This research will validate and test new methods for Direction of Arrival (DOA) processing in SeaSonde HF radars based on the use of open source Artificial Intelligence (AI) and Machine Learning (ML) algorithms. The new methods will improve accuracy and quantify uncertainty in the ocean current measurements, and simplify calibration of the HF radars, reducing operational efforts and costs. These research goals are aligned with the goals and objectives of Dr. Brian Emery’s research and expertise, and have been driven in part by his previous work. Dr. Emery will conduct testing and validation analysis in collaboration with partners at CODAR Ocean Sensors, Ltd. These efforts will utilize a unique dataset of collocated drifter and HF radar observations, previously collected by UCSB researchers, specifically designed for validating and testing improved DOA methods.