TY - GEN
T1 - Model fusion for inertial-based personal dead reckoning systems
AU - Meina, Michal
AU - Krasuski, Adam
AU - Rykaczewski, Krzysztof
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/6/24
Y1 - 2015/6/24
N2 - This paper introduces a model fusion approach that improves the effectiveness of Personal Dead Reckoning Systems that exploits foot-mounted Inertial Measurement Units. Our solution estimates a sensor orientation by exploiting the Madgwick's algorithm integrated with popular Kalman-based solution. This way, attitude and heading correction is not based on the Zero-Velocity phase assumption which introduces significant error. The experiments conducted on ground-truth data shows, that the proposed approach outperforms state-of-the-art solution by reducing systematic and modelling errors and also provides better heading estimation.
AB - This paper introduces a model fusion approach that improves the effectiveness of Personal Dead Reckoning Systems that exploits foot-mounted Inertial Measurement Units. Our solution estimates a sensor orientation by exploiting the Madgwick's algorithm integrated with popular Kalman-based solution. This way, attitude and heading correction is not based on the Zero-Velocity phase assumption which introduces significant error. The experiments conducted on ground-truth data shows, that the proposed approach outperforms state-of-the-art solution by reducing systematic and modelling errors and also provides better heading estimation.
UR - http://www.scopus.com/inward/record.url?scp=84939431565&partnerID=8YFLogxK
U2 - 10.1109/SAS.2015.7133658
DO - 10.1109/SAS.2015.7133658
M3 - Conference contribution
AN - SCOPUS:84939431565
T3 - SAS 2015 - 2015 IEEE Sensors Applications Symposium, Proceedings
BT - SAS 2015 - 2015 IEEE Sensors Applications Symposium, Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 10th IEEE Sensors Applications Symposium, SAS 2015
Y2 - 13 April 2015 through 15 April 2015
ER -