Maurizio di Bisceglie

Processing of synthetic Aperture Radar data with GPGPU

Synthetic aperture radar processing is a complex task that involves advanced signal processing techniques and intense computational effort. While the first issue has now reached a mature stage, the question of how to produce accurately focused images in real-time, without mainframe facilities, is still under debate. The recent introduction of general-purpose graphic processing units seems to be quite promising in this view, especially for the decreased per-core cost barrier and for the affordable programming complexity. The authors explain, in this work, the main computational features of a range-Doppler Synthetic Aperture Radar (SAR) processor, trying to disclose the degree of parallelism in the operations at the light of the CUDA programming model. Given the extremely flexible structure of the Single Instruction Multiple Threads (SIMT) model, the authors show that the optimization of a SAR processing unit cannot reduce to an FFT optimization, although this is a quite extensively used kernel. Actually, it is noticeable that the most significant advantage is obtained in the range cell migration correction kernel where a complex interpolation stage is performed very efficiently exploiting the SIMT model. Performance show that, using a single Nvidia Tesla-C1060 GPU board, the obtained processing time is more than fifteen time better than our test workstation.

GNSS-R Altimeter Based on Doppler Multi-looking

Measuring ocean mesoscale variability is one of the main objectives of next generation satellite altimeters. Current radar altimeters make observations only at the nadir sub-satellite ground track, which is not sufficient to sample the ocean surface with the required spatial and temporal sampling. The GNSS-R concept has been proposed as an alternative observation system in order to overcome this limitation, since it allows performing altimetry along several points simultaneously over a very wide swath. Latest proposed GNSS-R altimeter configurations allow measuring sea height with an accuracy of few decimeters over spatial scales of 50-100 km, by means of a single-pass. This paper proposes an innovative processing and retracking concept for GNSS-R altimeters based on the acquisition of the full delay-Doppler map (DDM), which allows to acquire multiple waveforms at different Doppler frequencies, whose footprints are located outside the typical pulse-limited region. The proposed processing adapts the Synthetic Aperture Radar (SAR) delay-Doppler concept of spaceborne radar altimeters for use in a GNSS-R system. This processing yields additional multi-look with respect to conventional GNSS-R concepts and translates into an improvement of the altimetry performance estimated to be at least 25%-30%, and even higher, depending on the wanted along-track spatial resolution. The proposed processing can also provide measurements with high spatial resolution at best possible performance, and more generally, offers various possibilities for optimal trade-off between spatial-resolution and height estimation accuracy.

The role of cooperative information spreading paradigms for Smart Grid monitoring

The large-scale deployment of the Smart Grid paradigm will support the evolution of conventional electrical power systems toward active, flexible and self-healing web energy networks composed of distributed and cooperative energy resources. In this field, the application of traditional hierarchical monitoring paradigms has some disadvantages that could hinder their application in Smart Grids where the constant growth of grid complexity and the need for massive pervasion of Distribution Generation Systems (DGS) require more scalable, more flexible control and regulation paradigms. To overcome these challenges, this paper proposes the concept of a decentralized non-hierarchical monitoring architecture based on intelligent and cooperative smart entities. These devices employ traditional sensors to acquire local bus variables and run information spreading algorithms in order to assess the main variables describing the global grid state. Two average consensus algorithms are compared : Kuramoto and Gossiping respectively and important remarks are underlined.

Stochastic Modeling and Simulation of Delay–Doppler Maps in GNSS-R Over the Ocean

A stochastic model for delay-Doppler map (DDM) simulation from global navigation satellite system reflectometry (GNSS-R) systems is presented. The aim is to provide a useful tool for investigating the performance of estimation and retrieval algorithms that are based on finite time series. The scattering inside a delay-Doppler cell is modeled as the sum of a random number of contributions from inner specular points that, as the mean number of such contributions gets larger, tends to a compound-Gaussian process. The statistical averages reveal that the model is fully consistent with the previous results provided by Zavorotny and Voronovich. Numerical simulations of large airborne and spaceborne DDMs are easily practicable and show the clear patterns due to signal fluctuations and thermal noise that fade away when the number of averaged observations increases. Comparisons with TechDemoSat-1 data show that the model and the simulation scheme provide accurate realizations of the onboard-processed DDMs.

