9th International Conference on Communications and Networking in China

Research Article

A High-Precision Collaboration Positioning Algorithm with Indoor Environment

  • @INPROCEEDINGS{10.4108/icst.chinacom.2014.256552,
        author={Jun-Hui Zhao and Xiaocen Jin and Yi Gong},
        title={A High-Precision Collaboration Positioning Algorithm with Indoor Environment},
        proceedings={9th International Conference on Communications and Networking in China},
        publisher={IEEE},
        proceedings_a={CHINACOM},
        year={2015},
        month={1},
        keywords={cellular networks; pseudolites; multiple positioning circles; multiple linear regression},
        doi={10.4108/icst.chinacom.2014.256552}
    }
    
  • Jun-Hui Zhao
    Xiaocen Jin
    Yi Gong
    Year: 2015
    A High-Precision Collaboration Positioning Algorithm with Indoor Environment
    CHINACOM
    IEEE
    DOI: 10.4108/icst.chinacom.2014.256552
Jun-Hui Zhao1,*, Xiaocen Jin1, Yi Gong2
  • 1: Beijing Jiaotong University
  • 2: South University of Science and Technology of China
*Contact email: junhuizhao@bjtu.edu.cn

Abstract

In this paper, the actual indoor environment the effects of reflection, diffraction, partition loss and other interference factors between the mobile station (MT) and a base station (BS), aiming at actual indoor environment is researched. The algorithm proposed here consists of real-time environment parameter measure, pseudolite positioning technology and cooperative multiple positioning circles algorithm. In view of the problems, such as the interference between mobile nodes and fixed BSs, multiple linear regression is applied to measure the environment parameter in real-time to ensure the follow-up positioning accuracy. Against the problem that traditional pseudolite positioning technology may introduce near and far field effect, multipath or other issues when the distance between the users is too close. a new location algorithm with collaboration of multiple positioning circles based on pseudolite is proposed in this paper. Simulation result shows that the new algorithm can effectively improve the positioning accuracy of the indoor environment.