Abstract
A technique is proposed for the extraction of spectral signals for which the components within a signal set are characterized by complex envelopes which exhibit correlation. The technique is based on an orthogonal decomposition of the cross (discrete) frequency correlation matrix describing the set in the presence of additive uncorrelated noise. Certain advantages of the technique relative to those based on Fourier analysis with either estimated power spectrum or minimum variance processing are presented. Specifically, it is illustrated how the detection performance of the technique is established by the total energy in the spectral set rather than by the levels of individual spectral elements in the set. Furthermore, it is shown how minimum variance spectrum analysis actually can suppress components in such a set.
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