一种基于频率细分的X射线脉冲星周期估计方法

Li-Rong Shen; Xiao-Ping Li; Hai-Feng Sun; Hai-Yan Fang; Meng-Fan Xue

doi:10.1631/FITEE.1500052

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一种基于频率细分的X射线脉冲星周期估计方法

计算机与自动化 | Updated：2022-06-06

- 一种基于频率细分的X射线脉冲星周期估计方法
- A novel period estimation method for X-ray pulsars based on frequency subdivision*
- 信息与电子工程前沿（英文） 2015年16卷第10期页码：858-870
- Affiliations：
  
  School of Aerospace Science and Technology, Xidian University, Xi’an 710071, China
- Author bio：
  
  ‡Corresponding Author
  †E-mail:slr_xidian@163.comxpli@xidian.edu.cnsunhaifeng@163.comhyfang@xidian.edu.cnxuemf@163.com
- Funds：
  
  *Project supported by the National Basic Research Program (973) of China (No. 2014CB340205), the National Natural Science Foundation of China (Nos. 61301173 and 61473228), and the Aerospaced TT&C Innovation Program of 704 Research Institute of China (No. 201405B)
- DOI：10.1631/FITEE.1500052
  中图分类号：
- 收稿：2015-02-09，
  
  修回：2015-09-09，
  
  录用：2015-06-19，
  
  纸质出版：2015-10
- Accepted：
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一种基于频率细分的X射线脉冲星周期估计方法[J]. 信息与电子工程前沿（英文）, 2015,16(10):858-870.

Li-Rong Shen, Xiao-Ping Li, Hai-Feng Sun, et al. A novel period estimation method for X-ray pulsars based on frequency subdivision*[J]. Frontiers of Information Technology & Electronic Engineering, 2015, 16(10): 858-870.
一种基于频率细分的X射线脉冲星周期估计方法[J]. 信息与电子工程前沿（英文）, 2015,16(10):858-870. DOI： 10.1631/FITEE.1500052.

Li-Rong Shen, Xiao-Ping Li, Hai-Feng Sun, et al. A novel period estimation method for X-ray pulsars based on frequency subdivision*[J]. Frontiers of Information Technology & Electronic Engineering, 2015, 16(10): 858-870. DOI： 10.1631/FITEE.1500052.

摘要

目的

针对现有脉冲星周期估计算法精度低的问题，研究一种利用短时观测数据进行高精度X射线脉冲星周期估计的算法，为促进实时高精度X射线脉冲星导航提供算法支撑。

创新点

提出频率细分的方法，推导continuous Lomb periodogram (CLP)

实现X射线脉冲星非等间隔到达光子序列在细分频率处的频域分析。该方法可以显著减少运算复杂度，同时提高频域分析的频率分辨率，进而提高脉冲星周期估计的精度。

方法

首先，考虑到X射线脉冲星信号是非等间隔到达的光子序列，本文采用专门用于非等间隔数据处理的fast Lomb方法对一段短时观测的脉冲星实测数据进行频域分析，获得一个初始频率作为脉冲星旋转频率的初值。然后，在该初始频率附近以高的频率分辨率做频率细分，获取设定数量的高精度细分频率。最后，对该段短时观测的脉冲星数据在这些细分频率处做CLP分析。在CLP中，峰值位置所对应的频率即为估计出的具有较高精度的脉冲星旋转频率，由该频率就可以确定高精度的脉冲星旋转周期。实测数据分析表明：当观测数据小于135 s时，本文算法的周期估计精度比fast Lomb方法和FFT方法高1到3个数量级，且仅增加了一点计算复杂度。同时，相比于HEAsoft的周期估计方法（efsearch），本文算法具有精度高计算复杂度低的优势。

结论

本文算法解决了fast Lomb方法在周期估计时精度受数据长度和观测时间限制的问题，显著提高了X射线脉冲星周期估计的精度并降低了计算复杂度。同时短时高精度的周期估计有助于提高TOA估计精度及X射线脉冲星导航中实时位置和速度的估计精度。本文算法还可以用于变星及其他天体的周期估计。

Abstract

Period estimation of X-ray pulsars plays an important role in X-ray pulsar based navigation (XPNAV). The fast Lomb periodogram is suitable for period estimation of X-ray pulsars

but its performance in terms of frequency resolution is limited by data length and observation time. Longer observation time or oversampling can be employed to improve frequency analysis results

but with greatly increased computational complexity and large amounts of sampling data. This greatly restricts real-time autonomous navigation based on X-ray pulsars. To resolve this issue

a new method based on frequency subdivision and the continuous Lomb periodogram (CLP) is proposed to improve precision of period estimation using short-time observation data. In the proposed method

an initial frequency is first calculated using fast Lomb periodogram. Then frequency subdivision is performed near the initial frequency to obtain frequencies with higher precision. Finally

a refined period is achieved by calculating the CLP in the obtained frequencies. Real data experiments show that when observation time is shorter than 135 s

the proposed method improves period estimation precision by 1–3 orders of magnitude compared with the fast Lomb periodogram and fast Fourier transform (FFT) methods

with only a slight increase in computational complexity. Furthermore

the proposed method performs better than efsearch (a period estimation method of HEAsoft) with lower computational complexity. The proposed method is suitable for estimating periods of X-ray pulsars and obtaining the rotation period of variable stars and other celestial bodies.

关键词

Keywords

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