Variational Bayesian Estimation of Time-Varying DOAs

We present a Bayesian method for sequential direction finding based on variational line spectral estimation (VALSE). The proposed method promotes sparse solutions by means of a Bernoulli-Gaussian amplitude model, is grid-less, and provides marginal posterior distributions from which DOA estimates and their uncertainties can be extracted. Simulation results demonstrate performance improvements in the considered scenario. We also evaluate the proposed method using acoustic data from an underwater source localization experiment.

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