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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.

Detection of man-made structures in urban areas, in terms of both geometric and electromagnetic features, from a single, possibly High Resolution (HR), Synthetic Aperture Radar (SAR) image is a highly interesting open challenge. Within this framework a possible approach for the extraction of some relevant parameters, describing shape and materials of a generic building, is here proposed. The approach is based on sound electromagnetic models for the radar returns of each element of the urban scene: a fully analytical representation of electromagnetic returns from the scene constituents to an active microwave sensor is employed. Some possible applications of feature extractions from real SAR images, based on above approach, have been already presented in literature as first examples of potentiality of a model-based approach but here the overall theory is analyzed and discussed in depth, to move to general considerations about its soundness and applicability, as well as efficiency of further applications may be derived.For the sake of conciseness, although the proposed approach is general and can be applied for the retrieval of different scene parameters (in principle, anyone contributing to the radar return), we here focus on the extraction of the building height, and we assume that the other parameters are either a priori known (e.g., electromagnetic properties of the materials), or have been previously retrieved from the same SAR image (e.g., building length and width). An analysis of the sensitiveness of the height retrieval to both model inaccuracies and to errors on the knowledge of the other parameters is performed. Some simulation examples accompany and validate the solution scheme that we propose.

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In a previous paper, a two-dimensional Fourier do-main synthetic aperture radar (SAR) raw signal simulator that exploits the efficiency of fast Fourier transform algorithms was presented. It accounts for the effects of sensor trajectory de-viations and is able to generate the raw signal corresponding to extended scenes in a few seconds. However, a narrow-beam-slow-deviation assumption is made; hence, the approach can be applied only to some SAR systems and/or trajectory devia-tions. To overcome this limitation, in this paper, we show that the narrow-beam-slow-deviation assumption can be relaxed, at the expense of computation efficiency, if use is made of one-dimensional azimuth Fourier domain processing followed by range time-domain integration. The latter approach only requires some reasonable assumptions on the sensor motion and on the SAR system features; hence, it can be used for airborne SAR systems, and turns out to be still much more efficient than the time-domain one; hence, extended scenes can still be considered. Validity limits of the approach are also analytically evaluated, and several simulation results are finally presented to verify the effectiveness of the proposed simulation scheme. © 2006 IEEE

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