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Analysis Of Noise Coherence In Airborne Magnetic Gradients For Uxo DetectionNormal access

Authors: T. Jeffrey Gamey, William E. Doll, Les P. Beard and David T. Bell
Event name: 16th EEGS Symposium on the Application of Geophysics to Engineering and Environmental Problems
Session: Unexploded Ordnance
Publication date: 06 April 2003
Organisations: EEGS
Language: English
Info: Extended abstract, PDF ( 760.74Kb )

Oak Ridge National Laboratory (ORNL) and the US Army Engineering and Support
Center, Huntsville (USAESCH) have been developing advanced helicopter platforms for
geophysical arrays since 1997. A significant portion of the funding since 1999 has been through
the Environmental Security Technology Certification Program (ESTCP). The most recent
refinements to the Oak Ridge Airborne Geophysical System (ORAGS) magnetometer array
focused on noise reduction techniques including specialized processing methods. In particular,
the use and optimal positioning of multiple sensors to reduce coherent noise through gradient
measurements has proven very effective.
In boom-mounted magnetometer systems, the primary noise source is the helicopter
itself. Noise from this source falls into two main categories: maneuver noise and rotor noise.
The former is relatively low frequency, while the latter is relatively high frequency. Frequency
filters of various types have been used with success, but fall short where the noise is within the
bandwidth of the signal. Such is often the case when searching for unexploded ordnance (UXO)
and other shallow targets at rapid flight speeds. Under these conditions, helicopter noise can be
reduced by making use of the fact that much of it is coherent between sensors.
In this paper, we follow up previous theoretical work (Gamey et al, SAGEEP 2002) with
field examples from recent ORAGS-VGrad surveys. We examine the coherence of various types
of helicopter noise and demonstrate that measured vertical gradients can offer raw signal-tonoise
improvements of 4:1 or more over comparable total field measurements.

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