Improved GNSS velocity estimation using sensor fusion

Roman Morer; Shlomi Hacohen; Boaz Ben-Moshe; Nir Shvalb; Roi Yozevitch

doi:10.1109/ICSEE.2016.7806069

Improved GNSS velocity estimation using sensor fusion

Roman Morer, Shlomi Hacohen, Boaz Ben-Moshe, Nir Shvalb, Roi Yozevitch

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Scopus citations

Abstract

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.

Original language	English
Title of host publication	2016 IEEE International Conference on the Science of Electrical Engineering, ICSEE 2016
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781509021529
DOIs	https://doi.org/10.1109/ICSEE.2016.7806069
State	Published - 4 Jan 2017
Event	2016 IEEE International Conference on the Science of Electrical Engineering, ICSEE 2016 - Eilat, Israel Duration: 16 Nov 2016 → 18 Nov 2016

Publication series

Name	2016 IEEE International Conference on the Science of Electrical Engineering, ICSEE 2016

Conference

Conference	2016 IEEE International Conference on the Science of Electrical Engineering, ICSEE 2016
Country/Territory	Israel
City	Eilat
Period	16/11/16 → 18/11/16

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10.1109/ICSEE.2016.7806069

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Morer, R., Hacohen, S., Ben-Moshe, B., Shvalb, N., & Yozevitch, R. (2017). Improved GNSS velocity estimation using sensor fusion. In 2016 IEEE International Conference on the Science of Electrical Engineering, ICSEE 2016 Article 7806069 (2016 IEEE International Conference on the Science of Electrical Engineering, ICSEE 2016). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICSEE.2016.7806069

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title = "Improved GNSS velocity estimation using sensor fusion",

abstract = "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.",

author = "Roman Morer and Shlomi Hacohen and Boaz Ben-Moshe and Nir Shvalb and Roi Yozevitch",

note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 2016 IEEE International Conference on the Science of Electrical Engineering, ICSEE 2016 ; Conference date: 16-11-2016 Through 18-11-2016",

year = "2017",

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doi = "10.1109/ICSEE.2016.7806069",

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Morer, R, Hacohen, S, Ben-Moshe, B , Shvalb, N & Yozevitch, R 2017, Improved GNSS velocity estimation using sensor fusion. in 2016 IEEE International Conference on the Science of Electrical Engineering, ICSEE 2016., 7806069, 2016 IEEE International Conference on the Science of Electrical Engineering, ICSEE 2016, Institute of Electrical and Electronics Engineers Inc., 2016 IEEE International Conference on the Science of Electrical Engineering, ICSEE 2016, Eilat, Israel, 16/11/16. https://doi.org/10.1109/ICSEE.2016.7806069

Improved GNSS velocity estimation using sensor fusion. / Morer, Roman; Hacohen, Shlomi; Ben-Moshe, Boaz et al.
2016 IEEE International Conference on the Science of Electrical Engineering, ICSEE 2016. Institute of Electrical and Electronics Engineers Inc., 2017. 7806069 (2016 IEEE International Conference on the Science of Electrical Engineering, ICSEE 2016).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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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.

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Morer R, Hacohen S, Ben-Moshe B , Shvalb N , Yozevitch R. Improved GNSS velocity estimation using sensor fusion. In 2016 IEEE International Conference on the Science of Electrical Engineering, ICSEE 2016. Institute of Electrical and Electronics Engineers Inc. 2017. 7806069. (2016 IEEE International Conference on the Science of Electrical Engineering, ICSEE 2016). doi: 10.1109/ICSEE.2016.7806069

Improved GNSS velocity estimation using sensor fusion

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