Adaptive Temporal Radio Maps for Indoor Location Estimation

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FILA: Fine-grained indoor localization (2012, background): “However, most existing WLAN-based localization approaches either requires long time in the offline training phase (fingerprint-based) [10], or time-consuming in the online phase to obtain an stable metric: RSSI (modelbased).”
Indoor Localization System using RSSI Measurement of Wireless Sensor Network based on ZigBee Standard (2006, unknown): “Keywords performance evaluation, localization, RSSI, ZigBee”
Adaptive Localization in a Dynamic WiFi Environment through Multi-view Learning (2007, methodology): “To reduce the need of the additional equipments, ( Yin, Yang, & Ni 2005 ) apply a model tree based method, called LEMT, to adapt RSS maps by only using a few reference points, which are additional sensors for recording RSS values over time.”
Wi-Fi Fingerprint-Based Indoor Positioning: Recent Advances and Comparisons (2016, background): “Typical algorithms include Gaussian process [142] and decision tree [145], [146], which are based on existing statistical learning techniques [147], [148].”
VIRE: Active RFID-based Localization Using Virtual Reference Elimination (2007, background): “The tracking object is able to receive RSSI information from nearby transmitters (e.g., 802.11x access points) and compute its current position [4] [5].”