Research Article
Data Process for Indoor Positioning based on WiFi Fingerprint
@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
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.
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