GPS/GLONASS/SINS synergistic integration into flight vehicle for optimal navigation solution

This paper aims the importance of GPS/GLONASS/SINS integration into flight vehicle and the optimal use of twenty seven error states by using various error models such as SINS error model, sensors error model and GPS/GLONASS error model. The main riveted part of system model is the inclusion of GPS/GLONASS error model. Position and velocity errors of GPS as random clock errors are used as first order markov process noise inside the system model. This error model, describing the error states is considered as first order differential equation. In this paper a system model for GPS/GLONASS/SINS integration is designed and applied. Loosely coupled closed loop Kalman filter architecture is realized for this mission for its robustness and less sensitivity to parameter variations. North pointing navigation algorithm and its error model is developed and evaluated in this integration mode. The local frame ENU is used as the navigation frame. The integrated system uses the position and velocity as measurements. Both the integrated GPS/GLONASS/SINS and the stand alone noisy sensor SINS navigation simulations results are analyzed, and compared to reference ideal trajectory navigation parameters. The numerical computer simulation results demonstrate the optimal performance of GPS/GLONASS/SINS integration with required accuracy for the mission.