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

摘要

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