Improved Gamma-Ray Point Source Quantification in Three Dimensions by Modeling Attenuation in the Scene

TL;DR

This paper introduces a novel 3D gamma-ray source localization method that models scene attenuation using LiDAR data and maximum likelihood estimation, improving accuracy in complex environments.

Contribution

The work develops a voxelized scene model with attenuation estimation, enhancing gamma-ray source localization in 3D with intervening materials.

Findings

Accurately reconstructs source location and activity in simulated data.

Achieves good agreement with measured data.

Estimates attenuation coefficient of scene materials.

Abstract

Using a series of detector measurements taken at different locations to localize a source of radiation is a well-studied problem. The source of radiation is sometimes constrained to a single point-like source, in which case the location of the point source can be found using techniques such as maximum likelihood. Recent advancements have shown the ability to locate point sources in 2D and even 3D, but few have studied the effect of intervening material on the problem. In this work we examine gamma-ray data taken from a freely moving system and develop voxelized 3-D models of the scene using data from the onboard LiDAR. Ray casting is used to compute the distance each gamma ray travels through the scene material, which is then used to calculate attenuation assuming a single attenuation coefficient for solids within the geometry. Parameter estimation using maximum likelihood is performed to simultaneously find the attenuation coefficient, source activity, and source position that best match the data. Using a simulation, we validate the ability of this method to reconstruct the true location and activity of a source, along with the true attenuation coefficient of the structure it is inside, and then we apply the method to measured data with sources and find good agreement.