Indoor/Outdoor Pedestrian Navigation with an Embedded GPS/RFID/Self-contained Sensor System

This paper describes an embedded pedestrian navigation system composed of a self-contained sensors, the Global Positioning System (GPS) and an active Radio Frequency Identification (RFID) tag system. We use self-contained sensors (accelerometers, gyrosensors and magnetometers) to estimate relative displacement by analyzing human walking locomotion. The GPS is used outdoors to adjust errors in position and direction accumulated by the dead-reckoning. In indoor environments, we use an active RFID tag system sparsely placed in key spot areas. The tag system obviously has limited availability and thus dead-reckoning is used to cover the environment. We propose a method of complementary compensation algorithm for the GPS/RFID localization and the selfcontained navigation represented by simple equations in a Kalman filter framework. Experimental results using the proposed method reveals that integration of GPS/RFID/dead-reckoning improve positioning accuracy in both indoor and outdoor environments. The pedestrian positioning is realized as a software module with the web-based APIs so that crossplatform development can easily be achieved. A pedestrian navigation system is implemented on an embedded wearable system and is proven to be useful even for unexperienced users.