Onboard and External Magnetic Bias Estimation for UAS through CDGNSS/Visual Cooperative Navigation
This paper describes a calibration technique aimed at combined estimation of onboard and external magnetic disturbances for small Unmanned Aerial Systems (UAS). In particular, the objective is to estimate the onboard horizontal bias components and the external magnetic declination, thus improving he...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-05-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/21/11/3582 |
| _version_ | 1827691841195081728 |
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| author | Federica Vitiello Flavia Causa Roberto Opromolla Giancarmine Fasano |
| author_facet | Federica Vitiello Flavia Causa Roberto Opromolla Giancarmine Fasano |
| author_sort | Federica Vitiello |
| collection | DOAJ |
| description | This paper describes a calibration technique aimed at combined estimation of onboard and external magnetic disturbances for small Unmanned Aerial Systems (UAS). In particular, the objective is to estimate the onboard horizontal bias components and the external magnetic declination, thus improving heading estimation accuracy. This result is important to support flight autonomy, even in environments characterized by significant magnetic disturbances. Moreover, in general, more accurate attitude estimates provide benefits for georeferencing and mapping applications. The approach exploits cooperation with one or more “deputy” UAVs and combines drone-to-drone carrier phase differential GNSS and visual measurements to attain magnetic-independent attitude information. Specifically, visual and GNSS information is acquired at different heading angles, and bias estimation is modelled as a non-linear least squares problem solved by means of the Levenberg–Marquardt method. An analytical error budget is derived to predict the achievable accuracy. The method is then demonstrated in flight using two customized quadrotors. A pointing analysis based on ground and airborne control points demonstrates that the calibrated heading estimate allows obtaining an angular error below 1°, thus resulting in a substantial improvement against the use of either the non-calibrated magnetic heading or the multi-sensor-based solution of the DJI onboard navigation filter, which determine angular errors of the order of several degrees. |
| first_indexed | 2024-03-10T11:11:11Z |
| format | Article |
| id | doaj.art-509ef5070dec46eead5334b2a0deeaf8 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T11:11:11Z |
| publishDate | 2021-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-509ef5070dec46eead5334b2a0deeaf82023-11-21T20:48:07ZengMDPI AGSensors1424-82202021-05-012111358210.3390/s21113582Onboard and External Magnetic Bias Estimation for UAS through CDGNSS/Visual Cooperative NavigationFederica Vitiello0Flavia Causa1Roberto Opromolla2Giancarmine Fasano3Department of Industrial Engineering, University of Naples “Federico II”, P.le Tecchio 80, 80125 Naples, ItalyDepartment of Industrial Engineering, University of Naples “Federico II”, P.le Tecchio 80, 80125 Naples, ItalyDepartment of Industrial Engineering, University of Naples “Federico II”, P.le Tecchio 80, 80125 Naples, ItalyDepartment of Industrial Engineering, University of Naples “Federico II”, P.le Tecchio 80, 80125 Naples, ItalyThis paper describes a calibration technique aimed at combined estimation of onboard and external magnetic disturbances for small Unmanned Aerial Systems (UAS). In particular, the objective is to estimate the onboard horizontal bias components and the external magnetic declination, thus improving heading estimation accuracy. This result is important to support flight autonomy, even in environments characterized by significant magnetic disturbances. Moreover, in general, more accurate attitude estimates provide benefits for georeferencing and mapping applications. The approach exploits cooperation with one or more “deputy” UAVs and combines drone-to-drone carrier phase differential GNSS and visual measurements to attain magnetic-independent attitude information. Specifically, visual and GNSS information is acquired at different heading angles, and bias estimation is modelled as a non-linear least squares problem solved by means of the Levenberg–Marquardt method. An analytical error budget is derived to predict the achievable accuracy. The method is then demonstrated in flight using two customized quadrotors. A pointing analysis based on ground and airborne control points demonstrates that the calibrated heading estimate allows obtaining an angular error below 1°, thus resulting in a substantial improvement against the use of either the non-calibrated magnetic heading or the multi-sensor-based solution of the DJI onboard navigation filter, which determine angular errors of the order of several degrees.https://www.mdpi.com/1424-8220/21/11/3582multi-UAV cooperationcalibrationmagnetic biasesmagnetic declinationLevenberg–Marquardterror budget analysis |
| spellingShingle | Federica Vitiello Flavia Causa Roberto Opromolla Giancarmine Fasano Onboard and External Magnetic Bias Estimation for UAS through CDGNSS/Visual Cooperative Navigation Sensors multi-UAV cooperation calibration magnetic biases magnetic declination Levenberg–Marquardt error budget analysis |
| title | Onboard and External Magnetic Bias Estimation for UAS through CDGNSS/Visual Cooperative Navigation |
| title_full | Onboard and External Magnetic Bias Estimation for UAS through CDGNSS/Visual Cooperative Navigation |
| title_fullStr | Onboard and External Magnetic Bias Estimation for UAS through CDGNSS/Visual Cooperative Navigation |
| title_full_unstemmed | Onboard and External Magnetic Bias Estimation for UAS through CDGNSS/Visual Cooperative Navigation |
| title_short | Onboard and External Magnetic Bias Estimation for UAS through CDGNSS/Visual Cooperative Navigation |
| title_sort | onboard and external magnetic bias estimation for uas through cdgnss visual cooperative navigation |
| topic | multi-UAV cooperation calibration magnetic biases magnetic declination Levenberg–Marquardt error budget analysis |
| url | https://www.mdpi.com/1424-8220/21/11/3582 |
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