Seamless pedestrian navigation augmented by walk status detection and context features
An Inertial Navigation System (INS) is self contained, immune to jamming/interference and in many other ways is ideally for pedestrian navigation applications especially in indoor environments. However, due to the sensor properties the quality of the navigation solution from a stand alone INS will degrade rapidly, and must rely on some form of external correction/calibration/aiding to ensure system stability and reliability. In this contribution the authors use GPS when outdoors and WiFi when indoors to aid the INS in order to support seamless pedestrian navigation. Firstly, constraints based on walk status detection are applied to reduce the INS divergence. That are, position update by step detection and heading constraint based on turn detection. Then, to improve the performance of WiFi positioning, a new fingerprinting database augmented by two types of map based information is used. One is the topological relationship linking corridors, and the other is the orientation information of different corridors. Test results confirm that with this constraints the navigation accuracy and stability are improved.
2016 Fourth International Conference on Ubiquitous Positioning, Indoor Navigation and Location Based Services (UPINLBS)