TY - JOUR N2 - The BeiDou navigation satellite system (BDS) is one of the four global navigation satellite systems. More attention has been paid to the positioning algorithm of the BDS. Based on the study on the Kalman filter (KF) algorithm, this paper proposed a novel algorithm for the BDS, named as the minimum dispersion coefficient criteria Kalman filter (MDCCKF) positioning algorithm. The MDCCKF algorithm adopts minimum dispersion coefficient criteria (MDCC) to remove the influence of noise with an alpha-stable distribution (ASD) model which can describe non-Gaussian noise effectively, especially for the pulse noise in positioning. By minimizing the dispersion coefficient of the positioning error, the MDCCKF assures positioning accuracy under both Gaussian and non-Gaussian environment. Compared with the original KF algorithm, it is shown that the MDCCKF algorithm has higher positioning accuracy and robustness. The MDCCKF algorithm provides insightful results for potential future research. L1 - http://czasopisma.pan.pl/Content/108837/PDF/art03.pdf L2 - http://czasopisma.pan.pl/Content/108837 PY - 2018 IS - No 4 EP - 739–753 DO - 10.24425/aee.2018.124737 KW - alpha-stable distribution KW - BeiDou satellites KW - Kalman filter KW - minimum dispersion coefficient criteria KW - non-Gaussian noise KW - positioning algorithm A1 - Wang, Lina A1 - Li, LinLin PB - Polish Academy of Sciences VL - vol. 67 DA - 2018.11.19 T1 - Minimum dispersion coefficient criteria based positioning algorithm for BDS SP - 739–753 UR - http://czasopisma.pan.pl/dlibra/publication/edition/108837 T2 - Archives of Electrical Engineering ER -