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Multichannel inteferometric synthetic aperture radar (InSAR) systems allow to improve the accuracy of the estimation of the height profiles of the observed scenes. Multichannel images can be acquired by using different sensors operating at different frequencies (multifrequency InSAR) or acquiring multiple images with slightly different view angles (multibaseline InSAR). The enhanced accuracy height estimation is obtained exploiting the multichannel interferometric phases and an a priori inaccurate ground profile and requires the knowledge of the joint probability distribution of the multichannel interferometric phases, whose evaluation in a closed form is very complicated and is not found in literature. In this paper, we evaluate the analytical form of the second-order probability density function (pdf) of dual-baseline InSAR phase interferograms, obtained from three mutually correlated interferometric images. The evaluation exploits the Gaussian model for the complex SAR images, takes into account the mutual correlation of all the images, and does not use any approximation. The closed form of the second-order joint pdf can be usefully adopted in statistical digital elevation model (DEM) estimation methods using dual-baseline SAR systems, which commonly use an approximate expression of the joint pdf of measured interferometric phases, given by the product of the marginal pdfs of each phase interferogram, obtained in the assumption of independent interferograms. The effect of this approximation is evaluated by computing the Cramer-Rao lower bounds and the mean square estimation errors obtained using the exact and the approximate model. Presented results represent the basis for the generalization to the case of more than two interferograms.Index Terms-Digital elevation model (DEM) estimation, higher order statistics, multibaselines synthetic aperture radar (SAR) interferometry, phase difference statistical distribution.

Multiple SAR signals acquired along different orbits can be exploited for reconstructing a three dimensional (3-D) reflectivity profile of the scene along azimuth, range and elevation co-ordinates. For the 3-D image formation, the problem of the non-uniform spacing of the orbits has to be considered. In this paper we propose a technique based on two steps: 1) a preprocessing step, in which the samples of the multi-pass signal is computed on a grid which is uniform in the elevation direction, starting from its unevenly spaced samples; 2) a 3-D image focusing based on a simple 3-D convolution operator. The technique proposed has the main advantages of preserving numerical efficiency and allowing to easily include information on the signals bandwidth in the pre-processing step, in such a way to regularize the problem and obtain stable solutions.

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