基于Bayesian估计的X射线脉冲星微弱信号检测

累积轮廓、流量和周期是X射线脉冲星辐射信号的三个重要特征,将其应用于X射线脉冲星信号检测中,提出了一种基于Bayesian估计的X射线脉冲星周期辐射信号时域检测方法.该方法以非脉冲区噪声观测为先验知识,利用X射线脉冲星辐射信号的泊松分布模型推导了信号概率密度分布函数,以该函数的累积分布函数为判据,对X射线脉冲星微弱信号进行检测,并提取位相偏移量.利用仿真数据和RXTE卫星的实测数据进行实验验证,结果表明:本文方法性能优于同类的基于高斯分布模型的检测方法,在检测信号的同时能在一定精度下给出信号位相偏移值. 关键词： 脉冲星 Bayesian估计 位相测量 时域检测

X-ray pulsar weak signal detection based on Bayesian estimation

Integrated profile, flux and period are three major characteristics of pulsar. Taking advantage of these characteristics, a time domain detecting method is presented based on Bayesian estimation to detect pulsar periodic radiation signals. The signal probability distribution is deduced based on the Poisson distribution model of X-ray pulsar, with noise observation of non-pulse region used as the priori knowledge. The cumulative distribution function of the signal probability is used as a criterion to detect weak signals of X-ray pulsars and extract the phase offset. The RXTE data and the simulation data are used for experimental verification, and the results show that the method outperforms a similar method which is based on the Gauss distribution model, in addition, it can give the phase offset in a certain accuracy.