Online Stochastic Modelling for INS/GPS Integration

Jinling Wang, Mike Stewart and Maria Tsakiri

Abstract:	GPS and inertial navigation systems (INS) are widely used in autonomous positioning and attitude determination. Although each system has its own performance character-istics, integration of GPS with INS can overcome their shortcomings. Moreover, such a multi-sensor integration can significantly improve the integrity of positioning and thus provide reliable geometric reference information for wide range of applications. INS/GPS integration, the combination of raw measure-ments from INS and GPS sensors, can be implemented using Kalman filtering techniques. Reliable Kalman fil-tering results, however, rely heavily on the correct defini-tion of the stochastic model used in the filtering process. The stochastic model is mainly given by the covariance matrices of the measurement errors and the process noises. Because the error features for each sensor are different and vary over time, an online stochastic modelling method must be implemented in the integrated system to ensure reliable navigation results. In this paper, an online stochastic modelling method is in-troduced to adaptively estimate the stochastic model real-time. The principle idea of the method is that the (post-fitted) filtering residuals collected from the previous segment of positioning results are used to estimate the sto-chastic model for the current epoch. Test results indicate that using such an online stochastic modelling method can improve the success rate of ambiguity resolution and the precision of the estimated navigation parameters.
Published in:	Proceedings of the 12th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GPS 1999) September 14 - 17, 1999 Nashville, TN
Pages:	1887 - 1896
Cite this article:	Wang, Jinling, Stewart, Mike, Tsakiri, Maria, "Online Stochastic Modelling for INS/GPS Integration," Proceedings of the 12th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GPS 1999), Nashville, TN, September 1999, pp. 1887-1896.
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