A Square-Root Adaptive Filtering Algorithm for Accuracy Estimation of Transfer Alignment

Since the parameters of the Inertial Navigation System(INS) model usually have some deviations from the actual physical process,and the noise statistic characteristic is not exactly known,the normal Kalman filter may behave badly or diverge.For the purpose of estimating transfer alignment accuracy,a square-root adaptive filtering algorithm based on combination of square-root filtering and adaptive filtering algorithm was proposed to meet the estimating accuracy and stability demands.A simplified time-varying noise estimator was set between the time updating and measurement updating process of square-root filtering,which may restrict modeling divergence and computational divergence.Finally,the new algorithm was compared with typical Kalman filtering algorithm and simplified Sage-Husa adaptive algorithm.The digital simulation showed that the algorithm can not only strengthen the filtering convergence capability,but also improve the estimating accuracy,which can estimate the accuracy of transfer alignment efficiently.