ML-Based Angle-of-arrival Estimation of a Parametric Source

Abstract

In angle of arrival estimation, the direction of a signal is usually assumed to be a point. If the direction of a signal is distributed due to some reasons in real surroundings, however, angle of arrival estimation techniques based on the point source assumption may result in poor performance. In this paper, we consider angle of arrival estimation when the signal sources are distributed. A parametric source model is proposed, and the estimation techniques based on well-known maximum likelihood technique is considered under the model. In addition, various statistical properties of the estimation errors were considered.