Synthetic case study: discrimination of unexploded ordnance (UXO) and non-UXO sources with varying remanent magnetization strength using magnetic data

Abstract

Summary We investigate if it is theoretically possible to discriminate between unexploded ordnance (UXO) and non-UXO sources by modelling the magnetic dipole moment for ferrous objects of different shapes and sizes. This is carried out by approximating the volumetric demagnetization factors of rectangular prisms, representing shapes similar to a long rod or flat steel plate. By modelling different UXO as prolate spheroids the demagnetization factors can be determined which can be compared with the magnetic response of a prism. The inversion is carried out in a probabilistic framework, where the UXO forward model and the non-UXO forward model are assigned individual prior models in terms of shape, size, orientation and remanent magnetization of the object. 95 independent realizations of the prism prior model are generated to make 95 synthetic anomalies exemplifying non-UXO objects, which are inverted for using the UXO model. It is investigated if an identical magnetic moment can be produced between the two models and how well resolved the magnetic moment is in terms of the measured anomaly. The case study is carried out in two steps where we first have little prior information of expected UXO properties and another where a UXO prior is introduced with expected values of aspect ratio and size of 24 different UXO, that are often encountered in the North Sea. With no prior information of expected UXO, discrimination is at many times implausible, unless elongated rod prism objects are considered, where the magnetic moment often can not be reproduced by a spheroid. Introducing the UXO prior we achieve a much better discrimination rate when using the list of expected UXO properties. By using the UXO prior we can account for a much higher remanent magnetization allowed in the prior, and still achieve high discrimination capabilities in comparison to a case with no UXO prior.

Probing with Each Step: How a Walking Crab-like Robot Classifies Buried Cylinders in Sand with Hall-Effect Sensors

“…Recently though, some efforts have focused on mitigating this issue. For example, the feasibility of UXO and non-UXO discrimination from magnetic data using a probabilistic framework has recently been investigated by Wigh et al [ 14 ], and Blachnik et al [ 15 ] proposed a numerical modeling method for generating training data based on the Digital Twin concept.…”

The Electromagnetic Characteristics of UXO Using the Electromagnetic Method

“…The 2D plane response of the target body is calculated as further identi cation of the target body attitude parameter variations 16,17 . After the position of the target body is localized, monostatic measurements are applied to calculate the component response at different attitudes.…”

High-Speed Magnetic Surveying for Unexploded Ordnance Using UAV Systems

“…This allowed for a simpler analysis of how well-resolved the source position and moment estimates are using different sensor setups. Inversion for model parameters was performed using the probabilistic inversion framework described in [34,35], and validated against the the deterministic inversion approach documented in [12]. All inversions were carried out on the along track difference (ATD) of the sensor data, thereby circumventing the majority of the sensor heading error while enhancing smaller wavelengths [12,14].…”