Self-Calibration of Tri-Axis Rotational Inertial Navigation System Based on Virtual Platform

There exist two structures of tri-axis rotational inertial navigation systems (TRINSs), namely, the outer-azimuth and inner-azimuth systems. Accurate calibration is one of the key endeavors toward high-precision TRINS. Regarding the TRINS calibration, there is a strict requirement of the navigation platform definition for the rotation excitation sequence. It means that one rotation excitation sequence cannot be applied to both outer-azimuth and inner-azimuth TRINSs. In this article, a virtual platform is constructed that is different from the usual navigation platform, the virtual platform is obtained by performing specific orthogonal transformation according to the requirements of the application scenario: one is to perform an orthogonal transformation on the g-frame and a-frame, and the other is to perform an orthogonal transformation on the p-frame. Based on the self-calibration rotation excitation sequence of the inner-azimuth TRINS, the Kalman filtering is employed to estimate the error parameters in the virtual platform that are then used to calibrate the outer-azimuth TRINS. Real tests with an outer-azimuth TRINS show that the proposed calibration method achieves the scale-factor accuracy of 0.51 ppm and installation accuracy of 0.11 '' for gyroscopes, and the scalefactor accuracy of 1.56 ppm, and the installation accuracy of 0.17 '' for accelerometers, the proposed method can improve the observability of self-calibration.