A hidden semi-Markov model for indoor radio source localization using received signal strength
Shuai Sun, Xuezhi Wang, Bill Moran, Wayne ST Rowe
Signal Processing | Elsevier | Published : 2020
Multipath propagation makes the use of received signal strength (RSS) unreliable as a signal propagation model for localization of a radio source based on RSS data. An approach to mitigation of this problem is the use of a Hidden Markov model (HMM) to represent the relationship between RSS and the radio source location by incorporating an environment prior and RSS source dynamics. The HMM structure forces a geometric form for the distribution for the sojourn time. This, combined with missing data problems, reduces confidence in location estimation. It is found, in this paper, that Hidden semi-Markov Models (HsMMs), with a more flexible sojourn time distribution are more able to represent sou..View full abstract
Awarded by Australia Research Council Linkage project
This work is partially supported by Australia Research Council Linkage project grant LP150100065.