HawkEye 360 Inc., a global leader in commercial space-based Radio Frequency (RF) data and analytics, has announced the launch of a new maritime association analytics capability that analyses RF signal geolocations and third-party global AIS maritime geolocations to provide insight into potential dark ship activity in key areas of interest (AOI) globally.
Tim Pavlick, Vice President of Product, Design, and AI said, “Finding dark vessels and illicit maritime activity shouldn’t involve endless trial and error and manual analysis with various data sources. HawkEye 360 is transforming Multi-INT sources into critical insights and creating analytic tools that multiply the value of RF monitoring by an order of magnitude, allowing analysts to gain a more holistic understanding of areas and events that matter most to them.”
Organizations can use marine insights to better analyze anomalies in the maritime domain and to collect intelligence more effectively using various collection and surveillance methods. Coast guards, navies, law enforcement, fisheries, and non-profit groups will be able to improve marine domain awareness and swiftly discover RF activity that cannot be linked to publicly identified maritime activity using this capacity.
Chief Growth Officer, Alex Fox, said, “Illicit activities at sea continue to rise, costing global economies billions of dollars and threatening global security. HawkEye 360’s unique capability can detect and geolocate dark ship activity across the globe and provide trusted analytics to support enforcement and prosecution associated with these activities. Our subscription services monitor millions of square kilometers of ocean to detect activities such as illegal fishing, which alone costs the global economy $10-$24 billion dollars per year.”
The algorithm analyzes the time and space attributes of HawkEye 360 and AIS data sets in order to automatically associate RF signal geolocations and vessel AIS data. Maritime Mobile Service Identity numbers and numeric scores are associated with geolocations that have a high probability of matching. RF geolocations are classified as DarkRF when there are no associations for them.
