Magnetometer Calibration for Small Unmanned Aerial Vehicles Using Cooperative Flight Data
This paper presents a new method to improve the accuracy in the heading angle estimate provided by low-cost magnetometers on board of small Unmanned Aerial Vehicles (UAVs). This task can be achieved by estimating the systematic error produced by the magnetic fields generated by onboard electric equi...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-01-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/20/2/538 |
| _version_ | 1811263226886750208 |
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| author | Roberto Opromolla |
| author_facet | Roberto Opromolla |
| author_sort | Roberto Opromolla |
| collection | DOAJ |
| description | This paper presents a new method to improve the accuracy in the heading angle estimate provided by low-cost magnetometers on board of small Unmanned Aerial Vehicles (UAVs). This task can be achieved by estimating the systematic error produced by the magnetic fields generated by onboard electric equipment. To this aim, calibration data must be collected in flight when, for instance, the level of thrust provided by the electric engines (and, consequently, the associated magnetic disturbance) is the same as the one occurring during nominal flight operations. The UAV whose magnetometers need to be calibrated (chief) must be able to detect and track a cooperative vehicle (deputy) using a visual camera, while flying under nominal GNSS coverage to enable relative positioning. The magnetic biases’ determination problem can be formulated as a system of non-linear equations by exploiting the acquired visual and GNSS data. The calibration can be carried out either off-line, using the data collected in flight (as done in this paper), or directly on board, i.e., in real time. Clearly, in the latter case, the two UAVs should rely on a communication link to exchange navigation data. Performance assessment is carried out by conducting multiple experimental flight tests. |
| first_indexed | 2024-04-12T19:42:19Z |
| format | Article |
| id | doaj.art-6d8516f6b1594539b5bdd93b26f7f9ef |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-12T19:42:19Z |
| publishDate | 2020-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-6d8516f6b1594539b5bdd93b26f7f9ef2022-12-22T03:19:04ZengMDPI AGSensors1424-82202020-01-0120253810.3390/s20020538s20020538Magnetometer Calibration for Small Unmanned Aerial Vehicles Using Cooperative Flight DataRoberto Opromolla0Department of Industrial Engineering, University of Naples Federico II, Piazzale Tecchio 80, 80125 Naples, ItalyThis paper presents a new method to improve the accuracy in the heading angle estimate provided by low-cost magnetometers on board of small Unmanned Aerial Vehicles (UAVs). This task can be achieved by estimating the systematic error produced by the magnetic fields generated by onboard electric equipment. To this aim, calibration data must be collected in flight when, for instance, the level of thrust provided by the electric engines (and, consequently, the associated magnetic disturbance) is the same as the one occurring during nominal flight operations. The UAV whose magnetometers need to be calibrated (chief) must be able to detect and track a cooperative vehicle (deputy) using a visual camera, while flying under nominal GNSS coverage to enable relative positioning. The magnetic biases’ determination problem can be formulated as a system of non-linear equations by exploiting the acquired visual and GNSS data. The calibration can be carried out either off-line, using the data collected in flight (as done in this paper), or directly on board, i.e., in real time. Clearly, in the latter case, the two UAVs should rely on a communication link to exchange navigation data. Performance assessment is carried out by conducting multiple experimental flight tests.https://www.mdpi.com/1424-8220/20/2/538unmanned aerial vehiclesmagnetometersmagnetic biasmagnetic headingmulti-uav cooperationvision-based relative sensinggnss-based relative sensinglevenberg-marquardt |
| spellingShingle | Roberto Opromolla Magnetometer Calibration for Small Unmanned Aerial Vehicles Using Cooperative Flight Data Sensors unmanned aerial vehicles magnetometers magnetic bias magnetic heading multi-uav cooperation vision-based relative sensing gnss-based relative sensing levenberg-marquardt |
| title | Magnetometer Calibration for Small Unmanned Aerial Vehicles Using Cooperative Flight Data |
| title_full | Magnetometer Calibration for Small Unmanned Aerial Vehicles Using Cooperative Flight Data |
| title_fullStr | Magnetometer Calibration for Small Unmanned Aerial Vehicles Using Cooperative Flight Data |
| title_full_unstemmed | Magnetometer Calibration for Small Unmanned Aerial Vehicles Using Cooperative Flight Data |
| title_short | Magnetometer Calibration for Small Unmanned Aerial Vehicles Using Cooperative Flight Data |
| title_sort | magnetometer calibration for small unmanned aerial vehicles using cooperative flight data |
| topic | unmanned aerial vehicles magnetometers magnetic bias magnetic heading multi-uav cooperation vision-based relative sensing gnss-based relative sensing levenberg-marquardt |
| url | https://www.mdpi.com/1424-8220/20/2/538 |
| work_keys_str_mv | AT robertoopromolla magnetometercalibrationforsmallunmannedaerialvehiclesusingcooperativeflightdata |