Stochastic integration H_∞ filter for rapid transfer alignment of INS

The performance of an inertial navigation system (INS) operated on a moving base greatly depends on the accuracy of rapid transfer alignment (RTA). However, in practice, the coexistence of large initial attitude errors and uncertain observation noise statistics poses a great challenge for the estimation accuracy of misalignment angles. This study aims to develop a novel robust nonlinear filter, namely the stochastic integration H_∞ filter (SIH_∞ F) for improving both the accuracy and robustness of RTA. In this new nonlinear H_∞ filter, the stochastic spherical-radial integration rule is incorporated with the framework of the derivative-free H_∞ filter for the first time, and the resulting SIH_∞ F simultaneously attenuates the negative effect in estimations caused by significant nonlinearity and large uncertainty. Comparisons between the SIH_∞ F and previously well-known methodologies are carried out by means of numerical simulation and a van test. The results demonstrate that the newly-proposed method outperforms the cubature H_∞ filter. Moreover, the SIH_∞ F inherits the benefit of the traditional stochastic integration filter, but with more robustness in the presence of uncertainty.