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A robust in-motion attitude alignment method for odometer-aided strapdown inertial navigation system
Yiding Sun1, Gongliu Yang1, Qingzhong Cai1
1School of Instrumentation and Optoelectronics Engineering, Beihang University, 37 Xueyuan Road, Beijing 100191, China.
Abstract:
A significant issue of land vehicle navigation is in-motion attitude alignment of the odometer (OD)-aided strapdown inertial navigation system (SINS). The consecutive OD outliers can occur due to sudden wheel slipping and skidding while vehicle maneuvering. They seriously reduce the robustness and precision of attitude alignment. In this paper, we investigate a robust in-motion attitude alignment method for the OD-aided SINS. The method consists of in-motion coarse alignment and in-motion fine alignment. In the in-motion coarse alignment process, we developed Huber's M-estimation and integral formula based robust Kalman filter (HRKF/IF-CA), which can restrain the interference of consecutive OD outliers on reconstructed observation vectors. Thus, HRKF/IF-CA can contribute to better coarse attitude results. The next process is in-motion fine alignment. Under the popular repeated backtracking scheme, we investigate HRKF based fine alignment (HRKF-FA) with the SINS/OD summed measurement model. HRKF-FA can refine attitude alignment and restrain the interference of consecutive OD outliers simultaneously. Finally, the proposed method is evaluated by simulation and vehicle test. The attitude alignment results show that this method can achieve reasonable attitude results, and the interference of consecutive OD outliers caused by sudden wheel slipping and skidding can be greatly restrained.
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