activity
20202025
most citedReconstructing the Position and Intensity of Multiple Gamma-Ray Point Sources with a Sparse Parametric Algorithm

27 citations · 75 across the 11 of their papers we have counts for

collaborators

11 papers

physics.ins-det2025

Data-driven performance optimization of gamma spectrometers with many channels

Jayson R. Vavrek, Hannah S. Parrilla, Gabriel Aversano +3

In gamma spectrometers with variable spectroscopic performance across many channels (e.g., many pixels or voxels), a tradeoff exists between including data from successively worse-…

physics.ins-det2025

Demonstration of a new CLLBC-based gamma- and neutron-sensitive free-moving omnidirectional imaging detector

Jayson R. Vavrek, Ryan Pavlovsky, Victor Negut +4

We have developed a CLLBC-based gamma- and neutron-sensitive multi-channel omnidirectional imaging detector, suitable for handheld or vehicle-borne operation and capable of quantit…

physics.ins-det2024★ 2 cited

Simulations of Sparse Static Detector Networks for City-Scale Radiological/Nuclear Detection

E. Rofors, N. Abgrall, M. S. Bandstra +6

Sparse static detector networks in urban environments can be used in efforts to detect illicit radioactive sources, such as stolen nuclear material or radioactive "dirty bombs". We…

physics.ins-det2024

Surrogate distributed radiological sources III: quantitative distributed source reconstructions

Jayson R. Vavrek, Jaewon Lee, Marco Salathe +4

In this third part of a multi-paper series, we present quantitative image reconstruction results from aerial measurements of eight different surrogate distributed gamma-ray sources…

eess.SP2023★ 1 cited

Mobile Object Tracking in Panoramic Video and LiDAR for Radiological Source-Object Attribution and Improved Source Detection

M. R. Marshall, R. J. Cooper, J. C. Curtis +4

The addition of contextual sensors to mobile radiation sensors provides valuable information about radiological source encounters that can assist in adjudication of alarms. This st…

physics.ins-det2023

Networked Sensing for Radiation Detection, Localization, and Tracking

R. J. Cooper, N. Abgrall, G. Aversano +18

The detection, identification, and localization of illicit radiological and nuclear material continue to be key components of nuclear non-proliferation and nuclear security efforts…

physics.ins-det2023

Background and Anomaly Learning Methods for Static Gamma-ray Detectors

M. S. Bandstra, N. Abgrall, R. J. Cooper +8

Static gamma-ray detector systems that are deployed outdoors for radiological monitoring purposes experience time- and spatially-varying natural backgrounds and encounters with man…

physics.ins-det2022★ 1 cited

Design and deployment of radiological point-source arrays for the emulation of continuous distributed sources

Jayson R. Vavrek, C. Corey Hines, Mark S. Bandstra +6

We demonstrate a method for using arrays of point sources that emulate -- when measured from a standoff of at least several meters -- distributed gamma-ray sources, and present res…

physics.ins-det2021★ 25 cited

Free-moving Quantitative Gamma-ray Imaging

Daniel Hellfeld, Mark S. Bandstra, Jayson R. Vavrek +11

The ability to map and estimate the activity of radiological source distributions in unknown three-dimensional environments has applications in the prevention and response to radio…

physics.ins-det2021★ 19 cited

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

M. S. Bandstra, D. Hellfeld, J. R. Vavrek +8

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 t…

physics.ins-det2020★ 27 cited

Reconstructing the Position and Intensity of Multiple Gamma-Ray Point Sources with a Sparse Parametric Algorithm

Jayson R. Vavrek, Daniel Hellfeld, Mark S. Bandstra +8

We present an experimental demonstration of Additive Point Source Localization (APSL), a sparse parametric imaging algorithm that reconstructs the 3D positions and activities of mu…