Abstract
Remote sensing of water parameter and flow dynamic progress is of critical importance to water environment observation. Underwater acoustic tomography technology uses multiple sound stations to construct distributed sensing network for large scale measuring, which has big superiority in water parameter observation compared with fix-point measurement. Water parameter variation progress can be monitored with underwater acoustic tomography sensing system. This paper develops a Grid-averaged Trust-Region Method for water parameter detailed profiling with coastal acoustic tomography (CAT) systems. A remote sensing experiment was conducted with 5 Coastal Acoustic Tomography (CAT) systems from February 28th to March 7th, 2022 in the Huangcai Reservoir in Changsha, China. Four CAT systems were deployed in same position with different depth of sound transceivers and another CAT station was set 650m apart. Water temperature and flow current reconstruction results along sound propagate section was analyzed with trust-region method and compared with the temperature data acquired with temperature sensor. The accuracy and feasibility of this method are verified with observation results.
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