New insights into wifi-based device-free localization

Abstract

WiFi-based device-free localization is a main indoor localization technique that has attracted much attention recently. Typically, due to the complex wireless propagation in indoor environments, WiFi-based device-free localization requires a construction of a fingerprint map that captures the signal strength characteristics when the human is standing at certain locations in the area of interest. This fingerprint requires significant overhead in construction, and thus has been one of the major drawbacks of WiFi-based device-free localization. In this paper, we leverage an automated tool for fingerprint constructions to study novel scenarios for WiFi-based device-free localization training and testing that are difficult to evaluate in a real environment. In particular, we examine the effect of changing the access points (AP) mounting location, AP technology upgrade, and outsider effect; on the accuracy of the localization system. Our analysis provides recommendations for better localization and provides insights for both researchers and practitioners.