Fast implementation of root-form eigen-based methods for detecting closely spaced sources
Ta-Sung Lee · IEE Proceedings F Radar and Signal Processing · 1992
Root-form eigen-based methods for direction-of-arrival (DOA) estimation represent a class of estimators that exhibit a higher resolution capability relative to spectral-form estimators in detecting closely spaced sources with a linear, equally spaced (LES) array. These methods require an eigenvalue decomposition (EVD) and a polynomial rooting. Although the numerical complexity associated with the EVD is greatly reduced with the use of beamspace transformation, largeorder polynomial rooting still raises practical difficulties. As a remedy, the author proposes a novel iterative implementation of beamspace root-form methods without the need for large-order polynomial rooting. The new method exploits the banded structure of the augmented noise eigenvector matrix associated with an LES array. It requires only rooting in parallel several smallorder polynomials and some minor matrix manipulations at each iteration. It is shown that the proposed method offers the performance of beamspace root-MUSIC.