摘要

Sections 1 though 4 of the full paper explain our algorithm mentioned in the title, which we believe is better than existing ones. Their core consists of: (1) due to the problem of weak observability of yaw angle in Chinese low-cost MIMU/GPS integrated navigation for land vehicle, we put forward a new measurement equation adding the information of yaw angle determined from GPS velocity, which enhances the observability of yaw angle and solves the problem; MINU stands for Miniature Inertial Measurement Unit and GPS stands for Global Positioning System; (2) for improving the efficiency of real-time calculations and considering hard-to-obtain statistical properties of low-precision inertial devices, we adopt reduced order state model; (3) our filter algorithm, which combines that of the modified strong tracking Kalman filter with that of the UD decomposition filter, is designed to suppress the filter divergence cause of imprecise model. The experimental results, presented in Figs.2 through 7 and Table 1, and their analysis show preliminarily that our algorithm is indeed better for the low-cost MIMU/GPS integrated navigation system for land vehicle.

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