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Monitoring coastal vessels for environmental applications: Application of Kalman filtering

Maritime domain awareness is important for coastal nations in terms of applications to coastal conservancy, security, fishery and stewardship of their exclusive economic zones (EEZs). 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 information from 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 false targets related to wave echoes, interference and the high variability of HF echoes from ships. This is due in part to the aspect and frequency dependence of ship radar cross-section and to the presence of clutter bands at known Doppler shifts from both the ground and ocean surfaces. Distinguishing ship echoes from false alarm echoes is significantly aided by identifying radar targets with ship-like behavior. Thus, tracking ships using their HF radar echoes becomes an important means for effectively monitoring the presence of ships in the coastal ocean. We demonstrate the application of Kalman filtering to the ship-tracking problem with examples using data from the COCMP HF radar network along the California coast. As with other radar tracking problems, the Kalman approach proves effective in this application as well.