Automatic Identification System (AIS) Dynamic Data Estimation Based on Discrete Kalman Filter (KF) Algorithm

Due to the safety reason, the ship movement on the littoral area should be monitored, tracked, recorded and stored. Automatic Identification System (AIS) is the perfect tool to ensure this requirement. The limit probability for the AIS dynamic data availability can be limited by the lack of Global Position System (GPS) signal, heading (HDG) and rate of turn (ROT) data in position report. Availability of data link is an additional limitation. For this purpose, it is possible to attach the Discrete Kalman filter (KF) for the position, and course estimation. Coordinate estimation in the absence of a transmission link can improve the quality of AIS service at Vessel Traffic Service (VTS) stations. This article presents Kalman filtering algorithm to improve the possibilities of ship motion tracking and monitoring in the TSS (Traffic Separation Scheme) and fairways area. Only 39 iterations were presented to familiarize how the Kalman filter algorithm works. The archival data from 2006 were used deliberately. During that time, there were problems with the AIS availability service. With the use of measurements series from those years, it is easier to observe the effectiveness of Kalman filter in absence of AIS data.