Recently, the newest methods based on Artificial Intelligence (AI) are used in order to provide reliable positioning information for various navigation applications for ground vehicles with the help of (GNSS) technology, with integrated inertial navigation system (INS).

All existing methods based on Artificial Intelligence (AI) rest upon the INS system error regarding the correct INS operation, at certain times, and do not take into account the error relation for the past INS values. This study presented, therefore, suggests the use of entry-Delayed Networks Neural (IDNN) to model both the INS position and velocity errors based on past samples of the...