Bayesian Tracking in an Uncertain Shallow Water Environment  

作　　者：李倩倩 

机构地区：[1]Key Laboratory of Marine Surveying and Mapping in Universities of Shandong,Shandong University of Science and Technology [2]State Key Laboratory of Acoustics,Institute of Acoustics,Chinese Academy of Sciences

出　　处：《Chinese Physics Letters》2016年第3期52-55,共4页中国物理快报（英文版）

基　　金：Supported by the National Natural Science Foundation of China under Grant Nos 11434012,10974218,and 11174312;the State Key Laboratory of Acoustics of Chinese Academy of Sciences under Grant No SKLA201407;the Key Laboratory of Marine Surveying and Charting in Universities of Shandong of Shandong University of Science and Technology under Grant No 2013A02;the Scientific Research Foundation of Shandong University of Science and Technology for Recruited Talents under Grant No2014RCJJ004;the Project of the Public Science and Technology Research of Ocean under Grant No 201305034;the National Key Technology R&D Program under Grant No 2012BAB16B01

摘　　要：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.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.

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分 类 号：TB56[交通运输工程—水声工程]