摘要
Ocean sound speed profile(SSP) is the key factor affecting acoustic propagation. The acquisition of SSPsin real time with high precision is meaningful for underwater activities. By means of the remote sensing method, thesea surface data could be obtained in near-real time. Typically, the subsurface fields are correlated with the sea surfaceparameters. Thus, the SSPs could be obtained by means of satellite remote sensing. In this paper, the history as wellas the current research over the reconstruction of subsurface fields by means of sea surface data is introduced. Thentwo methods to reconstruct the SSPs with sea surface data, including the linear regression method using the empiricalorthogonal function, and the self-organizing method based on the big data theory, are described in detail in the paper.
Ocean sound speed profile(SSP) is the key factor affecting acoustic propagation. The acquisition of SSPsin real time with high precision is meaningful for underwater activities. By means of the remote sensing method, thesea surface data could be obtained in near-real time. Typically, the subsurface fields are correlated with the sea surfaceparameters. Thus, the SSPs could be obtained by means of satellite remote sensing. In this paper, the history as wellas the current research over the reconstruction of subsurface fields by means of sea surface data is introduced. Thentwo methods to reconstruct the SSPs with sea surface data, including the linear regression method using the empiricalorthogonal function, and the self-organizing method based on the big data theory, are described in detail in the paper.
