Abstract
In the theory of augmented array beamforming, a spatial invariance property of the noise field is exploited in order to constrain the beam pattern of the array at more points than the number of elements in the array. This results in weight vectors of the augmented array with the dimensions greater than the number of elements. Due to the larger dimensionality, the constrained least-mean-square (LMS) algorithm in the usual form cannot be used to adaptively estimate these weights. This article presents an algorithm to iteratively estimate the optimal weights of an augmented array.
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