A Dual-IMU Positioning System Based on IHDE and Multiconstraint Framework

Inertial navigation systems (INS) provide continuous high-frequency positioning with inherent stability. The pedestrian positioning system based on INS is considered to be an important application of the Global Navigation Satellite System (GNSS)-degraded environments and open outdoor scenarios, including but not limited to emergency rescue, security patrol, soldier positioning, and many other fields. To improve the positioning accuracy of the pedestrian inertial navigation system, a dual-IMU positioning correction algorithm is proposed. First, an improved Heuristic Drift Elimination (IHDE) algorithm is proposed. The IHDE establishes a linear regression model for the INS positioning solution of a single IMU, and the observation vector and observation matrix based on the type of pedestrian motion are constructed to reduce the INS error by combining the heading difference between the main heading and the calculated heading. Then, the pedestrian’s two-foot constraint relationship is used to establish a constraint model to mutually constrain the position information of the left and right foot to correct the positioning accuracy. Comprehensive experiments demonstrate that the proposed algorithm achieves that the solved trajectory is closer to the real trajectory, and the average closed-loop error is reduced from 2.6%D to 0.3%D compared with the traditional mechanical algorithm. In summary, the proposed algorithm effectively improves the INS positioning accuracy and has high value in engineering applications.