Fundamentals of statistical signal processing: estimation theory
Fundamentals of statistical signal processing: estimation theory
Estimation of nominal direction of arrival and angular spread using an array of sensors
Signal Processing - Special issue on subspace methods, part I: array signal processing and subspace computations
Decoupled estimation of DOA and angular spread for a spatiallydistributed source
IEEE Transactions on Signal Processing
Parametric localization of distributed sources
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
The effects of local scattering on direction of arrival estimationwith MUSIC
IEEE Transactions on Signal Processing
Simplified Estimation of 2D DOA for Coherently Distributed Sources
Wireless Personal Communications: An International Journal
Low-Complexity Estimation of DOA and Angular Spread for an Incoherently Distributed Source
Wireless Personal Communications: An International Journal
A Simplified Estimator for Tridimensional Localization of Single Incoherently Distributed Source
Wireless Personal Communications: An International Journal
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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 theform of the azimuthal power distribution is explicitly known or not. For bothmodels, the block-diagonal structure of the associated Fisher InformationMatrix (FIM) is exploited to decouple the estimation of the DOA from that ofthe other model parameters. An asymptotically efficient Maximum Likelihood(ML)DOA estimator is derived which entails solving a 1-D minimization problemonly.Furthermore, the 1-D criterion can be expressed as a simple Fourier Transform.A numerical comparison with the Cramér-Rao Bound (CRB) illustrates thefactthat our computationally very simple DOA estimators are statisticallyefficientfor a wide range of scenarios.