Radar Target Classification using Recursive Knowledge-Based Methods

The topic of this thesis is target classification of radar tracks from a 2D mechanically scanning coastal surveillance radar. The measurements provided by the radar are position data and therefore the classification is mainly based on kinematic data, which is deduced from the position. The target classes used in this work are classes, which are normal for coastal surveillance e.g.~ships, helicopters, birds etc. The classifier must be recursive as all data of a track is not present at any given moment. If all data were available, it would be too late to classify the track, as the track would have been terminated. Therefore, an update of the classification results must be made for each measurement of the target. The data for this work are collected throughout the PhD and are both collected from radars and other sensors such as GPS.