Probabilistic Direction of Arrival Estimation Through Bayesian Compressive Sensing

In this paper a class of recently introduced Bayesian approaches for the solution of directions-of-arrival (DoAs) estimation problems is illustrated and discussed. More in detail, the problem of the estimation of the DoAs of electromagnetic narrow-band signals impinging on an antenna array is addressed in this paper by means of a strategy based on the Bayesian Compressive Sensing (BCS). Firstly, the relation between the data (i. e. the measured voltages) and the unknown DoAs is formulated as a linear relationship with sparse solution. Successively, the problem is solved by applying the BCS in order to estimate the most probable sparse solution fitting the measured input data. Preliminary numerical examples aimed at assessing the effectiveness of the considered techniques are presented.