Mohammed Nabil El Korso

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—Near-field source localization problem by a passive antenna array makes the assumption that the time-varying sources are located near the antenna. In this context, the far-field assumption (i.e., planar wave-front) is, of course, no longer valid and one has to consider a more complicated model parameterized by the bearing (as in the far-field case) and by(More)
In this paper, we consider the range and bearing estimation of near-field narrow-band sources from noisy data observed across a passive sensor array. For some difficult scenarios as for correlated and largely spaced sources at low SNRs, or correlated and closely spaced sources, the Near FieLd (NFL) version of the MUltiple SIgnal Classification (MUSIC)(More)
—Among the family of polarization sensitive arrays, we can find the so-called cocentered orthogonal loop and dipole uniform linear array (COLD-ULA). The COLD-ULA exhibits some interesting properties, e.g., the insensibility of the polarization vector with respect to the source lo-calization in the plan of the array. In this correspondence, we derive the(More)
The concept of Statistical Resolution Limit (SRL), which is defined as the minimal separation to resolve two closely spaced signals, is an important tool to quantify performance in parametric estimation problems. This paper generalizes the SRL based on the Cramér-Rao bound to multiple parameters of interest per signal and for multiple signals. We first(More)
The statistical resolution limit (SRL), which is defined as the minimal separation between parameters to allow a correct resolvability, is an important statistical tool to quantify the ultimate performance for parametric estimation problems. In this article, we generalize the concept of the SRL to the multidimensional SRL (MSRL) applied to the(More)
Near-field source localization problem by a passive antenna array makes the assumption that the time-varying sources are located near the antenna. In this situation, the far-field assumption (planar wave-front) is no longer valid and we have to consider a more complicated model parameterized by the bearing (as in the far-field case) and by the distance,(More)
The resolvability of two closely-spaced signals is an important performance measure for parametric estimation problems. In this paper we investigate the so-called resolution limit (RL) in a MIMO radar context, i.e., the minimum angular separation required to resolve two closely-spaced targets. Due to the limited number of elementary scatterers, the Gaussian(More)
The asymptotic statistical resolution limit (SRL), denoted by d, characterizing the minimal separation to resolve two closely spaced far-field narrowband sources for a large number of observations, among a total number of M Z 2, impinging on a linear array is derived. The two sources of interest (SOI) are corrupted by (1) the interference resulting from the(More)
—During the last decade, multiple-input multiple-ouput (MIMO) radar has received an increasing interest. One can find several estimation schemes in the literature related to the direction of arrivals and/or direction of departures, but their ultimate performance in terms of the statistical resolution limit (SRL) have not been fully investigated. In this(More)
In this paper, we derive the Multidimensional Statistical Resolution Limit (MSRL) to resolve two closely spaced targets using a widely spaced MIMO radar. Toward this end, we perform a hypothesis test formulation using the Generalized Likelihood Ratio Test (GLRT). More precisely, we link the MSRL to the minimum Signal-to-Noise Ratio (SNR) required to resolve(More)