A Novel Clustering Algorithm for Wi-Fi Indoor Positioning

• Published in: IEEE access Vol. 7; p. 1
• Main Authors: Ren, Jin, Wang, Yunan, Niu, Changliu, Song, Wei, Huang, Songyang
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.01.2019; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Accuracy; Algorithms; Classification algorithms; Cluster analysis; Clustering; Clustering algorithms; Euclidean distance; Fingerprint recognition; Fingerprints; Improved public c-means (IPC) clustering algorithm; Indoor environments; Indoor positioning; K-nearest neighbors algorithm; Received signal strength indicator; Signal strength; the k-nearest neighbors (KNN) algorithm; The knearest neighbors (KNN) algorithm; Vector quantization; Wi-Fi; Wireless fidelity

In recent years, the Wi-Fi-based indoor positioning technology has become a research hotspot. This technology mainly locates the indoor Wi-Fi based on the received signal strength indicator (RSSI) signals. The most popular Wi-Fi positioning algorithm is the k-nearest neighbors (KNN) algorithm. Due t...