Low-cost Tightly Coupled GPS/INS Integration Based on a Nonlinear Kalman Filtering Design

Y. Li, J. Wang, C. Rizos, P. Mumford, and W. Ding

Abstract:	This paper describes the design of a tightly coupled GPS/INS integration system based on nonlinear Kalman filtering methods. The traditional methods include linearization of the system around a nominal trajectory, and the extended Kalman filtering (EKF) method which linearizes the system around the previous estimate, or the predication, whichever is available. The recently proposed sigma-point Kalman filtering (SPKF) method uses a set of weighted samples (sigma points) to completely capture the first and second order moments of the prior random variable. In contrast to the EKF, the SPKF has a simpler implementation as it does not require the Jacobian matrices – the computation of which may lead to analytical or computational problems in some applications. This research is conducted under the Australian Cooperative Research Centre (CRC) for Spatial Information (CRC-SI) project 1.3 'Integrated Positioning and Geo-referencing Platform'. The project aims to develop a generic hardware/software platform for positioning and imaging sensor integration. The current work focuses on development of software and algorithms, and a field programmable gate arrays (FPGA) based GPS/INS data logging system. In the current development phase, a tightly coupled GPS/INS integration system based on a linearization around the INS solution has been designed and implemented. The system uses the GPS pseudorange and Doppler measurements to estimate the INS errors. This paper describes further developments of the integration filter design based on the EKF and SPKF methodologies, in order to compare the performance of nonlinear filtering approaches. Experimental results are presented and further planned developments are outlined.
Published in:	Proceedings of the 2006 National Technical Meeting of The Institute of Navigation January 18 - 20, 2006 Hyatt Regency Hotel Monterey, CA
Pages:	958 - 966
Cite this article:	Li, Y., Wang, J., Rizos, C., Mumford, P., Ding, W., "Low-cost Tightly Coupled GPS/INS Integration Based on a Nonlinear Kalman Filtering Design," Proceedings of the 2006 National Technical Meeting of The Institute of Navigation, Monterey, CA, January 2006, pp. 958-966.
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