The U. S. Army Engineer Research and Development Center (ERDC) is the lead Army research and development organization for force protection, military engineering, and geospatial research engineering. The ERDC is expanding its efforts in support of new Department of Defense (DoD) protection requirements and capability gaps for troops in high-threat environments. The present work is critical to meet protection requirements and capability gaps for current research and development programs and for the planning and scheduling for future science and technology efforts within the U.S. DoD.

The Cold Regions Research and Engineering Laboratory (ERDC-CRREL) and the Geotechnical Structures Laboratory (ERDC-GSL) are supporting the U.S. Air Force Civil Engineer Center through research and development of an unmanned aerial vehicle–mounted electromagnetic induction (EMI) device capable of localizing embedded unexploded ordinance (UXO) for expedited runway and military range remediation. There are presently no standoff (no ground contact) UXO detection capabilities available to soldiers. Developing and delivering such a capability will provide a distinct improvement in their ability to quickly and efficiently recover from an attack.

EMI is a noninvasive, standoff geophysical technique that can be used to localize and determine orientation of UXO and underground cavities caused by fragmented munitions detonation. EMI devices have long been used for mapping UXO and detecting improvised explosive devices (IED). Additionally, they have been flown on helicopter-based airborne systems for large-scale mineral exploration and groundwater applications. Yet, until recently, they have not been evaluated for use on unmanned aerial systems (UASs) in a reconnaissance approach. While other geophysical techniques are gaining popularity for UAS sensor implementation, EMI for UASs has not yet been successfully implemented. With that in mind, there are some academic institutions and research groups working on the problem.

Potential applications for a UAS-based EMI system are widespread from civil infrastructure, such as permafrost mapping, levee and dam assessment, slope stability assessment, and landfill characterization, to military mobility operations, including UXO and IED detection, runway remediation, and ground surface structural competency evaluations.

The initial development phases of this UAS-based EMI system require an understanding of the electromagnetic fields emitted by the UAS platform itself to optimize the performance of the system. Here we measure the fields emitted by two different UAS motor configurations at varying standoff distances from 0 to 53 cm. For this initial phase of the investigation, shielding variables are not introduced. The results from the investigation determine the minimum distance needed for the sensor to operate without negative influence from the electrical noise of the UAS motor.

The U.S. military has a need to remotely characterize in situ UXO associated with runway bombardment. While EMI sensors exist for UXO detection, there are currently no UAS-based EMI systems that can provide this remote characterization of UXO with a near-real-time target classification. The EMI sensors currently available for detection and classification of metallic UXO and IEDs are bulky and cumbersome, making it difficult to implement on a remotely controlled UAS acquisition system. ERDC-CRREL and ERDC-GSL, in conjunction with Dartmouth College, has developed or aided in the development of multiple EMI devices for detection of UXO and IEDs, including GEM-3D, MPV, MPV-II, Pedemis, and High-Frequency EMI (HFEMI) for nonmetallic UXO.

This work was done by Benjamin Barrowes, Dan R. Glaser, Brian G. Quinn, Mikheil Prishvin, and Fridon Shubitidze for the Army Engineer Research and Development Center. For more information, download the Technical Support Package (free white paper) below. ERDC-0012

This Brief includes a Technical Support Package (TSP).
Unmanned Aerial Systems Electromagnetic Induction Sensor Development

(reference ERDC-0012) is currently available for download from the TSP library.

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