Infrastructure-free Collaborative Indoor Positioning Scheme for Time-critical Team Operations

Abstract

Indoor localization is the key infrastructure for indoor location-aware applications. In this paper, we consider an emergency scenario, where a team of soldiers or first responders perform time-critical missions in a large and complex building. In particular, we consider the case where infrastructure-based localization is not feasible for various reasons such as installation/management costs, a power outage, and terrorist attacks. We design a novel algorithm called the collaborative indoor positioning scheme (CLIPS), which does not require any pre-existing indoor infrastructure. Given that users are equipped with a signal strength map for the intended area for reference, CLIPS uses this map to compare and extract a set of feasible positions from all positions on the map when the device measures signal strength values at run time. Dead reckoning is then performed to remove invalid candidate coordinates, eventually leading to only correct positions. The main departure from existing peer-assisted localization algorithms is that our approach does not require any infrastructure or manual configuration. We perform testbed experiments and extensive simulations, and our results verify that our proposed scheme converges to an accurate set of positions much faster than existing noncollaborative solutions.