Matched field processing in noisy and imperfectly known ocean environments

Summary form only given. The generalization of conventional array signal processing to multidimensional matched field processing for source localization in the ocean environment is complicated by several factors associated with the nonideal waveguide nature of the acoustic propagation and the presence of natural ambient noise. A number of nonlinear beamformers that combine the sidelobe suppression performance of the maximum-likelihood method (MLM) with the lower resolution of the linear beamformer, in essence widening the mainlobe at the source position without totally sacrificing the sidelobe suppression, have been developed resulting in a more tolerant and robust processing algorithm. A full-wave-field propagation model has been used to simulate realistic ambient noise and signal fields, and the source localization performance of these beamforming algorithms has been analyzed, with particular focus on the effects of noise correlation and environmental mismatch