MATCHED MODE PROCESSING FOR SPARSE 3-DIMENSIONAL ARRAYS

Matched mode processing (MMP) has been demonstrated to localize underw ater sound sources with vertical hydrophone arrays. Two new MMP algori thms for arbitrarily shaped three-dimensional arrays in a range-indepe ndent environment are presented. The first algorithm, exact matched mo de processing (EMMP), is a generalization of vertical array MMP; its m ode decomposition depends on source bearing. The second algorithm, app roximate matched mode processing (AMMP), ignores bearing dependence du ring mode decomposition, reinserting it afterward. The AMMP azimuth be am pattern is similar to that of matched field processing (MFP) and co nventional beamforming. The performance of the EMMP and AMMP algorithm s is investigated and compared with MFP using simulated data. A slante d vertical array, a horizontal array, and a T-shaped array composed of horizontal and vertical segments were considered. It was found that t he AMMP and MFP yield similar peak-to-sidelobe ratio (PSR) and peak-to -average-sidelobe ratio (PASR) in range and depth localization. In con trast, the EMMP yields higher PSR and PASR in range and depth localiza tion for known source bearings. Its bearing search properties were not investigated; they may be less robust than AMMP, MFP and conventional beamforming.