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Barla M.,Polytechnic University of Turin | Antolini F.,Polytechnic University of Turin | D'Aria D.,Aresys srl | Amoroso G.,Aresys srl
Engineering Geology | Year: 2017

This paper describes the use of the discontinuous Ground-Based Interferometric Synthetic Aperture Radar technique (GBInSAR) to monitor the displacement of the Comba Citrin landslide in the North Western Italian Alps. Two GBInSAR surveys were carried out respectively during the summer and the fall of 2015 separated by a temporal baseline of 63 days. For each GBInSAR survey, which lasted respectively 166.2 h (6 dd, 22 h, 12′) and 238.3 h (9 dd, 22 h, 18′), two sets of 139 and 275 SAR images were acquired. After the selection of a specific stack of Persistent Scatterers, the SAR images of each survey were analyzed separately and in combination with the images of the other survey to detect the possible displacements occurred both in every single survey as well as in the elapsed time between the two different campaigns. The displacement maps showed that two different sectors of the monitored slope were affected by millimetres to centimetres movements during the monitoring period. The results obtained for the Comba Citrin landslide show that the discontinuous GBInSAR can be reliably adopted to monitor the displacement of landslides moving at an average rate of few centimetres per year. © 2016 Elsevier B.V.


Pastina D.,University of Rome La Sapienza | Colone F.,University of Rome La Sapienza | Martelli T.,University of Rome La Sapienza | Falcone P.,ARESYS SRL
IEEE Transactions on Vehicular Technology | Year: 2015

In this paper, we examine the potentiality of passive coherent location (PCL) for indoor area monitoring. In particular, we show that Wi-Fi transmissions can be successfully exploited as waveforms of opportunity to perform moving target detection and localization based on the passive radar principle. Moreover, we investigate the advanced capability to obtain high-resolution cross-range profiles of the observed targets via inverse-synthetic-aperture-radar (ISAR) techniques. To these purposes, appropriate processing techniques are introduced to cope with the limitations resulting from the indoor applications such as the strong returns from the stationary scene and the high density of potential targets. The proposed system concept has been tested against both simulated and real data sets. The reported results clearly show that using few receiving channels connected to properly dislocated antennas allows an accurate target localization and tracking. In addition, reliable and stable profiles are obtained for the targets moving in the surveyed scene, which might fruitfully feed a classification stage. This contributes to the demonstration of the effective applicability of the passive radar concept for improving internal and external security of private/public premises. © 1967-2012 IEEE.


Colone F.,University of Rome La Sapienza | Pastina D.,University of Rome La Sapienza | Falcone P.,University of Rome La Sapienza | Falcone P.,ARESYS Srl | Lombardo P.,University of Rome La Sapienza
IEEE Transactions on Geoscience and Remote Sensing | Year: 2014

This paper presents an effective signal processing scheme to track moving vehicles and to obtain their cross-range profiles with a passive bistatic radar (PBR) based on the signals of opportunity emitted by a WiFi router. While the target detection using WiFi-based PBR has already been studied by the authors, this paper focuses on the targets moving with a low radial velocity component. These are especially interesting since they might have a reasonable cross-range velocity component, which allows us to apply inverse synthetic aperture radar (ISAR) techniques to provide a high-resolution cross-range profile. A specific problem for these targets is the presence of possibly strong echoes from the stationary background (clutter), which tend to mask their contributions. In such cases, the standard Doppler processing does not help in separating the targets from this clutter. Therefore, appropriate clutter cancellation schemes are applied, and their effectiveness and impact are analyzed both on the tracking and on the ISAR profiling. An appropriate ISAR scheme for cross-range profiling is introduced, tailored for the typical short-range and possibly bistatic surveillance scenarios of the WiFi-based PBR; this scheme comprises the automatic estimation from the data of the target motion components up to a higher order than in usual long-range imaging and their compensation. The reliability of the obtained profiles is also investigated, for both the monostatic and bistatic cases, which is essential both for the vehicle size/characteristics estimation and for the automatic recognition schemes based on vehicle databases. The results obtained using an experimental setup developed and fielded at the University of Rome "La Sapienza," Rome, Italy, show that the considered approach is effective and that the obtained cross-range profiles achieved by ISAR processing with WiFi-based passive radar are quite reliable both in the monostatic and bistatic cases. © 2013 IEEE.


