Name
Title | ||
|---|---|---|
A Fast-Initial Alignment Method With Angular Rate Aiding Based On Robust Kalman Filter |
Abstract | ||
|---|---|---|
In this paper, a fast-initial alignment method with angular rate aiding based on robust Kalman filter is proposed. First, the traditional system model of the initial alignment is derived, and the angular rate aiding method in the navigation frame is studied. To address the defects of the traditional angular rate aiding alignment method, the angular rate aiding method in body frame is derived. Then, a state augmentation method is employed to address the correlation between process noise and the measurement noise, which exists in the angular rate aiding methods. Considering the practical application, it is hard to keep completely still when the initial alignment is carried out on the vehicle. Therefore, a Huber's M-estimation has been adopted to eliminate the external interferences, and the robustness of the proposed method has been improved. Then, an analytical method for the observability of the proposed method is studied. The reason why the proposed method is faster than the traditional method is analyzed in detail. Finally, simulated and field tests are designed to validate the performance of the proposed method. The results show that the proposed method can finish the initial alignment when it is carried on the vehicle. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/ACCESS.2019.2910275 | IEEE ACCESS |
Keywords | Field | DocType |
Strapdown inertial navigation system (SINS), initial alignment, angular rate aiding, robust Kalman filter, state augmentation, analytical observability | Observability,Computer science,Algorithm,Process noise,Kalman filter,Robustness (computer science),System model,Distributed computing | Journal |
Volume | ISSN | Citations |
7 | 2169-3536 | 0 |
PageRank | References | Authors |
0.34 | 0 | 3 |