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The notion of Symmetric Non-causal Auto-Regressive Signals (SNARS) arises in several, mostly spatial, signal processing applications. In this paper we introduce a subspace fitting approach for parameter estimation of SNARS from noise-corrupted measurements. We show that the subspaces associated with a Hankel matrix built from the data covariances contain enough information to determine the signal...
The problem of Direction-Of-Arrival (DOA) estimation in the presence of local scatterers using a uniform linear array (ULA) of sensors is addressed. We consider two models depending on whether the form of the azimuthal power distribution is explicitly known or not. For both models, the block-diagonal structure of the associated Fisher Information Matrix (FIM) is exploited to decouple the estimation...
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