Giuseppe Ruello

SAR raw signal simulation for urban structures

A synthetic aperture radar (SAR) raw signal simulator for urban scenes is presented along with models it employs to compute the backscattered field and to account for the imaging radar sensor characteristics. Urban areas are represented as a set of dielectric buildings placed over a random rough nonflat dielectric terrain. The adopted models allow evaluation of the raw signal on a sound physical and mathematical background: the scattering model employs the Kirchhoff approach appropriately extended to include multiple-reflection effects, and the radar model operates in the two-dimensional Fourier transformed domain. Details to assess how and why the simulator is also efficient with respect to the computational time are provided. In addition, relevant examples are discussed to show the simulator potentialities and assess the validity of the main results. It is shown that the simulator is able to quantitatively assess performances of SAR sensors over urban structures. The proposed simulator turns out to be also useful to train numerical schemes devoted to feature extraction, and to test any specific SAR processing technique. Comments for further developments of the simulation tool are presented.

SAR raw signal simulation of oil slicks in ocean environments

Synthetic aperture radar (SAR) raw signal simulation is a powerful tool for design of oil slick detection and interpretation systems. In this paper, the ocean simulation issues are presented, and the main problems relating to the oil presence on the sea surface are treated. Attention is focused on the electromagnetic side of the problem, taking account of the sensor signatures, the dielectric, physical-chemical, and geometric nature of the oil slick, and the environmental conditions. The presented SAR simulator is based on an ocean model and an oil slick model. The former makes use of multiscale description of the ocean surface: the distributed surface model for the SAR-ocean interaction is considered by taking into account the nonlinear hydrodynamic effect for the water particle movement. The latter model implements a modification of the ocean spectrum, based on the Marangoni theory and accounting for the nonlinear wave interaction mechanism. However, the proposed SAR raw signal simulator is modular and flexible, thus allowing other possible physical models for modeling the oil slick effect over the ocean spectrum. Meaningful SAR simulation experiments are presented and discussed, elucidating the role of difference on pollutants, oil thickness, wind speed and direction, incident wavelength and angle and other radar parameters. Validation of the simulator is also presented by comparison with experimental data. A striking conclusion of the paper is that higher order moments (from the second on) of oil slick SAR image statistics are quite different compared to those pertinent to an equivalent wind speed decrease on the imaged area. This suggests a convenient way to define new appropriate oil slick signatures.

Efficient spotlight SAR raw signal simulation of extended scenes

Synthetic aperture radar (SAR) raw signal simulation is a powerful tool for designing new sensors, testing processing algorithms, planning missions, and devising inversion algorithms. In this paper, a spotlight SAR raw signal simulator for distributed targets is presented. The proposed procedure is based on a Fourier domain analysis: a proper analytical reformulation of the spotlight SAR raw signal expression is presented. It is shown that this reformulation allows us to design a very efficient simulation scheme that employs fast Fourier transform codes. Accordingly, the computational load is dramatically reduced with respect to a time-domain simulation and this, for the first time, makes spotlight simulation of extended scenes feasible.

A Novel Approach for Disaster Monitoring: Fractal Models and Tools

In this paper, we present a complete framework to support the monitoring of natural and man-made disasters by means of synthetic aperture radar (SAR) images. The fractal geometry is the most appropriate mathematical instrument in describing the irregularity of a natural observed scene, by means of few effective and reliable parameters. Therefore, fractal concepts can be used to model and identify geometrical changes that occurred in areas hit by disasters. We present an overall framework employing fractal-based models, algorithms, and tools to support the identification of natural area changes due to natural or man-made disasters. Such a framework includes an algorithm used to extract fractal parameters from a 2-D signal, a fractal interpolation tool, and a SAR raw-signal simulator. The combined use of these tools provides an innovative instrument for disaster monitoring applications. In this paper, we implement the fractal framework to obtain a relation between the fractal parameters of a SAR image and those of the relative imaged area. In addition, a case study is discussed, showing the potentiality of our framework for flooding detection

Building feature extraction via a deterministic approach: application to real high resolution SAR images

Interpretation of high resolution SAR (synthetic aperture radar) images is still a hard task, especially when man-made objects crowd the scene under detection. This paper contributes to the analysis of this kind of data by adopting an approach, based on a scattering model, for the retrieval of buildings height from real SAR images and presenting first numerical results.

