强噪声背景下微弱核脉冲信号提取方法

Weak nuclear pulse signal extraction from intensive background noise

针对强噪声背景下,微弱核脉冲信号的幅度与发生时刻信息检测存在困难的问题,提出一种基于Gabor变换及稀疏表示的核脉冲信号提取方法.首先利用Gabor变换根据样本信号构建单核脉冲信号表示字典;其次采用K-SVD算法消除因不同探测器和噪声引起的Gabor基函数的差异,构建完备字典,将其用于表征淹没在噪声中的有用信号,通过改进的OMP算法重构信号达到抑制噪声的目的,实现微弱核脉冲信号的提取.为验证该方法的可行性和有效性,利用CsI(Tl)探测器测量得到的实际核脉冲信号和仿真数据进行实验,结果表明,所提出算法恢复的核脉冲信号幅度和峰值发生时刻误差小于传统的Salley-Key最优平滑滤波和Kalman滤波算法.

It is a very challenging problem to extract the amplitude and occurring time of weak nuclear pulse signals in the existence of intensive background noise.To solve this problem,this paper proposes a pulse signal estimation method based on Gabor transform and sparse representation.Firstly,it builds a pulse signal representation dictionary through the Gabor decomposition of mononuclear pulse signal samples.Then it eliminates the fluctuation of the Gabor bases,which is caused by the detector variation and the measurement noise,by using K-SVD algorithm,and learns a self-consistent over-complete dictionary which is used to represent the useful signal being overwhelmed in the background noise.Finally,it reconstructs the desired signal by an improved OMP algorithm,greatly attenuates the noise and achieves the goal of extracting the weak nuclear pulse signal.The effectiveness and efficiency of the proposed method are verified through simulations and experiments on a CsI(Tl)detector.Results confirm that the proposed method outperforms the traditional Salley-Keys smoothing and Kalman filtering methods with smaller estimation errors of the amplitude and peak occurring time of the concerned nuclear pulse signal.