The target signal received by acoustic sensor has the characters of time-delay and bearingonly. The problems of time-delay registration and target locating can be solved by composing acoustic sensor network. In this paper, a MVEKF (Modified covariance Extended Kalman Filtering) based passive acoustic network localization algorithm is present According to the time-delay equation, the target bearing angle will be corrected firstly. Then it modified the covariance matrix in filtering process. Finally, get the position estimation of the target The simulation results show that, compared with the EKF method algorithm, it improves convergence speed, positioning accuracy and has better tracking performance.
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