Indoor PDR performance enhancement using minimal map information and particle filters

For professional users such as firefighters and other first responders, GNSS positioning technology (GPS, assisted GPS) can satisfy outdoor positioning requirements in many instances. However, there is still a need for high-performance deep indoor positioning for use by these same professional users. This need has already been clearly expressed by various communities of end users in the context of WearIT@Work, an R&D project funded by the European Community's Sixth Framework Program. It is known that map matching can help for indoor pedestrian navigation. In most previous research, it was assumed that detailed building plans are available. However, in many emergency / rescue scenarios, only very limited building plan information may be at hand. For example a building outline might be obtained from aerial photographs or cataster databases. Alternatively, an escape plan posted at the entrances to many building would yield only approximate exit door and stairwell locations as well as hallway and room orientation. What is not known is how much map information is really required for a USAR mission and how much each level of map detail might help to improve positioning accuracy. Obviously, the geometry of the building and the course through will be factors consider. The purpose of this paper is to show how a previously published Backtracking Particle Filter (BPF) can be combined with different levels of building plan detail to improve PDR performance. A new in/out scenario that might be typical of a reconnaissance mission during a fire in a two-story office building was evaluated. Using only external wall information, the new scenario yields positioning performance (2.56 m mean 2D error) that is greatly superior to the PDR-only, no map base case (7.74 m mean 2D error). This result has a substantial practical significance since this level of building plan detail could be quickly and easily generated in many emergency instances. The technique could be used to mitigate heading errors that result from exposing the IMU to extreme operating conditions. It is hoped that this mitigating effect will also occur for more irregular paths and in larger traversed spaces such as parking garages and warehouses.