Measurement fusion of connectivity and received signal strength for indoor localization and tracking

The range-free localization suffers from unstable connectivity information between wireless devices. To overcome this, we propose a Markov Chain Monte Carlo particle filter (MCMC PF)-based mobility tracking algorithm assisted by received signal strength (RSS) information. The range-free localization results and RSS measurements are used in the tracking algorithm. From MATLAB simulation, we confirm the performance of the proposed tracking algorithm compensating the defect of the range-free localization, and the efficient indoor mobility tracking in a realistic indoor environment has been demonstrated.