TY - GEN
T1 - Running pace estimation using complementary filter based fusion of GPS and pedometer data
AU - Skrzypczyk, Krzysztof
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/9/19
Y1 - 2017/9/19
N2 - This paper presents an application of complementary filtration for estimating running pace using GPS and pedometer data. In the approach presented two information sources are fused with dynamically adjusted importance factors. In the case of poor GPS signal the pedometer data are gained by the filter, and otherwise. The method proposed was verified using multiple simulations. An exemplary one is presented and discussed in the paper.
AB - This paper presents an application of complementary filtration for estimating running pace using GPS and pedometer data. In the approach presented two information sources are fused with dynamically adjusted importance factors. In the case of poor GPS signal the pedometer data are gained by the filter, and otherwise. The method proposed was verified using multiple simulations. An exemplary one is presented and discussed in the paper.
UR - https://www.scopus.com/pages/publications/85035352314
U2 - 10.1109/MMAR.2017.8046828
DO - 10.1109/MMAR.2017.8046828
M3 - Conference contribution
AN - SCOPUS:85035352314
T3 - 2017 22nd International Conference on Methods and Models in Automation and Robotics, MMAR 2017
SP - 222
EP - 225
BT - 2017 22nd International Conference on Methods and Models in Automation and Robotics, MMAR 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 22nd International Conference on Methods and Models in Automation and Robotics, MMAR 2017
Y2 - 28 August 2017 through 31 August 2017
ER -