Fauvel M.,French National Institute for Agricultural Research | Chanussot J.,CNRS GIPSA Laboratory | Benediktsson J.A.,University of Iceland | Villa A.,Aresys Srl | Villa A.,Polytechnic of Milan
Pattern Recognition | Year: 2013

The classification of high dimensional data with kernel methods is considered in this paper. Exploiting the emptiness property of high dimensional spaces, a kernel based on the Mahalanobis distance is proposed. The computation of the Mahalanobis distance requires the inversion of a covariance matrix. In high dimensional spaces, the estimated covariance matrix is ill-conditioned and its inversion is unstable or impossible. Using a parsimonious statistical model, namely the High Dimensional Discriminant Analysis model, the specific signal and noise subspaces are estimated for each considered class making the inverse of the class specific covariance matrix explicit and stable, leading to the definition of a parsimonious Mahalanobis kernel. A SVM based framework is used for selecting the hyperparameters of the parsimonious Mahalanobis kernel by optimizing the so-called radius-margin bound. Experimental results on three high dimensional data sets show that the proposed kernel is suitable for classifying high dimensional data, providing better classification accuracies than the conventional Gaussian kernel. © 2012 Elsevier Ltd.


Villa A.,Aresys Srl | Villa A.,Polytechnic of Milan | Chanussot J.,CNRS GIPSA Laboratory | Benediktsson J.A.,University of Iceland | And 2 more authors.
Pattern Recognition | Year: 2013

The problem of structure detection and unsupervised classification of hyperspectral images with low spatial resolution is addressed in this paper. Hyperspectral imaging is a continuously growing area in remote sensing applications. The wide spectral range, providing a very high spectral resolution, allows the detection and classification surfaces and chemical elements of the observed image. The main problem of hyperspectral images is that the spatial resolution can vary from a few to tens of meters. Many factors, such as imperfect imaging optics, atmospheric scattering, secondary illumination effects and sensor noise cause a degradation of the acquired image quality, making the spatial resolution one of the most expensive and hardest to improve in imaging systems. Due to such a constraint, mixed pixels, e.g., pixels containing mixture of different materials, are quite common in hyperspectral images. In this work, we exploit the rich spectral information of hyperspectral images to deal with the problem. Two methods, based on the concept of spectral unmixing and unsupervised classification, are proposed to obtain thematic maps at a finer spatial scale in a totally unsupervised way. Experiments are carried out on one simulated and two real hyperspectral data sets and clearly show the comparative effectiveness of the proposed method with respect to traditional unsupervised methods, both for classification and detection of spatial structures. © 2012 Elsevier Ltd.


Guccione P.,Polytechnic of Bari | Belotti M.,Aresys Srl | Giudici D.,Aresys Srl | Monti Guarnieri A.,Polytechnic of Milan | Navas-Traver I.,European Space Agency
IEEE Transactions on Geoscience and Remote Sensing | Year: 2015

This paper concerns the performance of the flexible dynamic block adaptive quantizer (FDBAQ), which is the onboard data compression scheme used by Sentinel-1 (S-1), i.e., the C-band synthetic aperture radar (SAR) constellation whose first satellite (Sentinel-1A) has been launched on April 3, 2014. The data rate that results from the fine resolution and the wide swath of S-1 would exceed, without data compression, the S-1 hardware limitations. The FDBAQ has been proposed as an efficient method to reduce the instrument data rate and limit the onboard storage requirement. The capabilities of such a compression scheme have not been tested on real data before. Preflight simulation and analysis were based on a simplified processing scheme and radar backscattering information taken from past missions. The purpose of this paper is to present the first results of the analysis of real acquisitions, comprising thousands of products, in every S-1 acquisition mode, acquired during and after the commissioning phase. Advantages and limits are presented in detail, comparing FDBAQ and the traditional block adaptive quantizer (BAQ) compression scheme, in terms of quantization noise level, signal-to-noise ratio, and average bit and data rates. © 2015 IEEE.


