Position and Velocity Detection with RADAR and GPS Fusion

In this paper, the fusion of distance and velocity measurements using radar and GPS is discussed. A Kalman Filter (KF) was designed for the fusion of the measurement results obtained with these different systems. The designed model was used to estimate the position and velocity of a runner. Different scenarios were produced and tested, such as error-free measurements for the entire time interval, unexpected measurements from radar or GPS satellites for a certain period of time. Root Mean Square Error values were calculated and the success of position and velocity estimations were examined. It has been observed that the designed Kalman Filter predictions are more successful than radar and GPS systems.