Matched field source detection and localization in high noise environments: A novel reduced-rank signal processing approach

摘要

A new matched-field acoustic source localization technique using reduced-rank signal processing is described. The authors pose the problem as joint detection and parameter estimation in the face of unknown, structured noise. They derive a reduced-rank likelihood ratio array processor and demonstrate its ability to detect and localize sources of interest. A key feature of reduced-rank signal processing is the ability to discard undesirable information from data matrices by their low rank approximation. Computer simulation results demonstrate its viability under a wide range of operating conditions.