A corrected effective density fluid model is developed for predicting sound speed dispersion and attenuation coefficient in gassy sediments. An acoustic experiment was undertaken to measure the attenuation coefficient in a frequency band of 600 to 3000 Hz in gassy unsaturated sand. The measured frequency spectra of the attenuation coefficient show four peaks due to bubble resonance. Then a method of using several modified Gaussian functions to model bubble size distribution is proposed to fit measured attenuation data, which shows that the magnitudes of the fitted model attenuation coefficients are broadly in agreement with those measured attenuation data.

Existing methods for source localization in an ocean waveguide generally require simultaneous range and depth estimation as they are intrinsically coupled in the acoustic field. Using beam intensities averaged over ranges longer than the mode cycle distances, it is shown that the range-averaged vertical beam distribution is insensitive to the source range and sensitive to the source depth. An incoherent matched beam processing method is presented and applied to the SWellEx96 moving source data to estimate source depth based on the 127 and 130 Hz signals with good results.

Zhou et al. (2022) proposed a method for instantaneous source depth estimation in deep water using matched beam intensity processing (MBIP) that leverages depth‐related oscillatory features arising from Lloyd's mirror interference in the frequency domain (Appl. Acoust., 2022, 186, 108493). However, the efficacy of MBIP diminishes with a random source spectrum. To counteract the effect of a random source spectrum, a vertical line array (VLA) positioned near the sea bottom is employed and a cross‐spectrum is generated from the conventional beamforming output, which is achieved by dividing the VLA into upper‐half and lower‐half arrays. The authors find that the cross‐spectrum phase interference pattern is determined by the source depth and is unaffected by the source spectrum. Consequently, a matched cross‐spectrum phase processing method is proposed, which demonstrates appreciable depth estimation accuracy compared to that of the existing techniques, as evidenced by the results from both simulated and experimental data.

This study proposed a matched field source localization method based on tensor decomposition. By considering the advantages of tensors in multidimensional data processing, a three-dimensional tensor signal model of space-time-frequency is constructed, and the signal subspace is estimated using high-order singular value decomposition (HOSVD). The source position is estimated by matching the measured data tensor signal subspace with the replica field tensor signal subspace. The S5 event data of SWellEx-96 is processed by the proposed tensor-based matched-field processing (TMFP). The comparison with the results of conventional matched field processing (MFP) shows that TMFP has a better suppression effect on ambient noise under low SNR and better source localization performance.