Knowledge-based ship tracking applied to HF surface wave radar data

In recent years, low-power high-frequency surface-wave radars have received significant attention thanks to their over-the-horizon coverage capability and the continuous-time operation mode. These radars have become effective long-range early-warning tools for maritime situational awareness applications. In this paper a knowledge-based multi-target tracking algorithm is described. The advantages in using a prior information on ship traffic are assessed exploiting real data acquired by two high-frequency surface-wave radars. The outcomes confirm the ability of the proposed approach to better follow targets with a time-on-target increment up to 30% with respect to existing methods. A reduction of the track fragmentation up to 20% is also observed.