Recovery of the sound speed as a function of space is the starting point for inferring oceanographic features in the water column. The sound speed profile (SSP) in shallow water is much more complicated than that in deep water. Concurrent with in-situ measurements, many inversion methods, such as matched-field inversion, have been put forward to invert the SSP from acoustic signals. In SSP inversion, empirical orthogonal functions (EOFs) are used in describing the SSP to reduce the total number of inverted parameters. However, the time cost might be too high in replica field calculation for matched-field processing (MFP).

In an effort to obtain a quasi-real-time inversion result, YU Yanxin, LI Zhenglin and HE Li of Institute of Acoustics, Chinese Academy of Sciences carried out a series of studies and employed the parallel computing in the research.

The researchers studied the feasibility and robustness of an acoustic tomography scheme with matched-field processing in shallow water, and described the sound speed profile by empirical orthogonal functions. They analyzed the acoustic signals from a vertical line array in ASIAEX2001 in the East China Sea to invert sound speed profiles with estimated empirical orthogonal functions and a parallel genetic algorithm to speed up the inversion. The results show that the inverted sound speed profiles are in good agreement with conductivity-temperature-depth measurements. Moreover, they carried out a posteriori probability analysis to verify the inversion results. 

This research result was published on the recently issued journal of Chinese Journal of Oceanology and Limnology (Vol. 28 No. 5, P. 1080-1085, 2010).