Enhancing Autonomous Ground Vehicle Positioning and Navigation through Cascaded Multi-Sensor Integration

Precise positioning and navigation are crucial for autonomous vehicles. An attempt to improve the preciseness of position and navigation measurements is made by using multiple sensors. This research proposes a multi-sensor integrated positioning and navigation system using cascaded data fusion for ground vehicles. The system consists of multiple Inertial Measurement Units (IMUs) and a Global Navigation Satellite System (GNSS) receiver. An approach for fusing multiple redundant IMUs using a weighted average is proposed to obtain a virtual IMU. The virtual IMU and GNSS are integrated using a loosely-coupled approach. The system is tested on a ground vehicle with particle models. Two datasets are used: one collected on a straight road and another collected in a suburban area. The results show that the proposed method improves the preciseness of position and navigation measurement.