Robust broadband matched-field localization: Results for a short, sparse vertical array

Matched-field localization is typically applied to signals received by long vertical arrays. A much more challenging problem is the application of these techniques to short vertical arrays. Short arrays require the use of multiple frequencies in localization processing to reduce ambiguities. In addition, any practical localization algorithm must also be robust to environmental uncertainties. In this paper, the results of applying the robust multiple uncertainty, replica-subspace weighted projections (MU-RSWP) localization algorithm to the broadband signal/short-array problem are presented. Simulation results for two uncertain shallow-water environments are given using a short five-element array which demonstrate the significant performance improvement in using MU-RSWP over the Bartlett processor. These results serve as an illustration of the applicability of using short arrays, in conjunction with a robust localization algorithm, for matched-field localization in realistic environmental scenarios.