Variable structure interacting multiple model algorithm for ship tracking using HF surface wave radar data

These last decades spawned a great interest towards low-power High-Frequency (HF) Surface-Wave (SW) radars for ocean remote sensing. By virtue of their over-the-horizon coverage capability and continuous-time mode of operation, these sensors are also effective long-range early-warning tools in maritime situational awareness applications. In this paper we show how it is possible to take advantage of a priori information on traffic by the means of a knowledge-based multi-target tracking algorithm, demonstrating that the tracking stage can be enhanced by combining on-line data from the HFSW radar with ship traffic information. A significant improvement of the proposed procedure, in terms of system performance, is demonstrated in comparison with the state-of-the-art approach recently presented in the literature. The main benefit of our approach is the ability to better follow targets without increasing the false alarm rate. The ability to follow targets can be over 30% better than existing methods. The proposed approach also exhibits a reduction of the track fragmentation. Average gains between the 13% and the 20% are observed.