A Kullback-Leibler Methodology for Unconditional ML DOA Estimation in Unknown Nonuniform Noise
Maximum likelihood (ML) direction-of arrival (DOA) estimation of multiple narrowband sources in unknown nonunifrom white noise is considered. A new iterative algorithm for stochastic ML DOA estimation is presented. The stepwise concentration of the log-likelihood (LL) function with respect to the signal and noise nuisance parameters is derived by alternating minimization of the Kullback-Leibler divergence between a model family of probability distributions defined on the unconditional model and...[Show more]
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|Source:||IEEE Transactions on Aerospace and Electronic Systems|
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