This paper presents the multitemporal adaptive processing (MAP3) framework for the treatment of multitemporal synthetic aperture radar (SAR) images. The framework is organized in three major activities dealing with calibration, adaptability, and representation. The processing chain has been designed looking at the simplicity, i.e., the minimization of the operations needed to obtain the products, and at the algorithms' availability in the literature. Innovation has been provided in the crosscalibration step, which is solved introducing the variable amplitude levels equalization (VALE) method, through which it is possible to establish a common metrics for the measurement of the amplitude levels exhibited by the images of the series. Representation issues are discussed with an application-based approach, supported by examples with regard to semiarid and temperate regions in which amplitude maps and interferometric coherence are combined in an original way.

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Abstract-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, with care to the sensor signatures, the dielectric, physical-chemical, and geometric nature of the oil slick, and to 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.

Abstract-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.