Bayesian Tracking in an Uncertain Shallow Water Environment

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.