A Rule-based Track Anomaly Detection Algorithm for Maritime Force Protection

We developed an anomaly detection tool using a Rule-based Algorithm that can detect anomalies in a set of pre-recorded tracks using their curvature, speed and weave. We devised a method that can quantify the amount of curvature in a recorded surface track. The anomaly detection tool uses the limiting values for curvature, speed and weaving provided by the user to classify a track as normal or anomalous . We tested two data sets consisting of radar tracks recorded in May and August 2007. We varied the threshold values that the tool uses. We compared the results of the tool s analysis of the data sets with a visual inspection performed by a navy combat system operator. The results of the tool s analysis were in good agreement with those of the visual inspection.