TY - JOUR
T1 - Indoor Localization Method Based on Sequential Motion Tracking Using Topological Path Map
AU - Lee, Yu Cheol
AU - Myung, Hyun
N1 - Publisher Copyright:
© 2013 IEEE.
PY - 2019
Y1 - 2019
N2 - This paper proposes a novel indoor localization method based on sequential motion tracking (SMT) using a topological path map that can improve the shortcomings of traditional methods using range-only measurement sensors. The proposed method consists of map generation and location estimation. First, in the map preparation, we present the construction method of a radio fingerprint map and the topological path map. The radio fingerprint map contains radio signals moderated by a median filter, and the topological path map includes possible path motions in the form of nodes and edges using a floorplan drawing. Second, for location estimation, fingerprint analysis and SMT methods are developed. Fingerprint analysis finds the global region based on a histogram evaluation between the radio fingerprint map and online observations, which rely on Wi-Fi. The SMT determines the optimal position on the topological path map by considering the historical motion data and the fingerprint analysis result. Finally, the experimental results show that the proposed method is robust to the uncertainty of the fingerprint analysis using the range sensors and that it can accurately track global positions with efficient computations.
AB - This paper proposes a novel indoor localization method based on sequential motion tracking (SMT) using a topological path map that can improve the shortcomings of traditional methods using range-only measurement sensors. The proposed method consists of map generation and location estimation. First, in the map preparation, we present the construction method of a radio fingerprint map and the topological path map. The radio fingerprint map contains radio signals moderated by a median filter, and the topological path map includes possible path motions in the form of nodes and edges using a floorplan drawing. Second, for location estimation, fingerprint analysis and SMT methods are developed. Fingerprint analysis finds the global region based on a histogram evaluation between the radio fingerprint map and online observations, which rely on Wi-Fi. The SMT determines the optimal position on the topological path map by considering the historical motion data and the fingerprint analysis result. Finally, the experimental results show that the proposed method is robust to the uncertainty of the fingerprint analysis using the range sensors and that it can accurately track global positions with efficient computations.
KW - Fingerprint analysis
KW - indoor localization
KW - range measurement sensor
KW - sequential motion tracking
KW - topological path map
UR - http://www.scopus.com/inward/record.url?scp=85064753782&partnerID=8YFLogxK
U2 - 10.1109/ACCESS.2019.2909309
DO - 10.1109/ACCESS.2019.2909309
M3 - Article
AN - SCOPUS:85064753782
SN - 2169-3536
VL - 7
SP - 46187
EP - 46197
JO - IEEE Access
JF - IEEE Access
M1 - 6287639
ER -