For the alignment in rotational inertial navigation system (RINS), which takes velocity errors of the navigation calculation as the filter measurements, the velocity error term caused by the coupling of the accelerometer’s inner lever arms (ILAs) and the gimbals’ angular motion will lead to a decline in the alignment accuracy. In view of that, a simplified model of the ILAs is proposed firstly in combination with the specific dual-axis rotation scheme, and then the ILAs are extended into state variables for filtering estimation, thereby improving the alignment accuracy. On this basis, in order to further improve the alignment rapidity, the bidirectional process-based rotation alignment method for dual-axis RINS is proposed in this paper. The bidirectional process, which combines the backward-forward RINS calculation and the backward-forward Kalman filtering, makes the best use of the stored IMU data repeatedly and is able to quickly obtain the IMU attitude matrix for RINS. The simulations and experiments show that the proposed bidirectional process-based rotation alignment method is able to accomplish the rapid and accurate alignment for the dual-axis RINS.
In an inertial navigation system (INS), it is generally assumed that three accelerometers in an inertial measurement unit measure the acceleration input at the same point in space. However, there are error vectors between the respective sensitive point of the three accelerometers and the theoretical measurement point, typically termed as inner lever arms (ILAs). In strapdown INS, the ILAs coupled with the carrier’s angular motion lead to a decline in navigation accuracy, while for dual-axis rotational INS (RINS), the ILAs coupled with the gimbals’ angular motion further introduce new navigation errors. Therefore, the calibration and compensation for the ILAs are important for enhancing the systemic reliability. In this paper, an ILA self-calibration method is proposed by leveraging the rotation gimbals of the RINS. To be able to obtain all the ILA parameters, we establish an error model by considering the ILAs, and design a reasonable rotation scheme to ensure all parameters observable. The simulations and experiments show that the proposed self-calibration method is able to accomplish the rapid and accurate estimation of all the ILAs and the velocity stage and slope errors are greatly corrected after compensation by the calibration results.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.