On pre-whitening and accuracy in DOA estimation by sparse signal processing on beamformed data
Dave J. Bekers, W.L. van Rossum, S. S. A. M. Jacobs, Matijs Heiligers, Laura Anitori, Emiel Stolp, Lorenzo Cifola, M. Podt · 2016
In this paper we consider the problem of direction of arrival estimation from a set of beamformed measurements corrupted by correlated Gaussian noise. We investigate the performance of sparse signal processing (SSP) on correlated and pre-whitened data, focusing on accuracy and false alarm rate. We considered both a fixed-grid and a gridless method, and performed several simulations. From our analysis we conclude that SSP applied to tapered and beamformed data without prewhitening is robust, but results in a lower accuracy than in the pre-whitened case. Furthermore, by comparing the two methods, we also observe that, for the scenario considered, the fixed-grid method performs as good as the gridless one.