Abstract
High-frequency (HF) radars are operated in the 3-30 MHz frequency band and are known to cover ranges up to some thousand kilometers. Sky wave over-the-horizon radars (OTHR) utilize reflection by the ionosphere, but they require a transmit power up to 100 kilowatts. Especially for oceanographic applications, low power high frequency surface wave radar (HFSWR) systems have been developed, which use ground wave propagation along the salty ocean surface. The WERA HF radar system transmits a power as low as 30 watts, but achieves detection ranges up to 200 kilometers, which are far beyond the conventional microwave radar coverage. Due to external noise, radio frequency interference, and different kinds of clutter, special techniques for target detection have to be applied. This paper describes a new signal processing approach based on a curvilinear regression analysis for thresholding combined with a constant false-alarm-rate (CFAR) algorithm for detection. The target locations detected by the HF radar are passed to a tracking filter utilizing range, azimuth, as well as radial and azimuthal velocities to track the ship locations. For a 12-hour period real HF radar data from the WERA system were processed and secondary ship locations were recorded from the automatic identification system (AIS). This data set is used to assess the performance of the HF radar detections. Comparisons have been made for a maximum distance of 5 km between AIS and radar detected locations. The deviation between AIS and radar detected locations was below 1 kilometer in 77% of these comparisons. A number of ships was detected and tracked by the radar, but could not be used for comparisons due to the lack of AIS information.
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