Quantized RSS based wifi-indoor localization with room level accuracy

Abstract

The prevalent deployment of Wi-Fi infrastructure provides a potentially lowcost way to track Wi-Fi enabled devices in a building. Many indoor Location Based Systems (LBS) aim to get sub-meter precision for grid position estimation, however such accuracy is not necessary for some indoor locationaware applications, such as conference room identification and elder-care alert etc. Our system is designed to track the mobile user at room level granularity with high accuracy and reliability. In this paper, a probabilistic fingerprint approach is proposed based on quantized Received Signal Strength (RSS) measurements. In the training phase, a histogram based radio map is constructed for each room by..