TY - GEN
T1 - FM-based indoor localization
AU - Chen, Yin
AU - Lymberopoulos, Dimitrios
AU - Liu, Jie
AU - Priyantha, Bodhi
PY - 2012/6/25
Y1 - 2012/6/25
N2 - The major challenge for accurate fingerprint-based indoor localization is the design of robust and discriminative wireless signatures. Even though WiFi RSSI signatures are widely available indoors, they vary significantly over time and are susceptible to human presence, multipath, and fading due to the high operating frequency. To overcome these limitations, we propose to use FM broadcast radio signals for robust indoor fingerprinting. Because of the lower frequency, FM signals are less susceptible to human presence, multipath and fading, they exhibit exceptional indoor penetration, and according to our experimental study they vary less over time when compared to WiFi signals. In this work, we demonstrate through a detailed experimental study in 3 different buildings across the US, that FM radio signal RSSI values can be used to achieve room-level indoor localization with similar or better accuracy to the one achieved by WiFi signals. Furthermore, we propose to use additional signal quality indicators at the physical layer (i.e., SNR, multipath etc.) to augment the wireless signature, and show that localization accuracy can be further improved by more than 5%. More importantly, we experimentally demonstrate that the localization errors of FM andWiFi signals are independent. When FM and WiFi signals are combined to generate wireless fingerprints, the localization accuracy increases as much as 83% (when accounting for wireless signal temporal variations) compared to when WiFi RSSI only is used as a signature.
AB - The major challenge for accurate fingerprint-based indoor localization is the design of robust and discriminative wireless signatures. Even though WiFi RSSI signatures are widely available indoors, they vary significantly over time and are susceptible to human presence, multipath, and fading due to the high operating frequency. To overcome these limitations, we propose to use FM broadcast radio signals for robust indoor fingerprinting. Because of the lower frequency, FM signals are less susceptible to human presence, multipath and fading, they exhibit exceptional indoor penetration, and according to our experimental study they vary less over time when compared to WiFi signals. In this work, we demonstrate through a detailed experimental study in 3 different buildings across the US, that FM radio signal RSSI values can be used to achieve room-level indoor localization with similar or better accuracy to the one achieved by WiFi signals. Furthermore, we propose to use additional signal quality indicators at the physical layer (i.e., SNR, multipath etc.) to augment the wireless signature, and show that localization accuracy can be further improved by more than 5%. More importantly, we experimentally demonstrate that the localization errors of FM andWiFi signals are independent. When FM and WiFi signals are combined to generate wireless fingerprints, the localization accuracy increases as much as 83% (when accounting for wireless signal temporal variations) compared to when WiFi RSSI only is used as a signature.
KW - fingerprinting
KW - fm
KW - localization
KW - mobile systems
KW - wireless
UR - https://www.scopus.com/pages/publications/84864357153
U2 - 10.1145/2307636.2307653
DO - 10.1145/2307636.2307653
M3 - 会议稿件
AN - SCOPUS:84864357153
SN - 9781450313018
T3 - MobiSys'12 - Proceedings of the 10th International Conference on Mobile Systems, Applications, and Services
SP - 169
EP - 181
BT - MobiSys'12 - Proceedings of the 10th International Conference on Mobile Systems, Applications, and Services
PB - Association for Computing Machinery
T2 - 10th International Conference on Mobile Systems, Applications, and Services, MobiSys 2012
Y2 - 25 June 2012 through 29 June 2012
ER -