Gravity adaptive parallel EKF matching algorithm based on CEP
In the existing inertial,gravity and gravity gradient integrated matching navigation,the model error of the EKF state equation and the filtering inaccuracy and divergence caused by the cumulative error of the inertial navigation system(INS)is of critical importance,an adaptive parallel EKF matching algorithm based on CEP(circular error possible)is proposed in this paper.Firstly,to weaken the error caused by the inaccuracy of the preset dynamic model,the weight of state prediction information is adjusted by adaptive factors.And using the circular probability error radius of INS,the sliding window layered model based on CEP is constructed simultaneously.Then,based on the filter measurement and window slope,the range of sliding window is constrained.Finally,a layered window parallel filter is established to obtain the optimal result.The experimental results in the South China Sea show that compared with the traditional EKF and the adaptive EKF algorithm,the positioning accuracies of proposed method are improved by 74.0％and 49.8％,respectively.With the proposed algorithm,the accumulation of time-lapse errors using INS can be shortened to some extent,and the positioning accuracy and robustness can be enhanced.
NETL
NSTL
万方数据
维普
