SINS／GPS tightly integrated algorithm with gaussian particle filter

Abstract:

To improve the reliability of integrated navigation, a tightly coupling nonlinear model based on pseudo range and rate is proposed for reducing the estimation error of tradi-tional algorithm using linear measurement model in this work. For the application of particle filtering to SINS/GPS tightly integrated navigation system, the dimension of the state variables has been a major constraint for the Real-time system. In this new arithmetic, a linear KF deduction and nonlinear GPF method have been employed for the linear part and the non-linear part to improve the precision and real time performance, respectively. Results from the simulation show that the hybrid algorithm can effectively improve the performance of the integrated navigation system, and the precision increases one time.