Simultaneous tracking of a maneuvering ship and its wake using Gaussian processes

Maneuvering ship tracking has applications in maritime surveillance and the performance of tracking algorithms is affected by background clutter and ship-generated wake. Previous works consider the wake as a form of clutter with some specific spatial distribution. In this paper, the Kelvin wake, which assumes that the ship-generated wake is V-shaped, is modelled as an extended target with an irregular and time-varying shape. Thus, the problem of maneuvering ship tracking in the presence of wake becomes a special multiple target tracking problem, where the ship is a point target and the wake is an extended target. A Gaussian Processes based Multiple Model Joint Probabilistic Data Association (GP-MM-JPDA) method is proposed to estimate the ship state and the wake state simultaneously. Two versions of the GP-MM-JPDA are implemented. The first one can be applied to most multiple target tracking problems and the second one is designed especially for the ship tracking problem. Both versions can improve the ship tracking performance. In addition, the proposed methods can also infer the ship length using the estimated wake angle, which facilitates ship classification. Simulation results show the effectiveness of the proposed methods.