High-Speed Magnetic Surveying for Unexploded Ordnance Using UAV Systems
Using Uncrewed Aerial vehicles (UAVs) to rapidly scan areas for potential unexploded ordnance (UXO) can provide an efficiency increase while minimizing detonation risks. We present a complete overview of how such mappings can be performed using scalar magnetometers, including initial sensor testing,...
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Published in | Remote sensing (Basel, Switzerland) Vol. 14; no. 5; p. 1134 |
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Main Authors | , , , , |
Format | Journal Article |
Language | English |
Published |
Basel
MDPI AG
01.03.2022
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Subjects | |
Online Access | Get full text |
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Summary: | Using Uncrewed Aerial vehicles (UAVs) to rapidly scan areas for potential unexploded ordnance (UXO) can provide an efficiency increase while minimizing detonation risks. We present a complete overview of how such mappings can be performed using scalar magnetometers, including initial sensor testing, time stamping validation, data positioning, noise removal, and source model inversion. A test survey was performed across disarmed UXO targets, during which three scalar magnetometers were towed in an airframe (“bird”) 10 m below a small (<25 kg) high speed (∼10 m/s) UAV to avoid magnetic disturbances from the UAV itself. Data were collected across ∼58 min of flight, with each sensor traversing ∼31.7 km to acquire dense data coverage across a 600 m × 100 m area. By using three individual magnetometers in the bird, UXO detection results across single-sensor data and several different multi-sensor configurations can be compared. The data obtained exhibited low apparent noise floors (on the order of tens of picoTesla) and retained a precision that enabled targeted modelling and removal of high-frequency noise with amplitudes of ±5 picoTesla. All of the different gradiometer configurations tested enabled recovery of most targets (including all major targets), although the horizontal configuration performed significantly worse in comparison. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 |
ISSN: | 2072-4292 2072-4292 |
DOI: | 10.3390/rs14051134 |