The augmented UKF adds the computational complexity. To reduce the complexity EW proposed a simplified UKF method when the process noises and measurement noises are purely white. However this simplified method has been proven not to be optimal under linear conditions in this paper. In other words it is not equivalent to Kalman filter under linear conditions which means the method is not correct. And at the same time it is also given that the partially augmented UKF which only adds process noised to the state vector could achieve optimal estimation and also reduces the computational complexity to some certain extent. Finally the simulation results in GPS/INS integrated navigation system have further proved the theoretical analysis is correct.
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张晶. 基于部分扩维的无迹卡尔曼滤波算法研究[J]. 科学技术与工程, 2014, 14(24): . Zhang-Jing. Research on the Part Augmented Filtered Based on UKF[J]. Science Technology and Engineering,2014,14(24).