12th EAI International Conference on Mobile Multimedia Communications, Mobimedia 2019, 29th - 30th Jun 2019, Weihai, China

Research Article

Data Process for Indoor Positioning based on WiFi Fingerprint

Download286 downloads
  • @INPROCEEDINGS{10.4108/eai.29-6-2019.2282793,
        author={Xuerong  Cui and Mengyan  Wang and Juan  Li and Meiqi  Ji and Jianhang  Liu and Tingpei  Huang and Haihua  Chen},
        title={Data Process for Indoor Positioning based on WiFi Fingerprint},
        proceedings={12th EAI International Conference on Mobile Multimedia Communications, Mobimedia 2019, 29th - 30th Jun 2019, Weihai, China},
        publisher={EAI},
        proceedings_a={MOBIMEDIA},
        year={2019},
        month={6},
        keywords={normal distribution kalman filter received signal strength indication fingerprint database},
        doi={10.4108/eai.29-6-2019.2282793}
    }
    
  • Xuerong Cui
    Mengyan Wang
    Juan Li
    Meiqi Ji
    Jianhang Liu
    Tingpei Huang
    Haihua Chen
    Year: 2019
    Data Process for Indoor Positioning based on WiFi Fingerprint
    MOBIMEDIA
    EAI
    DOI: 10.4108/eai.29-6-2019.2282793
Xuerong Cui,*, Mengyan Wang1, Juan Li1, Meiqi Ji1, Jianhang Liu1, Tingpei Huang1, Haihua Chen1
  • 1: Department of Computer and Communication Engineering, China University of Petroleum (East China)
*Contact email: cxr@upc.edu.cn

Abstract

Currently, most of the existing location fingerprint indoor positioning algorithms are based on the original fingerprint database. The accuracy of the fingerprint database will directly affect the final positioning accuracy. A method based on skewness-kurtosis normality test and Kalman filter fusion is proposed in this paper. Experiments shows that the fusion algorithm can effectively remove the abrupt data and noise fluctuations for the RSSI (Received Signal Strength Indication) data, and achieve accurate and smooth output of the RSSI value.