Autonomous navigation based on information filter multi-model SCKF
Wenlong Yao, Guotao Zhuang, Boyang Li, Ailing Chen · 2017
In order to reduce the adverse effect of Unscented Kalman filter on the noise statistic characteristic, a novel multi-model SCKF algorithm is proposed to solve the nonlinear system filtering problem with noise uncertainty and was applied to the navigation system which the track of the spacecraft is determined in real time. The algorithm utilized the multi-model filtering principle, firstly the motion pattern of the system is mapped into the model set, and then the different noise characteristics of the system are mapped into the model set. Each model is filtered by SCKF. The algorithm combines the IMM and SCKF algorithm organically, it provide the new ideas and methods for solving the dynamic filtering problem of nonlinear systems.