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Adaptive Beamforming For Large Arrays

Adaptive and high-resolution array processing techniques are usually considered for relatively small arrays in which the number of snapshots is large compared to the number of array elements. In this paper we consider the case of a large array in which the number of snapshots is smaller than the number of sensors, and therefore the sample covariance matrix is rank deficient. A numerically stable adaptive beamforming algorithm is derived for this case, and it is shown how eigenstructure based algorithms such as MUSIC need to be modified to handle the case of large arrays.