The paper is focused on Digital Elevation Model (DEM) reconstruction from differential interferometry synthetic aperture radar (DInSAR). In doing so, conventional DInSAR procedures are implemented to three repeat passes of RADARSAT-1 SAR fine mode data (F1). Further, the multichannel MAP height estimator is implemented with phase unwrapping technique. Consequently, the multichannel MAP height e...

A simple consistent nonparametric estimator of the long-run correlation between two series is proposed, based on the estimation of the bivariate k-lag difference correlation. It is shown that the estimator is asymptotically equivalent to the Bartlett kernel spectral estimator of the complex coherency at frequency zero. The asymptotic distribution is derived, with a test for the absence of long-...

We study the following model: Y = X + ε. We assume that we have at our disposal i.i.d. observations Y1, . . . , Yn and ε−1, . . . , ε−M . The (Xj)1≤j≤n are i.i.d. with density f , independent of the (εj)1≤j≤n, i.i.d. with density fε. The aim of the paper is to estimate f without knowing fε. We first define an estimator, for which we provide bounds for the integrated L-risk. We consider ordinary...

We consider the fundamental problem of matching a template to signal. do so by M-estimation, which encompasses procedures that are robust gross errors (i.e., outliers). Using standard results from empirical process theory, we derive convergence rate and asymptotic distribution M-estimator under relatively mild assumptions. also discuss optimality estimator, both in finite samples minimax sense ...

In this paper, we propose a fast algorithm for speeding up the process of template matching that uses M-estimators for dealing with outliers. We propose a particular image hierarchy called the p-pyramid that can be exploited to generate a list of ascending lower bounds of the minimal matching errors when a non-decreasing robust error measure is adopted. Then, the set of lower bounds can be used...

Two types of M-estimators of the parameters of the multi-variate linear model are considered. The first type corresponds to coordinatewise M-estimators; the second is an extension of Maronna's (1976) proposal for the multivariate location case. Under some general conditions on the error distribution, on the design matrix and on the score functions, the asymptotic distribution of the coordinatew...

Robust (M-) estimation in linear models generally involves statistical functional processes. For drawing statistical conclusions (in large samples), some (uniform) linear approximations are usually needed for such functionals. In this context, the role of Hadamard differentiability is critically examined in this dissertation. In particular, the concept of the second-order Hadamard differenti-ab...

The joint estimation of the location vector and shape matrix a set independent identically Complex Elliptically Symmetric (CES) distributed observations is investigated from both theoretical computational viewpoints. This problem framed in original context semiparametric models allowing us to handle (generally unknown) density generator as an infinite-dimensional nuisance parameter. In first pa...