An SAR simulator of an extended three-dimensional scene is presented. It is based on a facet model for the scene, asymptotic evaluation of SAR unit response, and a two-dimensional fast Fourier transform code for the data processing. Prescribed statistics of the model account for a realistic speckle of the image. The simulator is implemented in Synthetic Aperture Radar Advance Simulators (SARAS), whose performance is described and illustrated by a number of examples

A study on sea oil spill observation by means of polarimetric synthetic aperture radar (SAR) data is accomplished. It is based on the use of a polarimetric constant false alarm rate filter to detect dark patches over SAR images. Then, the target decomposition theorem is exploited to distinguish oil spills and look-alikes. Experiments are conducted on polarimetric SAR data acquired during the SIR-C/X-SAR mission on October 1994. The data were processed and calibrated at the Jet Propulsion Laboratory, National Aeronautics and Space Administration. Results show that the new polarimetric approach is able to assist classification

In this study dual‐polarized synthetic aperture radar (SAR) measurements were used to enhance oil spill observation. The co‐polarized phase difference (CPD) was modelled and used to characterize the scattering return from oil spills and biogenic slicks. The model predicts, under low to moderate wind conditions, a larger CPD standard deviation (σ) for oil with respect to the sea, while for biogenic slicks a σ value similar to that for the sea is obtained. Experiments accomplished with multilook complex (MLC) C‐ and L‐band SAR data show that the model predictions are confirmed and that the C‐band is, as expected, to be preferred to the L‐band.

In this article, a review of polarimetric synthetic aperture radar (SAR) methods for sea oil slick observation is presented. Marine oil pollution monitoring is a topic of great applicative and scientific relevance. In this framework, the use of remotely sensed measurements is of special interest and, in particular, the SAR because of its almost all-weather and all-day imaging capability at fine spatial resolution is the most effective tool. Conventional single-polarization SAR oil spill monitoring techniques are limited in their capability to detect oil slicks since they strongly rely on suitable thresholds, training samples, and ancillary information. Hence, an expert image analyst is due. The launch of a number of polarimetric SAR missions, along with the understanding of the peculiar physical mechanisms governing the scattering by an oil slick, led to a new paradigm (known as physical processing) that fostered a set of polarimetric algorithms particularly robust and efficient. Hence, suitable polarimetric models that exploit the departure from the slick-free sea Bragg scattering have been developed to effectively address oil slick monitoring. A set of polarimetric features extracted following such electromagnetic models have been proved to be reliable for oil slick monitoring. Polarimetric SAR observations led to a significant improvement in sea oil slick observation since they allow distinguishing oil slicks from a broad class of lookalikes in an unsupervised way. In addition, deeper information on the damping properties of the pollutant can be also inferred, which is of paramount importance for remediation purposes. Such physical processing has been demonstrated to be robust at variance of microwave carrier frequency, e.g. L-, C-, and X-band, and suitable to be exploited to extract information by dual-polarized, full-polarized, and compact modes. All these make such a physical approach of operational interest since it is able to exploit a larger set of SAR measurements building up a virtual constellation. In this review all these are detailed

In this paper, a new paradigm for coherent microwave polarimetric remote sensing observation of man-made metallic targets at sea is presented and demonstrated over real polarimetric synthetic aperture radar (SAR) data. It is based on the different symmetry properties of the sea and of the man-made targets. The rationale relies on physical principles instead of standard image processing. Hence, a simple and very effective filter to observe man-made metallic targets at sea by full-resolution dual-polarized SAR data is developed. The technique is compared to a classic polarimetric approach, namely the polarimetric cross-entropy (PCE) constant false alarm rate (CFAR), and it is shown to perform best. Experiments, undertaken over a large data set of single look complex (SLC) L-band ALOS-PALSAR and C-band RADARSAT-2 full-polarimetric SAR data, demonstrate the physical soundness of the theory and the effectiveness of the approach from an operational viewpoint.

The authors exploit the interferometric multifrequency potentiality of the SIR-C/X-SAR system which is equipped with an L-, C-, and X-band sensor. They present a solution to improve the unwrapping performance of the C- and X-band data by considering the L-band unwrapped pattern. A new algorithm for the generation of a single digital elevation model (DEM) combining L-, C-, and X-band information is presented. This solution is based on the fusion of the unwrapped phase patterns by using a Kalman filter. The proposed fusion operation also accounts for the coherence characteristics of the three data sets. The selected test site is the Mt. Etna region in Italy which is very interesting from the volcanological and geological point of view. Numerical assessments of the achieved results are provided by evaluating the height accuracy with respect to a reference DE