Matteo Pardini

Tandem-L: A Highly Innovative Bistatic SAR Mission for Global Observation of Dynamic Processes on the Earth's Surface

Tandem-L is a proposal for a highly innovative L-band SAR satellite mission for the global observation of dynamic processes on the Earths surface with hitherto unparalleled quality and resolution. It is based on the results of a pre-phase A study which started in 2013 and is currently undergoing a phase-A study. Thanks to the novel imaging techniques and the vast recording capacity with up to 8 terabytes/day, it will provide vital information for solving pressing scientific questions in the biosphere, geosphere, cryosphere, and hydrosphere. By this, the new L-band SAR mission will make an essential contribution for a better understanding of the Earth system and its dynamics. Tandem-L will, moreover, open new opportunities for risk analysis, disaster management and environmental monitoring by employing especially designed acquisition modes and techniques in combination with a reconfigurable tandem satellite configuration and an L-band SAR instrument with advanced digital beamforming techniques.

Superresolution Differential Tomography: Experiments on Identification of Multiple Scatterers in Spaceborne SAR Data

Interest is growing in the application of coherent processing of synthetic aperture radar (SAR) data to the monitoring of complex urban or infrastructure areas. However, such scenarios are characterized by the layover phenomenon, in the presence of which conventional interferometric SAR techniques degrade or cannot operate. As a consequence, to monitor reliably a high number of ground structures, the identification, i.e., the detection and height and deformation velocity estimation, of both single and multiple scatterers interfering in the same SAR cell can be a key step. This issue is addressed here by means of differential tomography (Diff-Tomo), a recent multibaseline-multitemporal generalized interferometric framework which allows to resolve multiple moving scatterers at different heights in the same cell. In particular, superresolution adaptive Diff-Tomo is extensively tested and augmented with a new information extraction algorithm for the automated identification of the multiple scatterers. Experiments have been carried out with real C-band spaceborne data over urban areas; corresponding results are shown and discussed.

3-D SAR Tomography: The Multibaseline Sector Interpolation Approach

Multibaseline (MB) synthetic aperture radar (SAR) tomography is a promising mode of SAR interferometry, allowing full 3-D imaging of volumetric and layover scatterers in place of a single elevation estimation capability for each SAR cell However, Fourier-based MB SAR tomography is generally affected by unsatisfactory imaging quality due to a typically low number of baselines with irregular distribution. In this paper, we improve the basic elevation focusing technique by reconstructing a set of uniform baselines data exploiting in the interpolation step the ancillary information about the extension of a height sector which contains all the scatterers. This a priori information can be derived from the knowledge of the kind of the observed scenario (e.g., forest or urban). To demonstrate the concept, an imaging enhancement analysis is carried out by simulation.

On the estimation of forest vertical structure from multibaseline polarimetric SAR data

Forest characterization and biomass estimation by means of remote sensing systems are nowadays “hot topics” within the remote sensing community, given their importance in the terrestrial carbon budget. In fact, forest vertical structure is a key variable for assessing biodiversity and structural degradation and/or regeneration. Moreover, the (vertical) structure information is important as it can allow the development of accurate and robust (alometric) estimators of the forest biomass. In this paper, potentials and challenges of forest vertical structure estimation with low frequency multibaseline polarimetric synthetic aperture radar are reviewed and discussed.

SAR tomography for scene elevation and deformation reconstruction: Algorithms and potentialities

Multi-Dimensional (MultiD) SAR imaging is a recent technique, based on coherent SAR data combination, aimed to space (full-3D) and space deformation-velocity (4D) analysis. It is an extension of the concepts of SAR Interferometry and Differential Interferometry and offers new options for the analysis and monitoring of ground scenes. In this work, we discuss the current status and the results obtained by processing ERS real satellite urban data, we investigate perspectives related to the next generation multi-static satellite formations, and we show some sample results regarding 3D and 4D theoretical performance bounds. First space-time 4D analysis results obtained by processing real airborne forest data are also reported.

Sub-canopy topography estimation: Experiments with multibaseline SAR data at L-band

Synthetic aperture radar (SAR) systems in L-band and P-band are characterized by deep penetration capabilities into volumes, enabling new opportunities for the radar remote sensing of forests. In the last years, the interest has been continuously growing in the estimation of the sub-canopy topography, especially by exploiting multibaseline (possibly polarimetric) SAR data. This work intends to contribute on this topic by presenting further experiments with real L-band data about ground topography estimation and by quantifying the obtained performance. Different forest scenarios are considered. Potentials and limitations are analyzed with particular reference to a multibaseline relaxation-based algorithm.

Estimating and understanding vertical structure of forests from multibaseline TanDEM-X Pol-InSAR data

TanDEM-X (TDX) forms with TerraSAR-X (TSX) the first single-pass synthetic aperture radar (SAR) interferometer in space with polarimetric capabilities. The availability of such system allows for the first time the acquisition and analysis of X-band Pol-InSAR data from space without the disturbing effect of temporal decorrelation. After two years of mission, time series with variable baseline over the same forest sites are available, allowing to (1) explore their information content, (2) assess penetration capabilities, (3) assess scattering model assumptions, and (4) estimate vertical structure and monitor its dynamics. This paper discusses for the first time the potential of estimating forest vertical structure from spaceborne single-pass interferometers, extending classical tomographic concepts. Results of first experiments with TSX/TDX multibaseline Pol-InSAR data acquired over the Tapajos national forest (Brazil) are shown. Especially regarding tropical forests, potentials and applications of X-band for forest structure monitoring will also be discussed.

Phase calibration of multibaseline SAR data based on a minimum entropy criterion

Prior to any processing of multibaseline (MB) synthetic aperture radar (SAR) data stacks, a MB phase calibration is necessary to compensate for phase contributions due to platform motions and/or atmospheric propagation delays. Classical calibration methods rely on the detection of point-like scatterers. However, especially in natural scenarios, their final calibration performance could be impaired by the nature of the scattering and by the typical low number of baselines. In this paper, we propose a calibration method based on the minimization of the entropy of the vertical profile of the backscattered power. This allows to potentially exploit the MB SAR signal independently of the nature of the scattering. The proposed method has been tested by processing simulated and real airborne datasets of a forest stand.

Detection of scatterer multiplicity in spaceborne SAR tomography with array errors

Processing of multibaseline/multitemporal SAR data from complex urban or infrastructure areas is of increasing interest. In this framework, the detection of single and multiple layover scatterers is an important problem, for an extensive and accurate signal interpretation. Recently, an hybrid 3D adaptive tomography-complex data domain model fitting detection method has been proposed. In this work, the basic method is tested with simulated data corrupted by non-idealities, in particular residual atmospheric compensation errors. Afterwards, the analyzed effects specific of the presence of the data non-idealities are taken into account for a more robust design of a detection method based on the same principle. The effectiveness of the algorithm is experimented with real satellite C-band data.

Multiple scatterers identification in complex scenarios with adaptive differential tomography

In the last few years, the interest is increasing in the interferometric processing of multibaseline/multitemporal SAR data from complex urban or infrastructure areas. In order to locate and monitor a high number of ground structures with the lowest signal misinterpretation, the identification, i.e. the detection and height and deformation velocity estimation, of both single and multiple layover scatterers is an important step. This issue is addressed here by extensively experimenting the technique of adaptive differential tomography, a recent interferometric framework which allows to resolve multiple moving scatterers at different heights in the same SAR cell. To this aim, adaptive differential tomography is augmented with an automated information extraction algorithm. The technique has been applied to real C-band spaceborne data over an urban area. Corresponding results are discussed.