Underwater source localization with a generalized likelihood ratio processor

The author describe a new matched-field acoustic source localization technique using reduced-rank signal processing. The problem is posed as a simultaneous detection and parameter estimation in which unknown, deterministic noise will act to obscure the source. They derive a reduced-rank likelihood ratio array processor and demonstrate its ability to detect and localize the signal of interest. The key advantage of this reduced-rank processor is its ability to remove the interference present while retaining the pertinent information necessary for detection and localization. This is accomplished using singular value decompositions of data matrices