Name
Abstract | ||
|---|---|---|
Coastal acoustic tomography (CAT), as an innovative technology, can perform water temperature measurements both in horizontal and vertical slices. Investigations on vertical slice observations are significantly fewer in number than horizontal observations due to difficulties in multi-path arrival peak identification. In this study, a two-station sound transmission experiment is carried out in Thousand-Island Lake, Hangzhou, China, to acquire acoustic data for water temperature profiling. Time windows, determined by range-independent ray simulation, are used to identify multi-path arrival peaks and obtain corresponding sound wave travel times. Special attention is paid to travel time correction, whose errors are caused by position drifting by more than 2 m of moored stations. The sound speed and temperature profiling are divided into four layers and are calculated by regularized inversion. Results show a good consistency with conductivity-temperature-depth (CTD) measurements. The root mean square error (RMSE) of water temperature is 0.3494, 0.6838, 1.0236 and 1.0985 degrees C for layer 1, 2, 3 and 4, respectively. The fluctuations of measurement are further smoothed by the moving average, which decreases the RMSE of water temperature to 0.2858, 0.4742, 0.7719 and 0.9945 degrees C, respectively. This study illustrates the feasibility and high accuracy of the coastal acoustic tomography method in short-range water temperature measurement. Furthermore, 3D water temperature field profiling can be performed with combined analyzing in horizontal and vertical slices. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.3390/s20164498 | SENSORS |
Keywords | DocType | Volume |
coastal acoustic tomography,vertical slice inversion,multi-path arrival identification,position correction,water temperature observation | Journal | 20 |
Issue | ISSN | Citations |
16 | 1424-8220 | 0 |
PageRank | References | Authors |
0.34 | 0 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Haocai Huang | 1 | 1 | 1.36 |
| Yong Guo | 2 | 10 | 8.01 |
| Guangming Li | 3 | 0 | 1.01 |
| Arata Kaneko | 4 | 1 | 2.99 |
| Xinyi Xie | 5 | 0 | 1.35 |
| Pan Xu | 6 | 0 | 0.34 |