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Matched Field Processing (MFP) locates the underwater sources by matching the received data with the replica vectors, which could be regarded as a generalized beamformer. In this paper, the MFP method is combined with a recently developed framework-Graph Signal Processing (GSP) method. Following the paradigm of GSP, a spatial adjacency matrix is constructed for the arbitrary distributed sensors based on the Green's function, then the source is located by utilizing the graph Fourier transform. The simulation results illustrate that the Graph-based MFP outperforms the the conventional MFP processors-the Bartlett processor and the Minimum Variance processor-for its good accuracy and robustness.

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The bottom parameters of the deep ocean are difficult to obtain through in situ measurement. These parameters demonstrate a significant physical meaning for predicting sound field accurately. Thus, geoacoustic inversion is required. An acoustic experiment was performed on a reliable acoustic path (RAP) in the Philippine Sea in 2013. A single bottom-moored hydrophone was deployed as the receiver, and the explosive charges were chosen as the sources. The experimental bottom loss (BL) versus angle was obtained with the water depth above 5000[Formula: see text]m for bottom parameter inversion. The inversion sediment parameters show a clay-silt feature. The marginal probability distributions (MPDs) represent that the inversion results have a high credibility. This method provides a feasible solution for the inversion of the bottom parameters in the deep ocean.

A striation-based method with a vertical line array is proposed for source depth estimation. Broadband striation structures of direct and surface-reflected arrivals after propagating to receivers near the ocean bottom are applied. A tracking algorithm for the striation structures is proposed based on the extended Kalman filter. A cost function for source depth estimation is presented by matching the traces of the measured striations with a library of model-based traces under different source depths. The method is demonstrated on array data collected during an acoustic research experiment in the South China Sea in 2016.