The Unified Mathematical Framework for IMU Preintegration in Inertial-Aided Navigation System
This work addresses the need for robust and adaptable state estimation in inertial-integrated navigation systems, particularly for applications in varying environments and motion conditions, representing an incremental improvement over existing methods.
The paper tackles the problem of IMU preintegration in inertial-aided navigation by proposing a unified mathematical framework that discretizes the navigation state into local and global increments, enabling more accurate and convenient online state estimation across different frames and motion conditions. It introduces covariance propagation based on left perturbation, independent of sensor inputs, and demonstrates monotonicity of uncertainty for optimality criteria.
This paper proposes a unified mathematical framework for inertial measurement unit (IMU) preintegration in inertial-aided navigation system in different frames under different motion condition. The navigation state is precisely discretized as three parts: local increment, global state, and global increment. The global increment can be calculated in different frames such as local geodetic navigation frame and earth-centered-earth-fixed frame. The local increment which is referred as the IMU preintegration can be calculated under different assumptions according to the motion of the agent and the grade of the IMU. Thus, it more accurate and more convenient for online state estimation of inertial-integrated navigation system under different environment. Furthermore, the covariance propagation based on left perturbation is proposed for the first time, which is independent of the inputs of the gyroscope and accelerometer. Finally, we show the monotonicity of the uncertainty for determinant optimality criteria and Rényi entropy optimality criteria.