As the core of the integrated navigation system, the data fusion algorithm should be designed seriously. In order to improve\nthe accuracy of data fusion, this work proposed an adaptive iterated extended Kalman (AIEKF) which used the noise statistics\nestimator in the iterated extended Kalman (IEKF), and then AIEKF is used to deal with the nonlinear problem in the inertial\nnavigation systems (INS)/wireless sensors networks (WSNs)-integrated navigation system. Practical test has been done to evaluate\nthe performance of the proposed method. The results show that the proposed method is effective to reduce the mean root-meansquare\nerror (RMSE) of position by about 92.53%, 67.93%, 55.97%, and 30.09% compared with the INS only,WSN, EKF, and IEKF.
Loading....