  Inertial measurement unit (IMU) preintegration is widely used in factor graph
optimization (FGO); e.g., in visual-inertial navigation system and global
navigation satellite system/inertial navigation system (GNSS/INS) integration.
However, most existing IMU preintegration models ignore the Earth's rotation
and lack delicate integration processes, and these limitations severely degrade
the INS accuracy. In this study, we construct a refined IMU preintegration
model that incorporates the Earth's rotation, and analytically compute the
covariance and Jacobian matrix. To mitigate the impact caused by sensors other
than IMU in the evaluation system, FGO-based GNSS/INS integration is adopted to
quantitatively evaluate the accuracy of the refined preintegration. Compared to
a classic filtering-based GNSS/INS integration baseline, the employed FGO-based
integration using the refined preintegration yields the same accuracy. In
contrast, the existing rough preintegration yields significant accuracy
degradation. The performance difference between the refined and rough
preintegration models can exceed 200% for an industrial-grade MEMS module and
10% for a consumer-grade MEMS chip. Clearly, the Earth's rotation is the major
factor to be considered in IMU preintegration in order to maintain the IMU
precision, even for a consumer-grade IMU.
