Sensor Fusion for Ocean Surface Wind, Wave and Current parameter Estimation and AIS Target Detection and Anti-Spoofing

High-frequency surface wave radar (HFSWR) is recognized as one of the essential tools for remote sensing of the ocean surface because it provides wide-area, all-weather, and near-real-time surveillance. It operates between 3 to 30 MHz and can detect a large area of thousands of square kilometers. Wind speed, wind direction, surface current, and significant wave height can be extracted from HFSWR Doppler spectra.
Although such methods can perform satisfactorily for ocean surface wave parameter estimation, there are other sensors that can provide better spatial resolution than HFSWR on its own. These sensors include Xband radar, which provides very good spatial resolution for parameter estimation, though usually with a reduced maximum range. Satellite imagery can provide parameter estimation over a very large area, however the spatial resolution is limited by the quality of the imagery and the temporal resolution may also be limited. By combining the data from all of these sensors, and possibly others, it is believed that estimates with high spatial and data resolutions for ocean surface wind, wave and current parameters may be extracted from the data from these various sources.

Faculty Supervisor:

Reza Shahidi;Eric Gill

Student:

Partner:

Springboard Atlantic Inc.

Discipline:

Engineering

Sector:

Ocean Tech; Other

University:

Memorial University of Newfoundland

Program: