Ground Radioactivity Distribution Reconstruction and Dose Rate Estimation Based on Spectrum Deconvolution.

Area of Science:

• Nuclear physics and environmental monitoring.
• Application of spectral deconvolution in radioactivity assessment.

Background:

• Accurate estimation of gamma dose rates and radioactive pollution distribution is crucial for aerial radiation monitoring using unmanned aerial vehicles.
• Current methods face challenges in reconstructing complex surface source radioactivity distributions.

Purpose of the Study:

• To propose a novel reconstruction algorithm for ground radioactivity distribution based on spectral deconvolution.
• To achieve accurate dose rate estimation at one meter above ground level from aerial monitoring data.
• To effectively reconstruct the distribution of multiple radioactive nuclides and their pollution levels.

Main Methods:

• Developed a spectral deconvolution algorithm to estimate radioactive nuclide types and their distributions.
• Incorporated energy windows to enhance the accuracy of deconvolution results.
• Validated the algorithm through modeling of single-nuclide (¹³⁷Cs) and multi-nuclide (¹³⁷Cs, ⁶⁰Co) surface sources.

Main Results:

• The algorithm accurately reconstructed radioactivity distribution and estimated dose rates, achieving high cosine similarities (0.9950 and 0.9965) with true values.
• Effectively distinguished and restored the radioactivity distribution of multiple radioactive nuclides.
• Demonstrated that lower statistical fluctuation and more energy window divisions improve deconvolution accuracy.

Conclusions:

• The proposed spectral deconvolution algorithm provides an effective method for regional surface source radioactivity distribution reconstruction and dose rate estimation.
• The technique enhances the capabilities of unmanned aerial vehicle nuclear radiation monitoring systems.
• Further improvements in accuracy are achievable by minimizing statistical fluctuations and optimizing energy window divisions.