Applicability and parameter optimization of the SASNIP algorithm for background subtraction of gamma spectra measured...

The accuracy of gamma spectrum background subtraction directly governs the reliability of radionuclide quantitative analysis. The step-approximation statistics-sensitive nonlinear iterative peak-clipping (SASNIP) algorithm has been verified for background removal of gamma spectra collected by high-purity germanium (HPGe) detectors, yet its adaptability and optimal parameter configuration for low-resolution thallium-doped sodium iodide (NaI(Tl)) scintillation gamma spectra have not been systematically studied. In this paper, two groups of measured ¹⁵²Eu gamma spectral datasets-original raw spectra with complex scattering backgrounds and scattering-corrected spectra after scattering component elimination-are employed to investigate how the two core parameters of SASNIP, namely the window width scaling coefficient t and iteration termination threshold, affect background subtraction accuracy. The mean absolute relative deviation (MARD) of net counting rates of multiple characteristic peaks and the standard deviation (SD) of absolute relative deviations were adopted as evaluation metrics for the accuracy of calculated net peak areas. Experimental results indicate that the window width scaling coefficient t dominates the overall background subtraction performance; quantification accuracy improves first and then deteriorates as t increases. When t is fixed, varying the iteration termination threshold does not lead to an obvious monotonic change in subtraction accuracy. Although raw spectra and scattering-corrected spectra differ greatly in background complexity, the optimal parameter combination applicable to both datasets is unified: scaling coefficient t = 0.8 and iteration termination threshold of 0.5%. This work confirms that the SASNIP algorithm achieves stable, accurate background stripping for NaI(Tl) gamma spectra.