Beamspace iterative quadratic WSF for DOA estimation

This article presents a beamspace version of the class of polynomial parameterized weighted subspace fitting (WSF) methods, including the well-known methods iterative quadratic maximum likelihood and method of direction estimation, for direction-ofarrival estimation with a uniform linear array. The difficulty with beamspace operation is that the Vandermonde structure of the array manifold may not preserve during a beamspace transformation. We tackle this obstacle using discrete Fourier transform beams and derive a parameterized polynomial representation of the signal subspace in the beamspace dimension. The resulting beamspace iterative quadratic WSF algorithm is not only computationally attractive, but also enjoys improved resolution threshold over element-space estimation.