Adaptive filtering design for in-motion alignment of INS

Submitted by BrandonB on Wed, 05/06/2015 - 9:35am

Title	Adaptive filtering design for in-motion alignment of INS
Publication Type	Conference Paper
Year of Publication	2014
Authors	Tong Liu, Qian Xu, Yuejun Li
Conference Name	Control and Decision Conference (2014 CCDC), The 26th Chinese
Date Published	May
Keywords	adaptive 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
Abstract	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.
URL	http://ieeexplore.ieee.org/document/6852624/
DOI	10.1109/CCDC.2014.6852624
Citation Key	6852624

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Science of Security VO