Abstract
The purpose of this paper is Co present a multidimensional MEM algorithm, valid for non-uniformly sampled arrays, which satisfies a "corrrelation-approximatily" constraint. To this end, the correlation matching.equality constraints of the usual MEM are replaced by a single inequality constraint whose form is based on a measure of the noise in the given acf. In this way, one can incorporate into the model knowledge of the noisy nature of the "given" acf, since the "given" acf is usually estimated from samples of the wavefield. The algorithm has been tested with 1-D synthetic data representing multiple sinusoids buried in additive white noise. The performance of this modified MEM algorithm is compared to a traditional MEM algorithm for extendible acfs and for different SNRs.
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