In recent years pedestrian dead reckoning (PDR) has been a popular indoor localization technique that takes advantage of inertial navigation sensors (INS) of smartphones due to its availability. This paper proposes a model that utilizes empirical mode decomposition (EMD) as the noise filter. EMD is an unconventional filter being applied in PDR to remove noise by processing the raw signal before implementing step counts, step lengths and heading estimation. The experiment made using the proposed model was able to perform the standard PDR technique without overlaps in heading estimation.The aim of this paper is to evaluate the performance of EMD with PDR and it achieved it with slight error in distance of about 4 meters. In the two tests conducted, the total steps taken were about 151 while the estimated steps were 153, resulting to a 98.7% accuracy. The estimated trajectory was also very similar with the actual trajectory made.EMD was evaluated in two occasions but still requires more experimentation on the effectiveness of EMD and present more advances on the study of applying EMD in pedestrian dead reckoning.
Volume 11 | 07-Special Issue
Pages: 1790-1794