A Bayesian source tracking approach is developed to track a moving acoustic source in an uncertain ocean environment. This approach treats the environmental parameters （e.g., water depth, sediment and bottom paramet...A Bayesian source tracking approach is developed to track a moving acoustic source in an uncertain ocean environment. This approach treats the environmental parameters （e.g., water depth, sediment and bottom parameters） at the source location and the source parameters （e.g., source depth, range and speed） as unknown random variables that evolve as the source moves. To track a target with low signal-to-noise ratio （SNR）, acoustic signals from a series of observations are treated in a simultaneous inversion. This allows real-time updating of the environment and accurate tracking of the moving source. The noise signals radiated from a surface ship target are processed and analyzed. It is found that the Bayesian source tracking method could enhance the localization accuracy in an uncertain water environment and low SNR.展开更多
基金Supported by the National Natural Science Foundation of China under Grant Nos 11434012,10974218,and 11174312the State Key Laboratory of Acoustics of Chinese Academy of Sciences under Grant No SKLA201407+3 种基金the Key Laboratory of Marine Surveying and Charting in Universities of Shandong of Shandong University of Science and Technology under Grant No 2013A02the Scientific Research Foundation of Shandong University of Science and Technology for Recruited Talents under Grant No2014RCJJ004the Project of the Public Science and Technology Research of Ocean under Grant No 201305034the National Key Technology R&D Program under Grant No 2012BAB16B01
文摘A Bayesian source tracking approach is developed to track a moving acoustic source in an uncertain ocean environment. This approach treats the environmental parameters （e.g., water depth, sediment and bottom parameters） at the source location and the source parameters （e.g., source depth, range and speed） as unknown random variables that evolve as the source moves. To track a target with low signal-to-noise ratio （SNR）, acoustic signals from a series of observations are treated in a simultaneous inversion. This allows real-time updating of the environment and accurate tracking of the moving source. The noise signals radiated from a surface ship target are processed and analyzed. It is found that the Bayesian source tracking method could enhance the localization accuracy in an uncertain water environment and low SNR.
