Review: Interpolation of missing AIS data in water transport using machine learning

The table gives an insight into the scientific papers that dealt with the problem of insufficient number of AIS data when processing ship trajectories. Missing AIS data of a ship refers to the gaps or missing information in the Automatic Identification System (AIS) data transmitted by the ship, which can occur due to various factors such as signal interference, equipment malfunction, or other technical issues. These missing data points can lead to gaps in the vessel's trajectory, which can affect the accuracy of the ship's position, course, and speed information, and can potentially impact maritime safety and navigation. Interpolating missing AIS data can help to recover the lost data and produce useful information for VTS stations or other ships. Interpolation is a mathematical technique used to estimate the value of a function or data point between two known values. Interpolation methods are used to fill in missing data points or to estimate values at points where data is not available. There are various interpolation methods, including linear interpolation, polynomial interpolation, spline interpolation and others types of interpolation like Long Short-Term Memory (LSTM) network, Random Forest (RF) algorithm and U-Net. The choice of interpolation method depends on the nature of the data and the desired level of accuracy.