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基于随机微分方程的脉冲星计时噪声建模方法及其导航应用-投稿深空探测前沿技术专刊

王禹淞,王奕迪,宋敏章,郑伟   

  1. 国防科技大学
  • 收稿日期:2026-02-27 修回日期:2026-09-07 出版日期:2026-09-10 发布日期:2026-09-10
  • 通讯作者: 王奕迪
  • 基金资助:
    国家自然科学基金;国家自然科学基金;湖南省杰出青年基金

Pulsar timing noise modeled with stochastic differential equation and its application in XNAV

Yu-Song WANGYidi WangMin-Zhang SONG宋2, 3   

  • Received:2026-02-27 Revised:2026-09-07 Online:2026-09-10 Published:2026-09-10
  • Contact: Yidi Wang

摘要: X射线脉冲星导航是一种十分有潜力的深空航天器自主导航技术。本文为了削弱脉冲星计时噪声对X射线脉冲星导航性能的影响,建立了脉冲星计时噪声的随机微分方程(Stochastic Differential Equation, SDE)模型并提出了改进的脉冲星导航方法。基于脉冲星天文中广泛采用的分数阶功率谱密度(Power Spectral Density, PSD)模型,将脉冲星计时噪声视为白噪声驱动的分数阶成形滤波器的输出。利用Oustaloup方法,将成形滤波器的分数阶传递函数近似为有理传递函数,并据此推导出脉冲星计时噪声的SDE模型。基于该SDE模型,提出了一种改进的脉冲星导航方法。该方法通过扩展状态法同步估计航天器的位置、速度以及脉冲星的计时噪声。基于仿真数据和NICER(Neutron star Interior Composition ExploreR)探测器实测数据的计算结果显示,所提的SDE模型能很好地表征脉冲星计时噪声的频域和时域特性。基于仿真和实测数据的计算结果显示,与不处理计时噪声的脉冲星导航方法和将计时噪声建模为一阶自回归(AutoRegressive, AR)模型的扩展状态法相比,本文所提的改进的脉冲星导航方法能够有效削弱计时噪声的影响,相比于基于AR模型的扩展状态法,所提方法将定位精度提高了约60%。

关键词: 脉冲星, X射线脉冲星导航, 脉冲星计时噪声, 成形滤波器, 随机微分方程

Abstract: X-ray pulsar-based navigation (XNAV) is a promising autonomous navigation technique for deep space spacecraft. To mitigate the impact of pulsar timing noise in XNAV, this paper proposes a stochastic differential equation (SDE) model for pulsar timing noise. Based on its fractional-order power spectral density (PSD) model, widely adopted in pulsar astronomy, pulsar timing noise is viewed as the output of a fractional-order shaping filter driven by white noise. The fractional-order transfer function of the shaping filter is approximated by a rational transfer function utilizing the Oustaloup approach, and the SDE model of the pulsar timing noise is then derived. Using the SDE model, an improved XNAV method is proposed that estimates pulsar timing noise along with the spacecraft's position and velocity. Experimental results based on simulated data and real data from NICER demonstrate that the derived SDE model performs well at characterizing pulsar timing noise in both the frequency and time domains. Compared with the conventional XNAV method, which does not account for pulsar timing noise, and the state-augmented (SA) approach with the first-order autoregressive (AR) model assumption, the proposed improved XNAV method achieves lower position estimation error. Compared with the SA approach with AR model assumption, the proposed method improved the position estimation accuracy by about 60%.

Key words: Pulsars, X-ray pulsar-based navigation, Pulsar timing noise, Shaping filter, Stochastic differential equation