title: Ground Penetrating Radar as a Contextual Sensor for Multi-Sensor Radiological Characterisation.
abstract: Radioactive sources exist in environments or contexts that influence how they are detected and localised. For instance, the context of a moving source is different from a stationary source because of the effects of motion. The need to incorporate this contextual information in the radiation detection and localisation process has necessitated the integration of radiological and contextual sensors. The benefits of the successful integration of both types of sensors is well known and widely reported in fields such as medical imaging. However, the integration of both types of sensors has also led to innovative solutions to challenges in characterising radioactive sources in non-medical applications. This paper presents a review of such recent applications. It also identifies that these applications mostly use visual sensors as contextual sensors for characterising radiation sources. However, visual sensors cannot retrieve contextual information about radioactive wastes located in opaque environments encountered at nuclear sites, e.g., underground contamination. Consequently, this paper also examines ground-penetrating radar (GPR) as a contextual sensor for characterising this category of wastes and proposes several ways of integrating data from GPR and radiological sensors. Finally, it demonstrates combined GPR and radiation imaging for three-dimensional localisation of contamination in underground pipes using radiation transport and GPR simulations.
authors.affiliation: Engineering Department, Lancaster University, Lancaster LA1 4YW, UK. i.ukaegbu@lancaster.ac.uk.
authors.forename: Ikechukwu K
authors.initials: IK
authors.lastname: Ukaegbu
authors.affiliation: Engineering Department, Lancaster University, Lancaster LA1 4YW, UK. k.gamage@lancaster.ac.uk.
authors.forename: Kelum A A
authors.initials: KA
authors.lastname: Gamage
keywords: ground-penetrating radar; radiological characterisation and multi-sensor data fusion