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基于Bayesian估计的X射线脉冲星微弱信号检测
  • 期刊名称:物理学报(SCI/EI)
  • 时间:0
  • 分类:TP181[自动化与计算机技术—控制科学与工程;自动化与计算机技术—控制理论与控制工程]
  • 作者机构:[1]西安电子科技大学电子工程学院,西安710071
  • 相关基金:国家高技术研究发展计划(批准号:2007AA12Z323); 国家自然科学基金(批准号:60772139)资助的课题
  • 相关项目:基于X射线脉冲星源的自主导航定位机理及关键技术研究
中文摘要:

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.

英文摘要:

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.

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