SPECTRUM ESTIMATION FOR DISTRIBUTED SOURCES.

This paper considers the problem of estimating the spectrum of distributed sources from measurements made at the outputs of a set of spatially deployed sensor elements. It is shown here that by combining the useful properties of both the maximum likelihood method (MLM) and the eigenstructure-based technique, a doubly constrained, data-dependent spectrum estimator, the output of which approximates the distributed spectrum, can be realized.