Underwater acoustic tomography is an advanced technology in water environment observation. Sound propagation duration between transceivers is used for underwater parameter distribution profile reconstruction in the inverse problem. The key points of acoustic tomography are accurate station distance and time synchronization. Two methods are introduced in this study for sound station position correction. The direct signal transmission correction (DSC) method corrects the multi-peak (expect direct ray) travel time via the travel time difference between different sound rays and reference direct ray. The ray-model position correction (RMC) method calculates exact station position by the station drift distance obtained from transceiver depth variations to correct direct ray travel time; the other multi-peak travel time is revised by the corrected direct ray travel time. A water temperature observation experiment was carried out in a reservoir using coastal acoustic tomography (CAT) systems to verify the flexibility of these two methods. Multi-ray arrival peaks are corrected using DSC and RMC methods; water temperature inversion results in a 2D vertical profile are obtained. The reliability of the method is proved by comparison with temperature depth sensor (TD) data. The methods improve the quality of initial data and can be attempted for further water environment observation in acoustic tomography observation studies.

Remote sensing of water temperature and flow dynamics is of paramount importance for water environment management. Coastal acoustic tomography (CAT), an innovative method for remote sensing in underwater environments, utilizes the dual-way travel time of multiple sound paths to reconstruct the underwater temperature field. However, the transmission experiments are susceptible to data noise caused by station drift and inaccuracies in travel time extraction. In this study, a three-dimensional Rousseeuw Phase-Space (3-D-RPS) thresholding algorithm is proposed to remove outliers in the travel time data obtained from Huangcai Reservoir using three CAT systems on September 16, 2020. Additionally, this work includes grid partitioning based on sound path propagation, calculation of sound path lengths, and reference transmission time within each grid, construction of a sparse matrix, and inversion of the two-dimensional temperature field and its associated inversion error. The accuracy and applicability of the proposed method are confirmed through a comparison with data obtained from temperature–depth (TD) sensors. The results demonstrate the precision and suitability of this approach. By effectively mitigating the impact of station drift and extraction accuracy issues, this method provides a reliable temperature field estimation.