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Chapter 61 A Direct Phase Estimation Method of X-ray Pulsar Signal Without Epoch Folding

机译:第61章无历元折叠的X射线脉冲星信号的直接相位估计方法

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X-ray Pulsar Navigation (XPNAV) is an attractive method for the future deep space autonomous navigation. Currently, techniques for the phase estimation of X-ray pulsar radiation involves maximization of generally non-convex object functions based on average profile from epoch folding method, which results in suppression of useful information and high computation. In this paper, a new maximum likelihood (ML) directly utilizing the measured Time of Arrivals (TOAs) is present. The x-ray pulsar radiation will be traded as a cyclostationary 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 proved the new process is equivalent to the general used Poisson model. Then, the phase estimation problem is recast as a cyclic shift parameter estimation process under ML estimation, and we also put forwards a parallel ML estimation method to improve the ML solution. Furthermore, numerical simulation results show how the herein described estimator present a higher precision and reduced computation complexity compared with the current estimators.
机译:X射线脉冲星导航(XPNAV)是未来深空自主导航的一种有吸引力的方法。当前,用于X射线脉冲星辐射的相位估计的技术涉及基于历元折叠方法的平均轮廓来最大化通常不凸的目标函数,这导致有用信息的抑制和高计算量。在本文中,提出了一种直接利用测得的到达时间(TOA)的新的最大似然(ML)。 X射线脉冲星辐射将以循环平稳过程进行交易,光子的TOA在一个周期内将被重新定义为新过程,其概率分布函数是脉冲星的归一化标准轮廓。我们证明了该新过程等效于通用的泊松模型。然后,将相位估计问题作为ML估计下的循环移位参数估计过程进行了重铸,并提出了并行ML估计方法以改进ML解决方案。此外,数值模拟结果表明,与当前的估计器相比,本文所述的估计器如何呈现出更高的精度和更低的计算复杂度。

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