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Estimating building layouts using exterior radar measurements is a challenging task involving electromagnetic modeling, many unknown parameters, and a limited number of sensors. We propose using the jump-diffusion algorithm as a powerful stochastic tool that can be used to estimate the number of walls, their unknown positions and other parameters. We develop an efficient iterative procedure that first uses low-frequency transmissions to obtain rough estimates of the building layout. These estimates are then used to initialize the estimation at higher frequencies, thus obtaining more accurate results. We show that with proper frequency selection, the building layout can be estimated using radar measurements at only a few frequencies. Numerical examples are used to illustrate the performance of the proposed algorithm in practical situations. Index Terms--Building layout estimation, frequency hopping, inverse scattering, jump-diffusion, multiple frequencies, through-the-wall sensing.

This work presents a framework for automatic feature extraction from images using stochastic geometry. Features in images are modeled as realizations of a spatial point process of geometrical shapes. This framework allows the incorporation of a priori knowledge on the spatial repartition of features. More specifically, we present a model based on the superposition of a process of segments and a process of rectangles. The former is dedicated to the detection of linear networks of discontinuities, whereas the latter aims at segmenting homogeneous areas. An energy is defined, favoring connections of segments, alignments of rectangles, and a relevant interaction between both types of objects. The estimation is performed by minimizing the energy using a simulated annealing algorithm. The proposed model is applied to the analysis of Digital Elevation Models (DEMs). These images are raster data representing the altimetry of a dense urban area. We present results on real data provided by the French National Geographic Institute (IGN) consisting in low-quality DEMs of various types. Index Terms--Image processing, Poisson point process, stochastic geometry, dense urban area, Digital Elevation Models, land register, building detection, MCMC, RJMCMC, simulated annealing.

A sequential detector for the release of biochemical substance is developed. Findings reveal that the proposed detector is useful in providing online detection of the appearance of a biochemical source in realistic complex environments.