Reconstruction of indoor gamma-ray background spectrum for HPGe detectors

Background reconstruction stands as a critical technique for diverse domains, such as signal isolation for gamma spectroscopy, pre-testing of radiation shielding designs, and environmental monitoring. Traditional methods aim to seek the optimal intensity of the background source under a fixed spatial distribution. However, their efficacy is often constrained due to the limited number of variable parameters, resulting in inadequate degrees of freedom and suboptimal performance. This paper introduces an innovative method for background reconstruction, aiming to overcome the limitations of existing approaches. The proposed technique involves the simultaneous adjustment of both intensities and shell thicknesses of a series of monoenergetic sources, modeled as spherical shells. The reconstructed spectrum is conceptualized as a superposition of simulated spectra from these sources, with the optimized parameters being the intensity and thickness of each source. The objective is to minimize the disparity in regions of interest (ROIs) between reconstructed and target spectra through a multivariate nonlinear optimization process, incorporating distinct weight factors for each ROI. The efficacy of the proposed method is validated using a simulation-generated theoretical spectrum. Results demonstrate successful reconstruction, with a high overall concordance between reconstructed and target spectra, showcasing reliability of the method. Subsequently, the method is applied to the reconstruction of an experimental spectrum, and a comparative analysis with a fixed spherical shell thickness method reveals the superior agreement of our proposed method with the experimental spectra.