An improved localization method in cyber-social environments with obstacles

Abstract

In Cyber-Social Systems (CSS), sensors play a key role in the intelligent perception and recognition of people, objects and the environments, in which target localizing is one of the important issues. It is often difficult to accurately and conveniently localize the sensors due to the presence of Non-Line Of Sight (NLOS) when there are obstacles. This paper proposes a sensor localization method based on WiFi (Wireless Fidelity) localization, which first collects the angle and intensity information of the WiFi signals of mobile base stations during a linear or curvilinear motion, then uses the Nonlinear Inequality Constrained-Unscented Kalman Filter (NIC-UKF) method presented in this paper to filter interference, so as to localize the positions of sensors. The method has stronger stability, high precision, and acceptable computing overhead, which is suitable for the localization of fixed or low-speed moving targets in Cyber-Social environments with obstacles.