A joint indoor positioning scheme exploiting pedestrian dead reckoning and radio frequency tomography

The pedestrian dead reckoning (PDR) is a popular technique for recognizing a pedestrian’s trajectory. However, its inherent disadvantage of susceptibility to error accumulation limits its performance as the travelled distance is increased. Various techniques are combined with PDR to mitigate the error accumulation by regular position resetting. The radio frequency (RF) Tomography is an emerging technology for localization by sensing the received signal strength (RSS) fluctuation on a line-of-sight wireless link (LOSL). Conventional RF Tomography based schemes need specific large-scale networks and face with the problem of harsh environments and high hardware costs. Thus in this paper, we proposed the flexible and practical GF operators for PDR resetting work, in which we introduce the displacement estimation by PDR technique and the LOSL triggering sequence to build a PDR geometrical formulation (PDR-GF) model, and then this model is optimized by Particle Swarm Optimization (PSO) algorithm for crossing point (CP) estimation on the LOSLs. Finally, the estimated CP is in turn used for regular position resetting. Practical experiments are performed to evaluate the proposed positioning scheme. According to the results, the proposed scheme can achieve a finer accuracy of less than 1 m, outperforming the existing RSS-PDR positioning scheme.