%0 Electronic Article %A Chen Qian %A Sheng Li %A Qingwei Chen %A Jian Guo %A Fei Yan %K filtering method %K integration rules %K filtering precision %K adaptation criterion %K online test %K marginalised adaptive sparse-grid quadrature filter %K accuracy level switching structure %K computation efficiency %K MASGQF %K marginalisation technique %K SINS alignment application %K strapdown inertial navigation system alignment process %X To effectively improve the computation efficiency in the strapdown inertial navigation system (SINS) alignment process, the authors propose a marginalised adaptive sparse-grid quadrature filter (MASGQF). The filtering method combines the virtues of marginalisation technique and accuracy level switching structure to decrease the computational burden and improve the filtering precision simultaneously. With the adaptation criterion and the predefined tolerance value, different integration rules corresponding to the different accuracy levels nested in the proposed filtering method can be adjusted autonomously. It is proved that the MASGQF is exponentially bounded by theoretical analysis. The performance comparison of different filtering methods is demonstrated by the numerical results of the simulation and offline experiment. On the basis of the data performance of the online test, the validity of the proposed MASGQF is verified in the SINS alignment application. %@ 1751-8822 %T MASGQF with application to SINS alignment %B IET Science, Measurement & Technology %D July 2020 %V 14 %N 5 %P 525-535 %I Institution of Engineering and Technology %U https://digital-library.theiet.org/;jsessionid=1fnc3687so03c.x-iet-live-01content/journals/10.1049/iet-smt.2019.0317 %G EN