Direction of Arrival and Angular Velocities (DOAV) Estimation using Minimum Variance Beamforming

The minimum variance distortionless beamforming (MVDR) is an excellent beamformer for estimating the location of a source when the background noise is Gaussian. This beamformer, also known as the Capon approach, is widely studied and used. In this paper, we investigate the use of the MVDR to estimate the angle of arrival and angular velocities by modeling the movement of the source emitting signal. As a result a four dimensional MVDR is proposed, to estimate the direction of arrival and angular velocities (DOAV) of moving sources, using a rectangular array of antennas. In order to estimate the emitting source parameters, a four dimensional search is required. In practice, this approach is costly and may not be suitable in realtime applications. To reduce the computational complexity of the approach, we exploit the geometry of the array, together with a parameter dimensionality decoupling technique to perform an initialization based on a subspace decomposition approach. This initialization results in two two-dimensional searches in parallel instead of the standard four-dimensional search. We further show that the initialization procedure fits well with the conventional MVDR concept. The performance of the subspace decomposition approach is demonstrated via simulations. We also investigate the effects of diagonal loading on a small sample size and how it can be used together with the MVDR initialization technique to enhance the performance of the overall MDVR approach.