Initial evaluation of the dominant mode rejection beamformer

Abstract

Long integration times are needed to give accurate cross-spectral matrix (CSM) estimates; however, integration times must be short enough so that the dynamic behavior of the noise described by the CSM is captured. The dominant mode rejection (DMR) beamformer, described by Owsley and Abraham, calculates adaptive weights based on a reduced rank (CSM) estimate, where the CSM estimate is formed with a subset of the eigenvalues containing the largest eigenvalues and their eigenvectors. Thus the integration time required to obtain this CSM estimate is reduced, as the largest eigenvalue/eigenvector pairs are estimated much more rapidly than the smaller ones. The purpose of this study was to determine whether performance comparable to a fully adaptive beamformer could be achieved with the DMR beamformer, without the potential penalties associated with requiring the increased integration time for the CSM. Data acquired with bottom-mounted horizontal line arrays, in both deep- and shallow-water environments, were used to test the dominant mode rejection beamformer performance. Appropriate DMR parameters were found using the deep-water data so that the DMR performance emulated the performance of a fully adaptive beamformer with a white-noise gain constraint. Additional processing performed on the shallow-water data showed that the DMR beamformer had equivalent performance to a robust fully adaptive beamformer, but with much less output power bias at small integration times.