GENERALIZATION AND ANALYSIS OF THE CONVENTIONAL BEAMFORMER FOR LOCALIZATION OF SPATIALLY DISTRIBUTED SOURCES

In this paper, we generalize the point source-based conven-tional beamformer (CBF) to localization of multiple dis-tributed sources that appear in sensor array processing. A distributed source is commonly parameterized by its mean angle and spatial spread. The generalized CBF uses the principal eigenvector of the parameterized signal covariance matrix as its optimal weight vector, which is also shown to be a matched filter. The desired parameter estimates are taken as the peaks of the generalized 2-dimensional beamforming spectrum. Further, the performance of the algorithm is com-pared numerically to a generalized Capon estimator [1]. Fi-nally, an asymptotic performance analysis of the proposed algorithm is provided and numerically verified. 1