In this paper, the position, velocity and attitude of a Hybrid Autonomous Underwater Glider (HAUG) have estimated by fusion of inertial navigation system (INS) and Doppler velocity log (DVL) to optimize the variables estimation. The filters have been used for estimate the position, velocity and attitude of HAUG, namely Extended Kalman Filter. In the EKF is implemented using nonlinear kinematic model of state error vector. The Allan variance method is used to calculate matrix Q and R parameters. Output of the system was estimated position, attitude and velocity of the vehicle. The result in open loop simulation of navigation process will compared to the output of model vehicle. The estimates have accurate results shown with graphs and average of error.