A source depth discrimination method based on wavenumber measured by bottom-mounted HLA

In research into underwater acoustics, the ability to differentiate submerged sources from surface sources could meet multiple applications. By using a bottom-mounted Horizontal Line Array (HLA), a solution to the problem of acoustic source depth discrimination in a downward-refracting underwater environment is presented. The testing problem is considered by beamforming in the modal domain. According to wavenumber offsets in the wavenumber spectra, a source depth feature is detected. The phenomenon is explained in terms of mode theory, using the concept of mode trapping. The decision metric is built based on the Accumulated Relative Wavenumber Offset (ARWO) derived by subarrays and broadband processing, then the simulation result reveals that the source can be correctly discriminated. Without mode matching or mode filtering, the method has high computational efficiency. In addition, the applicability for bottom-mounted HLA and the sediment independence of this method is proved. Finally, a moving surface source and a dipping submerged source during an experiment conducted in the South China Sea are taken into consideration. The source-depth characteristic is magnified by the ARWO. Over test trials, the classifier provides a satisfactory effect, with which the depth discrimination method is well explained.