  There is a growing need to quickly and accurately identify anomalous behavior
in ships. This paper applies a variation of the Density Based Spatial
Clustering Among Noise (DBSCAN) algorithm to identify such anomalous behavior
given a ship's Automatic Identification System (AIS) data. This variation of
the DBSCAN algorithm has been previously introduced in the literature, and in
this study, we elucidate and explore the mathematical details of this algorithm
and introduce an alternative anomaly metric which is more statistically
informative than the one previously suggested.
