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Front. Inform. Technol. Electron. Eng.  2014, Vol. 15 Issue (6): 458-469    DOI: 10.1631/jzus.C1300347
    
A new maximum-likelihood phase estimation method for X-ray pulsar signals
Hua Zhang, Lu-ping Xu, Yang-he Shen, Rong Jiao, Jing-rong Sun
School of Aerospace Science and Technology, Xidian University, Xi'an 710126, China
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Abstract  X-ray pulsar navigation (XPNAV) is an attractive method for autonomous navigation of deep space in the future. Currently, techniques for estimating the phase of X-ray pulsar radiation involve the maximization of the general non-convex object functions based on the average profile from the epoch folding method. This results in the suppression of useful information and highly complex computation. In this paper, a new maximum likelihood (ML) phase estimation method that directly utilizes the measured time of arrivals (TOAs) is presented. The X-ray pulsar radiation will be treated as a cyclo-stationary process and the TOAs of the photons in a period will be redefined as a new process, whose probability distribution function is the normalized standard profile of the pulsar. We demonstrate that the new process is equivalent to the generally used Poisson model. Then, the phase estimation problem is recast as a cyclic shift parameter estimation under the ML estimation, and we also put forward a parallel ML estimation method to improve the ML solution. Numerical simulation results show that the estimator described here presents a higher precision and reduces the computational complexity compared with currently used estimators.

Key words： X-ray pulsar      Poisson model      Phase estimation      Maximum likelihood     
Received: 05 December 2013      Published: 06 June 2014
CLC:  TP273  
  V11  
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Hua Zhang
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Hua Zhang, Lu-ping Xu, Yang-he Shen, Rong Jiao, Jing-rong Sun. A new maximum-likelihood phase estimation method for X-ray pulsar signals. Front. Inform. Technol. Electron. Eng., 2014, 15(6): 458-469.

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http://www.zjujournals.com/xueshu/fitee/10.1631/jzus.C1300347     OR     http://www.zjujournals.com/xueshu/fitee/Y2014/V15/I6/458


X射线脉冲星的一种新型最大似然相位估计方法

研究目的：X射线脉冲星导航是未来深空自主导航的一个热点方向。当今，X射线脉冲星的相位估计方法涉及求解光子到达时间的泊松分布函数的最值问题，会导致非常大的运算量。本文采用最大似然估计解决相位估计问题，并提出一种新型最大似然估计方法。
创新要点：这种新型最大似然估计方法直接运用了光子到达时间信息，提高了估计精度。同时提出一种并行最大似然估计方法，减少了运算量，节省了相位估计时间。
方法提亮：将X射线脉冲星辐射看成循环平稳过程。这样，我们把一个周期内的光子到达时间重新定义为一个新的随机过程，并证明它的概率密度函数等同于脉冲星的归一化轮廓，即它等效为普遍应用的泊松过程。接着，我们用最大似然估计解决相位估计问题，并提出一种并行最大似然估计方法。
重要结论：同当今估计方法相比，仿真数据显示，这种新型最大似然方法不仅提高了估计精度，而且减少了运算量。

关键词： X射线脉冲星,  最大似然,  相位估计,  泊松过程 
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