TY - GEN
T1 - Improved GNSS velocity estimation using sensor fusion
AU - Morer, Roman
AU - Hacohen, Shlomi
AU - Ben-Moshe, Boaz
AU - Shvalb, Nir
AU - Yozevitch, Roi
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2017/1/4
Y1 - 2017/1/4
N2 - This work presents a generic method for improving the velocity estimation of GNSS devices. The suggested algorithm is based on the famous Kalman Filter which utilizes both GNSS and IMU measurements. The suggested sensor-fusion method contains a built-in classifier for identifying measurements with low confidence. The algorithm was implemented and tested using both simulation and real-world data. The results show significant improvement in the velocity estimation. This improvement can be used for further positioning accuracy improvement of a wide range of COTS GNSS devices.
AB - This work presents a generic method for improving the velocity estimation of GNSS devices. The suggested algorithm is based on the famous Kalman Filter which utilizes both GNSS and IMU measurements. The suggested sensor-fusion method contains a built-in classifier for identifying measurements with low confidence. The algorithm was implemented and tested using both simulation and real-world data. The results show significant improvement in the velocity estimation. This improvement can be used for further positioning accuracy improvement of a wide range of COTS GNSS devices.
UR - https://www.scopus.com/pages/publications/85014222690
U2 - 10.1109/ICSEE.2016.7806069
DO - 10.1109/ICSEE.2016.7806069
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AN - SCOPUS:85014222690
T3 - 2016 IEEE International Conference on the Science of Electrical Engineering, ICSEE 2016
BT - 2016 IEEE International Conference on the Science of Electrical Engineering, ICSEE 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2016 IEEE International Conference on the Science of Electrical Engineering, ICSEE 2016
Y2 - 16 November 2016 through 18 November 2016
ER -