Multi-Sensor Multi-Floor 3D Localization With Robust Floor Detection

Location has become an essential part of the next-generation Internet of Things systems. This paper proposes a multi-sensor-based 3D indoor localization approach. Compared with the existing 3D localization methods, this paper presents a wireless received signal strength (RSS)-profile-based floor-detection approach to enhance RSS-based floor detection. The profile-based floor detection is further integrated with the barometer data to gain more reliable estimations of the height and the barometer bias. Furthermore, the data from inertial sensors, magnetometers, and a barometer are integrated with the RSS data through an extend Kalman filter. The proposed multi-sensor integration algorithm provided more robust and smoother floor detection and 3D localization solutions than the existing methods.