A Novel High-Precision Trajectory Generator with Complex Motion Simulation for Enhanced Inertial Navigation Algorithm Testing

With advancements in inertial navigation measurement units (IMUs), the focus of inertial navigation accuracy has shifted from hardware limitations to algorithm performance. To effectively test algorithms using high-precision IMUs, trajectory generators are essential; however, existing generators often lack diverse motion patterns, making them inadequate for evaluating algorithms under complex and challenging conditions, particularly for unmanned aerial vehicle (UAV) applications. To address this, we designed a high-precision trajectory generator that enhances traditional models by incorporating coning motion, paddle motion, and coning motion with angular velocity precession to simulate high-dynamic environments. Additionally, a one-sample-plus-one-previous-per-update algorithm was developed to improve the accuracy of the IMU output inversion by generating precise gyroscope and accelerometer data for processing within inertial navigation systems. The results demonstrate that both the one-sample-plus-one-previous-per-update and three-sample algorithms significantly improve the navigation accuracy under high-dynamic motion compared to single-sample algorithms. This trajectory generator effectively validates the accuracy of inertial navigation algorithms in complex conditions, particularly for UAVs, and provides a solid foundation for testing higher-precision algorithms.The proposed methodology directly supports the development of advanced actuator control systems in UAVs by enabling rigorous validation of navigation algorithms under realistic high-dynamic scenarios, a critical requirement for next-generation autonomous platforms.