Scagliola M.,ARESYS SRL | Dinardo S.,Serco | Fornari M.,European Space Agency
International Geoscience and Remote Sensing Symposium (IGARSS) | Year: 2015

One of the main benefits of the along-track processing in Synthetic Aperture Radar altimetry [1] is the speckle reduction that is achieved by averaging all the observations accumulated for a same scattering area. Being the different observations obtained by looking at the same scattering area from different positions of the instrument along the orbit, they result to be modulated by the along-track antenna pattern. By compensating the along-track antenna pattern before averaging, a higher speckle reduction can be achieved. This paper is aimed at presenting this processing method and at evaluating the possible improvement in the sense of the effective number of looks and of the precision of the physical parameters retrieved from the power waveforms. © 2015 IEEE.


Adamo A.,Aresys Srl | Mazzucchelli P.,Aresys Srl | Bienati N.,ENI S.p.A
International Geoscience and Remote Sensing Symposium (IGARSS) | Year: 2015

Seismic data usually show irregular spatial sampling because of cable feathering (for marine acquisitions) or physical obstacles in acquisition area (for land surveys). Seismic traces can be also irregularly distributed because of missing or noisy recordings and sensor faults. In recent literature, matrix and tensor rank optimization have been applied to achieve seismic data interpolation and to attenuate unstructured additive noise. In fact, low-rank components can capture the local features of the recorded data, such as envelope and slopes of the events. In this work, we derive a novel interpolation technique based on the low-rank approximation of matrices and tensors, which can interpolate irregularly sampled seismic data onto an arbitrary output geometry. Results on real data prove the feasibility of the proposed approach. © 2015 IEEE.


Mapelli D.,Aresys S.r.l. | Giudici D.,Aresys S.r.l.
European Space Agency, (Special Publication) ESA SP | Year: 2016

Oscillator phase noise level is negligible for a monostatic Synthetic Aperture Radar (SAR) but can severely worsen the performances of a bistatic SAR. In bistatic SAR systems, there is no cancellation of low frequency phase errors as in monostatic SAR, where the same oscillator is used for both modulation and demodulation. In bistatic systems, uncompensated phase noise may bring about consequences on SLC data and phase-based applications (e.g. interferometry). Our research, focuses on the possibility of retrieving the phase synchronization between the two local Ultra Stable Oscillators (USO), using the direct signal. In addition, we present here an alternative approach that, directly operating on SAR data, does not require any further complexity of SAOCOM-CS receiver. The actual benefits of each synchronization method are measured evaluating the residual phase noise.


Scagliola M.,ARESYS SRL | Fornari M.,European Space Agency | Bouffard J.,Earth Observation Directorate
European Space Agency, (Special Publication) ESA SP | Year: 2016

One of the main benefits of the along-trackprocessing in Synthetic Aperture Radar altimetry [1]is the speckle reduction that is achieved by averagingall the observations accumulated for a same scatteringarea. As a figure of merit to evaluate the residualspeckle on the multilooked power waveform, theEquivalent Number of Looks (ENL) is usually adopted[6].In this paper it is proposed a theoretical characterizationfor ENL, which allows quantifying the specklereduction that is achieved on the multilooked waveformfrom a SAR altimeter. The proposed characterization ofENL has been verified using CryoSat data [2] and it hasbeen exploited to understand how the systemparameters, the geophysical parameters and the Level1ground processing may affect the speckle reduction.

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