Comparison of proposed target tracking algorithm, GRNNa, to Kalman Filter in 3D environment

In this study, the method we proposed GRNNa which is the specialized General Regression Neural Network (GRNN) algorithm, was used for estimating the target position in 3 Dimensional (3D) measurement environment. Although GRNN has only been used for estimating target velocity, GRNNa has the capability of estimating target´s position as successful as the well known Kalman Filter (KF) algorithm. The performances of the mentioned algorithms are compared using simulated take-off and landing routes of aircrafts.