Computationally Efficient Maximum Likelihood Approach to DOA Estimation of a Scattered Source

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.

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