A Method for Automatic Lever-arm Estimation in Loosely-coupled GNSS/INS Integration System using Unscented Particle Filter

Y. Geng, R. Deurloo, L. Bastos

Abstract:	GNSS/INS integration is nowadays a standard approach for different navigation and remote sensing applications that involve position and velocity information. Physically, the inertial measurement unit (IMU), namely the sensors of the INS, and the GNSS antennas (as well as other auxiliary sensors that maybe used) cannot be mounted at the same position in a real system. Lever-arm uncertainty can be a serious problem in application where accurate position and navigation information is needed. Thus, the implementation of an universal method which has the ability to estimate the unknown lever-arm uncertainty automatically can be a real added value for the full exploitation of an GNSS/INS system. To develop the universal method for unknown lever-arm estimation, a basic set of error models for a strapdown INS for the integrated navigation system with unknown lever-arm has been derived. This includes the navigation parameters, the inertial sensor errors and the unknown lever-arm error states. A novel hybrid Unscented Particle filter was proposed for unknown lever-arm estimation in loosely coupled GNSS/INS integration system. The proposed algorithm takes advantage of both the linear time propagation of Kalman filter and nonlinear measurement propagation of Unscented Kalman filter. From both the simulation and field results, it can be shown that the proposed algorithm has the ability to estimate the lever-arm uncertain under the manoeuvre of the vehicle.
Published in:	Proceedings of the 2011 International Technical Meeting of The Institute of Navigation January 24 - 26, 2011 Catamaran Resort Hotel San Diego, CA
Pages:	841 - 849
Cite this article:	Geng, Y., Deurloo, R., Bastos, L., "A Method for Automatic Lever-arm Estimation in Loosely-coupled GNSS/INS Integration System using Unscented Particle Filter," Proceedings of the 2011 International Technical Meeting of The Institute of Navigation, San Diego, CA, January 2011, pp. 841-849.
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