Delay super resolution for GNSS-R

Global Navigation Satellite System Reflectometry (GNSS-R) is a new approach for earth observation using signals of opportunity in a bistatic configuration. The system, in the configuration of interest, exploits the 10 bits PN sequence of the GPS system to generate Delay/Doppler maps that are useful for monitoring the sea state. One of the open problems is that the achievable delay and Doppler resolution is limited by the GPS waveform. We will show that, exploiting a MUSIC-based algorithm, it is possible to move further the limits for the achievable delay and Doppler resolution.

Multimodel CFAR Detection in Foliage Penetrating SAR Images

A multimodel approach for constant false alarm ratio (CFAR) detection of vehicles through foliage in foliage penetrating synthetic aperture radar images is presented. Extreme value distributions and location scale properties are exploited to derive an adaptive CFAR approach that is able to cope with different forest densities. Performance analysis on real data is carried out to estimate the detection and false alarm probabilities in the presence of a ground truth.

The Hyperspectral Unmixing of Trace-Gases From ESA SCIAMACHY Reflectance Data

Atmospheric concentrations of trace-gases are retrieved from hyperspectral data using a blind source separation method. The algorithm relies on the assumption that the absorption cross sections of the gas components are weakly dependent on the overall atmospheric background. The unmixing of contributions from the logarithm of the spectral reflectance provides estimates of both individual trace-gas absorption cross sections and their concentrations. In the experimental analysis, nadir reflectances received by SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY are considered in two scenarios: the sulfur dioxide emissions from a volcanic eruption and the nitrogen dioxide production from anthropogenic pollution. In both cases, it is demonstrated that the algorithm performs very similarly to the Differential Optical Absorption Spectroscopy algorithm but with very little ancillary information.

Simulation of TechDemoSat-1 Delay-Doppler Maps for GPS Ocean Reflectometry

The increasing diffusion of spaceborne GNSS reflectometry as a remote sensing technique has motivated, recently, the development of end-to-end delay-Doppler map simulators. We present here the most relevant issues involved in the design of a simulator for applications of ocean wind remote sensing with a conventional acquisition technique. The approach is based on the stochastic Monte Carlo simulation of the scattered signal followed by a 2-D convolution and filtering accounting for the Doppler processing implemented on the TechDemoSat-1 platform. Simulation accuracy is assessed in the validation setup, where ensemble runs are supported by the estimation of the empirical cumulative distribution function.

A Location Scale Based CFAR Detection Framework for FOPEN SAR Images

The problem of target detection in a complex clutter environment, with Constant False Alarm Ratio (CFAR), is addressed in this paper. In particular an algorithm for CFAR target detection is applied to the context of FOliage PENetrating (FOPEN) Synthetic Aperture Radar (SAR) imaging. The extreme value distributions family is used to model the data and exploiting the location-scale property of this family of distributions, a multi-model CFAR algorithm is derived. Performance analysis on real data confirms the capability of the developed framework to control the false alarm probability.

CFAR detection of fire events in non-homogeneous non-Gaussian background

The problem of CFAR detection of thermal anomalies is discussed in this paper for multiple-band, non-homogeneous, non-Gaussian scenario. Data from 4- and 11 μm bands are projected onto a new coordinates system provided by the decorrelating Principal Component Analysis. A robust PCA is obtained by using the Minimum Covariance Determinant estimator for the covariance matrix that acts by strongly reducing the influence of thermal anomalies. A statistical validation has been carried out through a large bulk of data testing that the first and the second data component well fit a Gaussian and a Log-Normal distribution, respectively. Thus the first component directly satisfies the Location Scale property required for a CFAR detection, while for the second component the same property may be satisfied after a logarithmic transformation. A CFAR detection is applied to projected data and results of the two detectors are combined into a fusion block. Thanks to independence of uncorrelated data the two single detections can be combined with an AND or OR rule, and the overall false alarm probability is the product or the sum of corresponding per-channel probabilities. The results obtained in both cases are compared with the standard NASA-DAC-MOD14 product as a benchmark.