Joint estimation of system error and state based on cubature Kalman filter

Aiming at the adverse effects on state estimation precision caused by measurement system error, a novel joint estimation algorithm of system error and state is proposed in this paper. In the new algorithm, combined with the expansion technique of state vector dimension, the error registration model is firstly constructed in the nonlinear filtering framework. Secondly, system error is estimated effectively on the basis of the error registration model, and the adverse effect of system error from measurement residual on filtering precision is improved by the amendment of measurement prediction in cubature Kalman filter. The theoretical analysis and simulation results show the feasibility and effectiveness of the proposed algorithm. ©, 2015, Board of Optronics Lasers. All right reserved.