title: Performance enhancement for a GPS vector-tracking loop utilizing an adaptive iterated extended Kalman filter.
abstract: This paper deals with the problem of state estimation for the vector-tracking loop of a software-defined Global Positioning System (GPS) receiver. For a nonlinear system that has the model error and white Gaussian noise, a noise statistics estimator is used to estimate the model error, and based on this, a modified iterated extended Kalman filter (IEKF) named adaptive iterated Kalman filter (AIEKF) is proposed. A vector-tracking GPS receiver utilizing AIEKF is implemented to evaluate the performance of the proposed method. Through road tests, it is shown that the proposed method has an obvious accuracy advantage over the IEKF and Adaptive Extended Kalman filter (AEKF) in position determination. The results show that the proposed method is effective to reduce the root-mean-square error (RMSE) of position (including longitude, latitude and altitude). Comparing with EKF, the position RMSE values of AIEKF are reduced by about 45.1%, 40.9% and 54.6% in the east, north and up directions, respectively. Comparing with IEKF, the position RMSE values of AIEKF are reduced by about 25.7%, 19.3% and 35.7% in the east, north and up directions, respectively. Compared with AEKF, the position RMSE values of AIEKF are reduced by about 21.6%, 15.5% and 30.7% in the east, north and up directions, respectively.
authors.affiliation: School of Instrument Science and Engineering, Southeast University, Nanjing 210096, China. chxiyuan@seu.edu.cn.
authors.forename: Xiyuan
authors.initials: X
authors.lastname: Chen
authors.affiliation: School of Instrument Science and Engineering, Southeast University, Nanjing 210096, China. wangxiying@outlook.com.
authors.forename: Xiying
authors.initials: X
authors.lastname: Wang
authors.affiliation: School of Automation and Electrical Engineering, University of Jinan, Jinan 250022, China. xy_abric@126.com.
authors.forename: Yuan
authors.initials: Y
authors.lastname: Xu