Nuclear Techniques ›› 2020, Vol. 43 ›› Issue (6): 60401-060401.

• NUCLEAR ELECTRONICS AND INSTRUMENTATION •

### Application of improved Simpson-SNIP algorithm in background subtraction of airborne gamma-ray instrument spectrum

Jin YANG,Fei LI,Liangquan GE(),Qingxian ZHANG,Maolin XIONG,Kun SUN,Yi GU

1. The College of Nuclear Technology and Automation Engineering, Chengdu University of Technology, Chengdu 610059, China
• Received:2020-02-18 Revised:2020-04-05 Online:2020-06-15 Published:2020-06-12
• Contact: Liangquan GE E-mail:glq@cdut.edu.cn
• About author:YANG Jin, male, born in 1995, graduated from The Engineering Technical College of Chengdu University of Technology in 2018, master student, focusing on nuclear technology and its application
• Supported by:
National Natural Science Foundation of China(41774147);National Key Research and Development Plan(2017YFC0602105);Sichuan Science and Technology Support Program Project(2018GZ0004)

Abstract: Background

The background count in airborne gamma-ray spectrum measurement is mainly caused by Compton scattering effects, small angle scattering of gamma rays in the sensitive volume of the detector and interference caused by electronic noise in the energy range of the energy spectrum. Background subtraction is one of the important tasks of instrument spectral resolution in airborne gamma-ray measurement.

Purpose

This study aims to propose an improved background subtraction method to achieve accurate and efficient spectral analysis of airborne gamma-ray instrument spectrum.

Methods

As one of the best background subtraction algorithms, the statistics-sensitive nonlinear iterative peak-clipping (SNIP) algorithm with simple mathematical structure and reliable background subtraction effect, was easily affected by the parameters of peak width, and lead to longer running time due to slow convergence speed of iterative process. Motivated by the idea of the Simpson formula with higher algebraic precision, the second step of the SNIP iteration in the original algorithm was improved by using three points of interval bisection for integral interpolation. Comparison of SNIP algorithm before and after the improvement was performed for background subtraction of airborne gamma-ray spectrum with different iteration times and appropriate width of transformation.

Results

The comparison results show that the accuracy and the overall operating efficiency of the improved algorithm are improved by 41.8% and 2.53%, respectively, compared with the original SNIP algorithm.

Conclusions

The improved Simpson-SNIP algorithm achieves fast convergence speed and better accuracy of calculation results while preserves the advantages of simplicity and efficiency of the original, hence better background deduction effect.

CLC Number:

• TL99