@article{Stateczny_Kazimierski_2008, author = {Stateczny, Andrzej and Kazimierski, Witold}, title = {The Process of Radar Tracking by Means of GRNN Artificial Neural Network with Dynamically Adapted Teaching Sequence Length in Algorithmic Depiction}, journal = {TransNav, the International Journal on Marine Navigation and Safety of Sea Transportation}, volume = {2}, number = {1}, pages = {45-50}, year = {2008}, url = {./Article_The_Process_of_Radar_Tracking_by_Stateczny,5,70.html}, abstract = {The radar with the function of automatic target tracking is the navigator?s basic aid in estimating a collision situation with regard to his own vessel. The quality of radar tracking process affects the reliability of data provided to the navigator for situation assessment, including the vessel?s safety. The use of artificial intelligence methods (GRNN network in particular) for this purpose permits a decrease of tracking errors and the shortening of delay of the vector presented in relation to real time. The article presents an algorithmic depiction of radar tracking by means of GRNN-based neural filter. There have been presented a filter diagram, an algorithm of GRNN parameter selection, manoeuvre detection, as well as the process of radar tracking by means of this filter.}, issn = {2083-6473}, publisher = {Gdynia Maritime University, Faculty of Navigation}, keywords = {Aids to Navigation (AtoN), Radar Tracking, GRNN Artificial Neural Network, Algorithmic Depiction, Dynamically Adapted Teaching Sequence Length, Artificial Intelligence (AI), Manoeuvre Detection, Filter Diagram} }