aerospace Center (DLR) and EADS Astrium GmbH. The TanDEM-X satellite was successfully launched in June 2010 and the mission started its operational data acquisition in December 2010. This paper provides an overview of the TanDEM-X mission and summarizes its actual status and performance. Furthermore, results from several scientific radar experiments are presented that show the great potential of future formation-flying interferometric SAR missions to serve novel remote sensing applications.

A range-dependent autofocus algorithm based on the Tikhonov regularization method

Phase Gradient Autofocus (PGA) is an algorithm developed to estimate phase errors in synthetic aperture radar (SAR) images. It is widely used in SAR image processing and has been shown to be very robust on a variety of imagery and phase error functions. Original PGA makes a narrow beam assumption, which is valid for most SAR systems. But it is known that the narrow beam assumption is not valid for large swath or low-altitude mode SAR, where range-dependent phase errors need to be compensated. Some PGA-based range-dependent autofocus algorithms were proposed to deal with this problem, but during raw data processing, we found that there are ill-posed problems in the linear motion error estimation model that will affect the accuracy of the estimation. In this article, combining the Tikhonov regularization (TR) method with phase gradient estimation, a novel autofocus algorithm is proposed to deal with the ill-posed problem in estimation. Real data processing demonstrates that the new method avoids the effect of parameter errors, estimates the range-dependent phase errors more precisely and finally leads to better focusing quality.

Large SAR Antenna Deployable Structure Design and Optimization

Remote sensing satellites equipped with large synthetic aperture radar (SAR) can image the earth in all weather and lighting conditions. For high packaging efficiency in launch and precise configuration on orbit, deployable mechanisms are designed to deploy the large SAR antenna panels. For the two-panel antenna, a six-bar-linkage deployable driving mechanism is designed. According to the design, a parameterized dynamic model is built in ADAMS software with secondary development technology to obtain its dynamics characteristics through simulation analysis. To improve the dynamic characteristics and the precision of deployment design of experiments and optimizations were carried through in this paper.

Geo-referencing of continental-scale JERS-1 SAR mosaics based on matching homologous features with a digital elevation model: theory and practice

An effective method for a posteriori ortho-rectification of continental-scale synthetic aperture radar (SAR) mosaics using a digital elevation model (DEM) has been developed. The method is based on homologous feature matching between the DEM and a simulated SAR image. The simulated image is derived from the radar-viewing geometry, topographic information and contextual information provided by the Shuttle Radar Topography Mission (SRTM), shorelines and water bodies database (SWBD) and GeoCover Landsat mosaics. Two large L-band SAR mosaics (the global boreal forest mapping (GBFM) Siberia mosaic and the global rain forest mapping (GRFM) Africa mosaic), assembled from the Japanese Earth Resources Satellite-1 (JERS-1) data, were accurately geo-referenced and ortho-rectified. The GRFM Africa mosaic was also radiometrically corrected for topographic effects. The accurate co-registration with the DEM allows for improved classification methods based on the combination of SAR backscatter with terrain features. Comparison of the revised GBFM and GRFM mosaics with a forthcoming set of continental-scale mosaics assembled from the Advanced Land Observing Satellite (ALOS) Phased Array L-band Synthetic Aperture Radar (PALSAR) data will offer a unique possibility for change detection studies over the Tropical and Boreal forest zones with a temporal spacing of some 10 years.

Synthetic aperture radar satellite data for offshore wind assessment: A strategic sampling approach

Many studies have shown that the synthetic aperture radar (SAR) approach is an adequate tool for wind assessment and mapping in coastal and offshore areas. However, a large SAR scene sample is required to precisely calculate wind statistics. The proposed sampling algorithm, called strategic sampling, is based on a long term data series (e.g. QuikSCAT) from a nearby location to accurately evaluate the wind statistics with a reasonable number of wind observations (<45). Strategic sampling methodology relies on the complementarity of two databases: the SAR satellite RADARSAT-1 and the QuikSCAT scatterometer were chosen. Random sampling, on the other hand, requires 75 and 225 wind observations to estimate, respectively, the average wind speed and mean power output of a modern wind turbine, with an error less than 10% for a 90% confidence level. This represents a difference of at least two to seven times more SAR scenes for random sampling than for strategic sampling. The SAR sample selected via strategic sampling at a specific offshore location can then be used for wind predictions in neighboring regions. Finally, the strategic sampling algorithm is used to estimate the minimum number of SAR images for a coastal region located in eastern Canada.

