Litcius/Paper detail

Overhauser Sensor Array Based 3-D Magnetic Gradiometer for the Detection of Shallow Subsurface Unexploded Ordnance

Hongpeng Wang, Tao Meng, Wang Luo, Ruiping Yang, Huan Liu, Jian Ge, Haobin Dong

2023IEEE Transactions on Instrumentation and Measurement13 citationsDOI

Abstract

The information on the high-precision and multi-directional magnetic gradient is highly relevant to detecting and locating shallow subsurface unexploded ordnance. In this paper, the design of a three-dimensional (3D) Overhauser magnetic gradiometer is presented. Taking the sensor array interferences and working efficiency into account, a time slice overlapping based operating time sequence is devised. A precision narrow-band tuning capacitance network based on a cascaded subdivision strategy is constructed to improve the signal-to-noise ratio (SNR) of free induction decay (FID) signals. Additionally, a frequency measuring approach combining multi-phase clock and multi-channel is developed to suppress counting errors and improve the frequency measuring accuracy of FID signals. The 3D Overhauser magnetic gradiometer’s effectiveness was validated through extensive laboratory and field experiments. The laboratory test results show that the magnetic measuring performance of each sensor from the Overhauser magnetic sensor array is consistent. The proposed 3D Overhauser magnetic gradiometer is able to measure magnetic fields from 20 μT to 100 μT with an indicating error of less than 0.1 nT. The field exploration demonstrates the applicability of the gradiometer for shallow subsurface unexploded ordnance detection within the urban complex electromagnetic surroundings. Overall, this study can provide support for the accurate detection and localization of shallow subsurface unexploded ordnance under strong interference surroundings.

Topics & Concepts

GradiometerUnexploded ordnanceAcousticsNoise (video)SIGNAL (programming language)Signal-to-noise ratio (imaging)Sensor arrayMagnetic fieldComputer scienceMagnetometerRemote sensingElectronic engineeringPhysicsOpticsGeologyEngineeringArtificial intelligenceProgramming languageMachine learningImage (mathematics)Quantum mechanicsGeophysical and Geoelectrical MethodsMagnetic Field Sensors TechniquesGeophysical Methods and Applications