Identifying ship echoes in CODAR HF radar data: A Kalman filtering approach

TLDR: The application of Kalman filtering to the ship tracking problem is explored, following the techniques described by J. V. Candy, and the approach is described and demonstrated with a simple example.

Abstract: Coastal nations have an interest in maritime domain awareness for applications in national security, coastal conservancy, fishery and stewardship of the exclusive economic zones (EEZs) along their coastlines. Maritime situational awareness involves knowing the location, speed and bearing of ships and boats in the EEZ. HF radar is a useful tool in providing ship information in real time. It is especially effective when combined with ship-borne AIS beacons. Our previously developed HF radar and AIS ship detection models estimate signal to noise ratio (SNR) as a function of range, including ducted propagation for the AIS radio signals. However, ship detection is hampered by the high variability of HF echoes from ships. This is due in part to the aspect dependence of ship radar cross-section and to the presence of clutter bands at known Doppler shifts from both the ground and ocean waves. Tracking ships using their HF radar echoes becomes the means for effectively monitoring the presence of ships in the coastal ocean. We explore the application of Kalman filtering to the ship tracking problem, following the techniques described by J. V. Candy. This approach is described and demonstrated with a simple example.