Minimum dispersion coefficient criteria based positioning algorithm for BDS

作     者：Wang, Lina Li, Linlin 

作者机构：Univ Sci & Technol Beijing Sch Comp & Commun Engn Beijing 100083 Peoples R China 

出 版 物：《ARCHIVES OF ELECTRICAL ENGINEERING》 (Arch. Electr. Eng.)

年 卷 期：2018年第67卷第4期

页      面：739-753页

核心收录：

学科分类：0808[工学-电气工程] 08[工学] 

基　　金：National Natural Science Foundation of China University of Science and Technology Beijing Project Fundamental Research Funds for the Central Universities [FRF-BD-17-015A] Foundation of Beijing Engineering and Technology Center for Convergence Networks and Ubiquitous Services Beijing Key Laboratory of Knowledge Engineering for Materials Science 

主　　题：alpha-stable distribution BeiDou satellites Kalman filter minimum dispersion coefficient criteria non-Gaussian noise positioning algorithm 

摘      要：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 MS, 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.