微弱核辐射信号稀疏重构模型及核素快速识别方法研究

项目名称： 微弱核辐射信号稀疏重构模型及核素快速识别方法研究

项目编号： No.61501385

项目类型： 青年科学基金项目

立项/批准年度： 2016

项目学科： 无线电电子学、电信技术

项目作者： 王坤朋

作者单位： 西南科技大学

项目金额： 19万元

中文摘要： 本项目针对非接触式放射性材料探测中由环境本底噪声和康普顿散射引起的微弱核辐射信号难以检测的问题，以及复杂检测情境下由屏蔽体反射、衰减或运载工具运动等因素引起的γ能谱畸变问题，以提高强噪声背景下信号检测能力为切入点，探索核辐射信号的稀疏重构和能谱畸变校正方法，使之满足放射性材料微弱信号提取与核素识别的需求。通过对典型噪声的特征分析和统计建模，将噪声分为结构化和非结构化噪声，利用结构化噪声和核辐射信号理论波形建立用于表征隐藏在含噪信号下本真信号的过完备字典，并基于序贯贝叶斯分析进行核辐射特征脉冲甄别，采用稀疏信号重构的方式，提取被噪声污染的微弱核辐射信号；研究检测情境中干扰因素对能谱畸变的影响规律及影响关系的数学描述，去除由确定性因素引起的能谱测量误差；并基于证据理论对冗余信息和互补信息进行融合，解决在短时检测中γ射线全能峰不满足高斯假设而引起的能谱量测不确定性，最终实现核素种类的准确识别。

中文关键词： 弱信号检测；稀疏重构；γ能谱校正；信息融合；核素识别

英文摘要： Non-connect detection and recognition of radioactive material are open problems in nuclear arms control examination, the nuclear material smuggling and nuclear nonproliferation, etc. Because of the environmental background noise and Compton scattering events interference have great effect to week nuclear radiation signals detection, and gamma energy spectrum are easily distorted by the effect of shield reflection/attenuation or vehicle movement in complex testing situation. In this project, a novel week nuclear radiation signal sparse reconstruction method and a practical spectral distortion correction method are employed to improve the week signal detection and recognition performance under strong noise background. Through the characteristics analyzing and statistical modeling of typical noise, the noises can be classified into two categories: structured and unstructured. An over-complete dictionary is constructed by using the structured noise signal and the theoretical nuclear radiation signal waveform, which used for representation of the potential true signal in noise background. Then, using the sequential Bayesian analysis method to identify valid nuclear pulses, and applying sparse signal reconstructing method extract the corrupted week nuclear radiation signal. By analyzing the spectral distortion interference factors in the testing situation, build the mathematical description between spectral distortion and interference factors, the spectral distortion interference factors in the testing situation is analyzed, and the mathematical description between spectral distortion and interference factors is established. Based on evidence theory take the advantage of the redundant information and complementary information to solve the energy spectrum measurement uncertainty, which caused by full-energy peak does not meet the Gaussian hypothesis in short time detection. Finally the types of radioactive nuclide are accurately recognized.

英文关键词： Weak Signal Detection;Sparse Reconstruction;Gamma Spectrum Calibration;Information Fusion;Nuclide Identification