A scheme for decomposing overlapping peak based on the adaptive convolution method and enhanced northern goshawk...

NaI(Tl) gamma-ray energy spectrometers remain widely used in radioactivity measurements, but their limited resolution often causes overlapping peaks, complicating spectral analysis. To overcome this, we propose a scheme that combines an adaptive convolution (AC) method with an enhanced northern goshawk optimization (ENGO) algorithm. The AC method effectively suppresses background interference and improves noise resistance while preserving overlapping information. The ENGO algorithm, incorporating SPM chaotic mapping, Lévy flight, and a nonlinear step-size strategy, enhances parameter optimization in high-dimensional space. Applied to overlapping peaks within energy spectrums from numerical simulated, Monte Carlo simulated and IAEA, the scheme achieves relative deviations within ±0.530 %, ±0.573 %, ±1.173 % for all peak parameters and areas respectively, demonstrating accurate overlapping peak decomposition without background subtraction.