Comparison of post-processing algorithms for indoor navigation trajectories

Real time indoor navigation has lately been a growing field. Some applications might not need a real time estimation of the trajectory, and a post processing framework provides a better estimation of this trajectory. Thus, the aim of this paper is to present and compare three different algorithms to improve a real time trajectory estimation. Two different smoothing algorithms and the Viterbi algorithm are then implemented and evaluated. These methods improve regularity by reducing switches between hypotheses.