Anomaly detection in VHF radar measurements

The present work develops a new aspect in the use of HF radar as a tool for real time operational oceanography. We propose to implement new algorithms for detecting anomalies (outliers) on VHF radar data. Perspectives of such work are to detect changes in sea surface, such as ship or oil pollution. In this preliminary work, no information are given about the anomalies. We propose to study new detection methods based on Support Vector expansion to perform a binary separation between observations. This technique is well adapted to HF radar observations that are never statistically representative but give a good temporal resolution