一种简化的发射系下SINS/GPS/CNS组合导航系统无迹卡尔曼滤波算法.

Each state of integrated navigation system is strongly nonlinear and coupled with each other under missile-borne high-dynamic environment. Since the traditional extended Kalman filter algorithm ignors the interaction of higher order terms, its linear expansion may teads to its inaccuracy and the decrease in navigation precision. UKF algorithm can effectively avoid bringing a linearization error, but the real-time of the algorithm can be affected by the complex filtering calculation for a large number of particles in high-dimensional integrated navigation system. A simplified unscented Kalman filter(SUKF) algorithm isproposed for the requirement of high real-time and accuracy for the missile-borne integrated navigation system in launch inertial coordinate system. SUKF can be used to directly estimates the state parameters of the navigation system to achieve the real-time and improve the navigation precision without linearization extension in traditional EKF. The simulation results show that SUKF effectively improves the real-time and filtering precision of algorithm, so SUKF is very suitable for the actual engineering system. [ABSTRACT FROM AUTHOR]