An Improved Indoor Positioning Method Based on Affinity Propagation Clustering
Guochuan Deng, Sujuan Qin
Available Online September 2016.
- https://doi.org/10.2991/amitp-16.2016.57How to use a DOI?
- Fingerprinting; Indoor Localization; Affinity Propagation.
- The fingerprint-based wireless local area network (WLAN) positioning has gained significant interest in recent years. Indoor localization methods based on WLAN and RSS with advantage of low cost are most widely used. In this paper, we propose an improved indoor positioning method based on Affinity Propagation (AP) algorithm to obtain better accuracy: k coordinate points measured through KNN algorithm at the stage of orientation are clustered through Affinity Propagation (AP) algorithm into the largest cluster whose center node serves as the ultimate coordinate point. Experimental results conducted in the real environments show that our proposed algorithm can obtain improvement of the mean error distance of 18.68% and 34.72%, compared with the KNN method and traditional NN method, respectively.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Guochuan Deng AU - Sujuan Qin PY - 2016/09 DA - 2016/09 TI - An Improved Indoor Positioning Method Based on Affinity Propagation Clustering PB - Atlantis Press SP - 288 EP - 293 SN - 2352-538X UR - https://doi.org/10.2991/amitp-16.2016.57 DO - https://doi.org/10.2991/amitp-16.2016.57 ID - Deng2016/09 ER -