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High Resolution Spectrum Analysis by Dominant Mode Enhancement,
NAVAL UNDERWATER SYSTEMS CENTER NEW LONDON CT NEW LONDON LAB
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High-resolution, data adaptive spectrum analysis techniques can exploit prior knowledge of the signal dimensionality and noise coherence to obtain even higher resolution capabilities than previously envisioned. The classical minimum variance maximum likelihood and maximum entropy ME spectrum estimators form the basis for corresponding enhanced estimators which require only a prior knowledge of signal bandwidth to provide resolution which is limited only by observation time. The basic idea is to identify only that portion of the estimated data covariance matrix which corresponds to the coherent signal portion of the analysis data. This can be accomplished alternatively by eigensystem analysis, singular value decomposition and Cholesky factorization of the estimated signal only covariance matrix. In this paper, the dominant mode form of the analysis data covariance matrix is presented along with expression for the readily derived inverse of this matrix. Next, the minimum variance MV and ME spectrum estimators in modal decomposition form are developed along with 3 dB down resolution expressions. Finally, the modal MV and ME estimators are applied to passive sensor array processing for source range estimation.
APPROVED FOR PUBLIC RELEASE