@inproceedings{1c0c8599b8e143f080dd4c986b4c2ff5,
title = "Indoor localization with asymmetric grid-based filters in large areas utilizing smartphones",
abstract = "Location information is playing a significant role in nowadays mobile applications. Performing indoor localization with existing WiFi infrastructure and smartphone motion sensor through statistical filtering has been proven to be a feasible solution. Many literature have resorted to particle filters to deal with the multi-modal and non-Gaussian problem associated with the filtering process. Although grid-based filters can approximate the true densities better compared with particle filters, their computational cost is extremely expensive, especially for large areas. In this paper, we develop a novel asymmetric grid-based filter to accommodate both high-resolution requirement and computational cost-efficiency. The evaluation over an indoor area of 3750m2 has shown that our proposed method can achieve a median error of only 2.72m, which is 0.17m more accurate with only 24\% of the computation cost compared to particle filters.",
author = "Tong Guan and Le Fang and Wen Dong and Yunfei Hou and Chunming Qiao",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 2017 IEEE International Conference on Communications, ICC 2017 ; Conference date: 21-05-2017 Through 25-05-2017",
year = "2017",
month = jul,
day = "28",
doi = "10.1109/ICC.2017.7997094",
language = "English",
series = "IEEE International Conference on Communications",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
editor = "Merouane Debbah and David Gesbert and Abdelhamid Mellouk",
booktitle = "2017 IEEE International Conference on Communications, ICC 2017",
address = "United States",
}