Inertial navigation system calibration using GPS based on extended Kalman filter

Inertial navigation is a Newton rule-based method of determining the position and status of a moving object. For some reasons, this system is liable for increasing accuracy error. So in order to achieve higher accuracy, especially in long-term navigations, auxiliary systems are required. In this paper, error analysis and correction using integration of INS data with observations from velocity data of auxiliary navigation system (GPS), has been studied. Also integration of INS and GPS based on extended Kalman filter is simulated. Simulations for 1000 seconds of a moving object profile shows that fusion can correct INS modeling error and prevent diversions. Also, validation of Kalman filter estimation is proposed.