Trigonometric functions-based gaussian-like shaping algorithms for nuclear signals

Abstract

BackgroundGaussian shaping is commonly used to filter and extract the amplitude of nuclear pulse signals owing to its high signal-to-noise ratio, resistance to ballistic loss, and ease of amplitude extraction. However, the problems of asymmetry and downwash exist in Gaussian-like signals generated by Sallen-Key and CR-(RC)m filters.PurposeThis study aims to address the problems of asymmetry and downwash in Gaussian-like signals generated by Sallen-Key and CR-(RC)m filters, this paper presents a trigonometric function-based Gaussian-like pulse shaping algorithm for dual-exponential signals.MethodsFirst, the impact of shaping parameters on the shaping pulse and filtering performance of the algorithm was examined by applying Gaussian-like pulse shaping to simulated nuclear pulse signals. Then, the filtering performances of Gaussian-like and sin pulse shaping algorithms were compared and analyzed using the same shaping width. Finally, the characteristic X-ray signals of manganese (FAST-SDD detector) were collected using a self-made digital nuclear signal acquisition board under various tube flows. The energy resolution and count rate characteristics of the energy spectra obtained from Gaussian-like, sin, and trapezoidal shaping algorithms were comparatively analyzed for different tube flows and shaping times.ResultsComparison results show that Gaussian pulse shaping exhibits superior denoising performance to sin pulse shaping, with an 8.95% improvement in the SNR for the same peak arrival time. Additionally, the energy resolution of the spectrum obtained using Gaussian pulse shaping exceeds that of sin pulse shaping, and its stacking pulse separation ability outperforms that of trapezoidal pulse shaping, making it highly applicable.ConclusionsGaussian-like pulse shaping presented in this study demonstrats better stacking pulse separation capability than trapezoidal pulse shaping, indicating promising application prospects.

Keywords

• digital nuclear pulse signal
• gaussian-like shaping
• trigonometric digital shaping
• energy resolution