In-Motion Alignment with MEMS-IMU Using Multilocal Linearization Detection

In-motion alignment is a critical step in obtaining the initial state of an integrated navigation system. This article considers the in-motion initial alignment problem using the multilocal linearization detection method. In contrast to the OBA-based method, which fully relies on satellite signals to estimate the initial state of the Kalman filter, the proposed method utilizes the designed quasi-uniform quaternion generation method to estimate several possible initial states. Then, the proposed method selects the most probable result based on the generalized Schweppe likelihood ratios among multiple hypotheses. The experiment result of the proposed method demonstrates the advantage of estimation performance within poor-quality measurement conditions for the long-duration coarse alignment using MEMS-IMU compared with the OBA-based method. The proposed method has potential applications in alignment tasks for low-cost, small-scale vehicle navigation systems.