Interferometric Synthetic Aperture Radar (SAR) Missions Employing Formation Flying

This paper presents an overview of single-pass interferometric Synthetic Aperture Radar (SAR) missions employing two or more satellites flying in a close formation. The simultaneous reception of the scattered radar echoes from different viewing directions by multiple spatially distributed antennas enables the acquisition of unique Earth observation products for environmental and climate monitoring. After a short introduction to the basic principles and applications of SAR interferometry, designs for the twin satellite missions TanDEM-X and Tandem-L are presented. The primary objective of TanDEM-X (TerraSAR-X add-on for Digital Elevation Measurement) is the generation of a global Digital Elevation Model (DEM) with unprecedented accuracy as the basis for a wide range of scientific research as well as for commercial DEM production. This goal is achieved by enhancing the TerraSAR-X mission with a second TerraSAR-X like satellite that will be launched in spring 2010. Both satellites act then as a large single-pass SAR interferometer with the opportunity for flexible baseline selection. Building upon the experience gathered with the TanDEM-X mission design, the fully polarimetric L-band twin satellite formation Tandem-L is proposed. Important objectives of this highly capable interferometric SAR mission are the global acquisition of three-dimensional forest structure and biomass inventories, large-scale measurements of millimetric displacements due to tectonic shifts, and systematic observations of glacier movements. The sophisticated mission concept and the high data-acquisition capacity of Tandem-L will moreover provide a unique data source to systematically observe, analyze, and quantify the dynamics of a wide range of additional processes in the bio-, litho-, hydro-, and cryosphere. By this, Tandem-L will be an essential step to advance our understanding of the Earth system and its intricate dynamics. Enabling technologies and techniques are described in detail. An outlook on future interferometric and tomographic concepts and developments, including multistatic SAR systems with multiple receivers, is provided.

Using Multibaseline InSAR to Recover Layovered Terrain Considering Wideband Array Problem

This letter deals with the problems of retrieving height and synthetic aperture radar (SAR) reflectivity of layovered terrain using multibaseline SAR interferometry (InSAR). In particular, we focus on the wideband array problem caused by practically large InSAR arrays and high-resolution SAR images, i.e., the problem of signal envelope misalignment, which is neglected in the work by Gini We propose two methods to eliminate or mitigate the effect of envelope misalignment, one called the aligning method and the other called the joint range cell processing method. In the aligning method, we align each signal envelope for each searched height of the layovered components (i.e., ground resolution cells with different altitudes) during searching procedure. The joint range cell processing method jointly processes the neighboring cells in range to estimate the parameters of layovered components so that the effect of the envelope misalignment can be mitigated. Theoretical analysis and computer simulation results show that both methods have the ability to provide accurate estimation of the heights and radar reflectivities of multiple layovered resolution cells in the presence of large envelope misalignments.

Parallel Processing Strategies for Large SAR Image Data Sets in a Distributed Environment

Image processing of synthetic aperture radar (SAR) images is challenging due to distributed storage of input data sets and since appropriate algorithms are complex and time-consuming. Computers able to process these data in acceptable time usually are not at user's site. Our Concurrent and Distributed Image Processing (CDIP) system overcomes these problems and provides a platform-independent, transparent environment based on Java, CORBA and NetSolve. Users query a broker to find remote, high-performance servers on which the algorithms actually are executed. Key algorithms like image matching and Shape-from-Shading were parallelized mainly using MPI, and ported onto suitable computer architectures. Our experiments showed that all algorithms perform well, and they further proved the concept of CDIP to be beneficial: Usability of all integrated algorithms was significantly improved, mainly due to less user-centered network traffic, simple access to supercomputers, the creation of method sequences, and easy-to-use and well maintained algorithms.

A Massively Parallel Digital Processor for Spotlight Synthetic Aperture Radar

Near-real-time digital formation of large synthetic aper ture radar (SAR) images requires the computational throughput that only a dedicated special processor or a massively parallel computer can offer. This article documents the implementation of digital spotlight SAR processing components on three commercially avail able massively parallel computers: the Connection Ma chine (CM-2), the nCUBE 2, and the Intel iPSC/860. The three basic spotlight SAR processing components, the polar reformatter, the two-dimensional fast Fourier transformation, and autofocus, are briefly discussed to provide a technical background for the implementation issues that apply to massively parallel computers. As pects of the SAR components that can exploit features of a SIMD or MIMD architecture are also presented. Finally, timing test results on various computers are provided for evaluation and comparison.