Visible to the public Adaptive filtering design for in-motion alignment of INS

TitleAdaptive filtering design for in-motion alignment of INS
Publication TypeConference Paper
Year of Publication2014
AuthorsTong Liu, Qian Xu, Yuejun Li
Conference NameControl and Decision Conference (2014 CCDC), The 26th Chinese
Date PublishedMay
Keywordsadaptive filtering, adaptive filtering approach, adaptive filters, Celso adaptive stochastic filtering, filtering theory, Global Positioning System, GPS data, in-motion alignment, inertial navigation, INS, INS-GPS integration, INS/GPS integration, jerk tracking model, Kalman filters, Mathematical model, misalignment angle estimation, Noise, Noise measurement, Outlier detection, statistical analysis, Stochastic processes, strapdown inertial navigation system, time varying statistical properties, Vehicles

Misalignment angles estimation of strapdown inertial navigation system (INS) using global positioning system (GPS) data is highly affected by measurement noises, especially with noises displaying time varying statistical properties. Hence, adaptive filtering approach is recommended for the purpose of improving the accuracy of in-motion alignment. In this paper, a simplified form of Celso's adaptive stochastic filtering is derived and applied to estimate both the INS error states and measurement noise statistics. To detect and bound the influence of outliers in INS/GPS integration, outlier detection based on jerk tracking model is also proposed. The accuracy and validity of the proposed algorithm is tested through ground based navigation experiments.

Citation Key6852624