Name
Abstract | ||
|---|---|---|
For the problem that GNSS can't be used for positioning indoors and with the development of computing technology and the deployment widespread of Wi-Fi, Wi-Fi based indoor crowdsourced positioning methods have gradually become a hot spot for research and application. However, compared with professional fingerprint acquisition, crowdsourced data lacks accurate indoor labeled locations, which creates a serious positioning error if used to build the fingerprint database directly. Most of the current methods add too many constraints. To solve above issues, this paper proposes a method for the construction of crowdsourced location fingerprint map, which solves the error problem of data point dislocation caused by manifold dimensionality reduction while using only a small amount of labeled data which is some contain real physical coordinates data points. Using these data points as reference points and using some environmental elements constraining each data point to complete the build of the entire indoor environment. Practical experiment shows that the error of the proposed method can be reduced to 6m. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1109/IPIN54987.2022.9918145 | 2022 IEEE 12th International Conference on Indoor Positioning and Indoor Navigation (IPIN) |
Keywords | DocType | ISSN |
Crowdsourced data,Wi-Fi,Fingerprint Positioning,Manifold Learning,Map Constraints,Radio Map Construction | Conference | 2162-7347 |
ISBN | Citations | PageRank |
978-1-7281-6219-5 | 0 | 0.34 |
References | Authors | |
4 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhengyi Li | 1 | 0 | 0.34 |
| Wen Li | 2 | 0 | 0.34 |
| Dongyan Wei | 3 | 0 | 0.68 |
| Hong Yuan | 4 | 0 | 0.34 |
| Bingbing Xu | 5 | 0 | 0.34 |
| Huawei Shen | 6 | 739 | 61.40 |