Indoor Localization Methods Using Dead Reckoning and 3D Map Matching
In order to navigate or localize in 3D space such as parking garages, we would need height information in addition to 2D position. Conventionally, an altimeter is used to get the floor level/height information. We propose a novel method for three-dimensional navigation and localization of a land vehicle in a multi-storey parking-garage. The solution presented in this paper uses low cost gyro and odometer sensors, combined with a 3D map by means of particle filtering and collision detection techniques to localize the vehicle in a parking garage. This eliminates the necessity of an altimeter or other additional aiding sources such as radio signalling. Altimeters have inherent dynamic influential factors such as temperature and environmental pressure affecting the altitude readings, and for radio signals we need extra infrastructure requirements. The proposed solution can be used without any such additional infrastructure devices. Other sources of information, such as WLAN signals, can be used to complement the solution if and when available. In addition we extend this proposed method to novel concept of non-stationary 3D maps, as moving maps, within which localization of a track-able object is required. We also introduce novel techniques that enable seamless navigation solution from vehicular dead reckoning (VDR) to pedestrian dead reckoning (PDR) and vice versa to reduce user involvement. For achieving this we collect relevant measurements such as vehicle ignition status and accelerometer signal variance, and user pattern recognition to select appropriate dead reckoning method.
dead reckoning 3d map matching land vehicles particle filters sensor fusion indoor environments