Smartphone-Based Indoor Localization System Using Inertial Sensor and Acoustic Transmitter/Receiver

This paper presents a novel smartphone-based indoor localization system that integrates an infrastructure-based acoustic localization system with inertial sensor-based dead reckoning. A fuzzy inference system is developed to achieve a short-term high accuracy tracking by using inertial sensors. The acoustic positioning and the inertial sensor-based dead reckoning are then fused by a Kalman filter with a carefully designed decision making algorithm. Hence, long-term stable and precise indoor localization, which is also robust against short-term measurement noise of the acoustic system, can be achieved. The experimental results show that the proposed system is able to accurately follow the true trajectory meanwhile to maintain the robustness and stability even if the position data of acoustic localization system are missing or erroneous.