GPS/INS integration using nonlinear blending filters

In this paper we use four nonlinear blending filters in order to integrate global positioning system and strapdown inertial navigation system (GPS/SDINS). As we will see in this paper, the Unscented Kalman filter (UKF) in comparison with extended Kalman filter (EKF), central difference Kalman filter (CDKF) and particle filters (PFs) has the best performance both in estimation accuracy and computation time. It will also give us more reliable solution when encountering satellite signal blockage as a probable problem in land navigation. The results have clearly demonstrated that the UKF would improve the guidance from the point of accuracy and computation time to the mentioned problems.