An Underwater Target Tracking Algorithm Based on Extended Kalman Filter

The technology of ocean monitoring is more advanced while the continuous development of industrial Internet. Unmanned underwater vehicle (UUV) is one of major ways for underwater environment monitoring, which makes high-precision positioning, and tracking of it is one of the key problems and needs to be solved urgently. An underwater acoustic positioning and tracking algorithm based on multiple beacons is proposed to reduce the positioning error of underwater acoustic positioning system caused by uncertain sound speed. The system consists of multiple GPS intelligent buoys floated on the sea surface and acoustic signal generator installed on the UUV. The effective sound speeds between the UUV and different buoys are considered to be unequal and estimated as the state parameters, together with the kinematic parameters of the UUV. Based on the kinematic equations of the UUV, the tracking model is obtained under the framework of the extended Kalman filter. Simulation results show that the proposed algorithm can correct the sound speed and improve the stability and accuracy of underwater acoustic positioning system.