Abstract
In the WiFi received signal strength indication (RSSI) based indoor positioning system, the mean value of RSSI obeys the independent normal distribution. In this paper, the multivariate normal model is researched with the collected RSSI data from multiple access points (APs). Euclidean distance and the variance of different RSSI vectors are used to evaluate the performance of the WiFi RSSI indoor positioning system. Based on the proposed equation, a RSSI mapping method is developed. Experimental results show that our RSSI mapping method can improve the positioning accuracy more than 30%.
| Translated title of the contribution | Multivariate Normal Model Based RSSI Mapping Method |
|---|---|
| Original language | Chinese (Traditional) |
| Pages (from-to) | 52-56 |
| Number of pages | 5 |
| Journal | Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology |
| Volume | 39 |
| State | Published - Oct 2019 |
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