Validation of Automatic Identification System Information With Exteroceptive Sensor Fusion for Unmanned Marine Operations

The automatic identification system (AIS) can improve situational awareness at sea, but its protocol is simple and does not guarantee message integrity, authentication, and proper use. For example, the lack of safety measures creates problems when AIS messages are used for tracking a target or predicting a target trajectory. We present a methodology for the validation of AIS messages, a prerequisite for their safe use in maritime situational awareness applications. The validation method relies on target trackers that fuse AIS data and exteroceptive sensor data, and it detects errors in position, speed and course, and rate of turn. We use radar data to exemplify exteroceptive sensor data. With the use of simulated data, we show that the proposed methods effectively detect errors in the position and velocity data received through AIS messages and are also able to detect errors in turn-rate data. The effectiveness of the methods is demonstrated on a real-world dataset with injected false AIS data.