GLRT-Based Framework for the Multidimensional Statistical Resolution Limit

Mohammed Nabil El Korso (1) , Remy Boyer (1) , Alexandre Renaux (1) , Sylvie Marcos (1)

1 L2S - Laboratoire des signaux et systèmes

Recently, a criterion for Multidimensional Statistical Resolution Limit (MSRL) evaluation, which is defined as the minimal separation to resolve two closely spaced signals depending on several parameters, was empirically proposed in [1] but without a statistical analysis. In this paper, we fill this lack by demonstrating that this MSRL criterion is asymptotically equivalent (upon to a translator factor) to a UMP (Uniformly Most Powerful) test among all invariant statistical tests. This result is an extension of a previous work on mono-dimensional SRL (i.e., when the signals only depend on one parameter). As an illustrative example, the 3-D harmonic retrieval case for wireless channel sounding is treated to show the good agreement of the proposed result.

Domaines: Traitement du signal et de l'image [eess.SP]; Traitement du signal et de l'image [eess.SP]

Mohammed Nabil El Korso, Remy Boyer, Alexandre Renaux, Sylvie Marcos. GLRT-Based Framework for the Multidimensional Statistical Resolution Limit. IEEE International Workshop on Statistical Signal Processing 2011 - IEEE SSP'11, 2011, France. ⟨hal-00577273⟩