Efficient Simulation of hybrid stripmap/spotlight SAR raw signals from extended scenes

The hybrid stripmap/spotlight mode for a synthetic aperture radar (SAR) system is able to generate microwave images with an azimuth resolution better than the one achieved in the stripmap mode and a ground coverage better than the one of the spotlight mode. In this paper, time- and frequency-domain-based procedures to simulate the raw signal in the hybrid stripmap/spotlight mode are presented and compared. We show that a two-dimensional Fourier domain approach, although highly desirable for its efficiency, is not viable. Accordingly, we propose a one-dimensional (1-D) range Fourier domain approach, followed by 1-D azimuth time-domain integration. This method is much more efficient than the time-domain one, so that extended scenes can be considered. In addition, it involves approximations usually acceptable in actual cases. Effectiveness of the simulation scheme is assessed by using numerical examples.

Scattering From Layered Structures With One Rough Interface: A Unified Formulation of Perturbative Solutions

In this paper, we investigate analytically the connection between the existing first-order small perturbation method solutions for the scattering from a layered structure with one rough interface. First of all, by using effectively the concept of generalized reflection coefficients, we cast the existing models in a unified more compact formulation and point out the connection between the different analytical solutions. The obtained reformulations of the available analytical solutions allow us to subsequently prove the consistency of the considered models. Finally, a suitable expansion is performed that leads us to understand the physical meaning of the analytical expressions. The obtained unified formulation also opens the way toward a general closed-form solution for the problem of scattering by a layered structure with an arbitrary number of corrugated interfaces.

Filtering of Azimuth Ambiguity in Stripmap Synthetic Aperture Radar Images

Due to the specific characteristics of the SAR system, peculiar artifacts can appear on SAR images. In particular, finite pulse repetition frequency (PRF) and nonideal antenna pattern give rise to azimuth ambiguity, with the possible presence of “ghosts” on the image. They are due to the replica of strong targets located outside of the antenna main beam, superposed onto low intensity areas of the imaged scene. In this paper, we propose a method for the filtering of azimuth ambiguities on stripmap SAR images, that we name “asymmetric mapping and selective filtering” (AM&SF) method. Our framework is based on the theory of selective filtering and on a two-step procedure. In the first step, two asymmetric filters are used to suppress ambiguities due to each sidelobe of the antenna pattern, and the ratios between the original and filtered images are used to produce two maps of the ambiguity-affected areas (one for each sidelobe). In the second step, these maps are used to produce a final image in which only the areas affected by the ambiguities are replaced by their filtered (via the proper of the two filters) versions. The proposed method can be employed in situations in which similar approaches fail, and it has a smaller computational burden. The framework is positively tested on TerraSAR-X and COSMO/SkyMed SAR images of different marine scenes.

Synthesis, construction, and validation of a fractal surface

Fractal geometry provides reliable models to describe geometrical properties of natural surfaces. Therefore, their use in the electromagnetic scattering methods deserves careful research. In order to have complete insight into the phenomenon, a measurement campaign on a fractal surface in a controlled environment is a key step. In this paper, we propose a technique for building a fractal surface that can be used for electromagnetic scattering evaluation purposes. The surface characteristics are imposed by computer synthesizing a bandlimited Weierstrass-Mandelbrot function, whose actual shape is constructed by means of a cheap innovative technique: the synthesized surface is made from cardboard covered with aluminum foil, which gives a conducting surface and creates the micro-scale conditions, useful to represent manufacturing errors. Statistics of the overall surface shape are then measured, analyzed and compared with the imposed ones, providing and verifying the rationale for a fully controlled surface to be applied in any kind of experiment on natural surfaces.

Effectiveness of high-resolution SAR for water resource management in low-income semi-arid countries

This article presents an efficient framework and a sustainable pilot project on the effective use of spaceborne synthetic aperture radar (SAR) in low-income countries and semi-arid climatic contexts. The technical efficiency was pursued by integrating SAR models and hydrological assessment methods; the socio-economical sustainability was guaranteed by the joint work of scientists, technicians, and volunteers. The pilot project was developed in the Yatenga region, a Sahelian area in northern Burkina Faso. In particular, an original development of SAR interferometry algorithms was tailored to the peculiar climate, the soil characteristics, and the land cover of the semi-arid regions. A digital elevation model (DEM) was derived, and an original approach based on the use of SAR amplitude images is proposed for its validation. The achieved resolution (9 m) is significantly better than that of the previously available DEMs in the study area (30 m). Based on the DEM, the soil sedimentation rate of small reservoirs was estimated together with the average soil loss in the contributing catchments due to the erosion process. A multi-temporal filter was implemented on the SAR images for monitoring of water intake volume in small reservoirs, and its seasonal evolution. The developed tools provide an innovative contribution for the improvement of water resource management in the study area. This approach is repeatable and scalable to suit situations with similar economic and climatic conditions.