A fast pulse phase estimation method for X-ray pulsar signals based on epoch folding

X-ray pulsar-based navigation (XPNAV) is an attractive method for autonomous deep-space navigation in the future. The pulse phase estimation is a key task in XPNAV and its accuracy directly determines the navigation accuracy. State-of-the-art pulse phase estimation techniques either suffer from poor estimation accuracy, or involve the maximization of generally non-convex object function, thus resulting in a large computational cost. In this paper, a fast pulse phase estimation method based on epoch folding is presented. The statistical properties of the observed profile obtained through epoch folding are developed. Based on this, we recognize the joint prob-ability distribution of the observed profile as the likelihood function and utilize a fast Fourier transform-based procedure to estimate the pulse phase. Computational complexity of the proposed estimator is analyzed as well. Experimental results show that the proposed estimator significantly outperforms the currently used cross-correlation (CC) and nonlinear least squares (NLS) estima-tors, while significantly reduces the computational complexity compared with NLS and maximum likelihood (ML) estimators.     

XPNAV-1卫星实测数据处理与分析

为展示我国首颗脉冲星导航试验卫星XPNAV-1载荷实测数据的性能，采用与国外公布实测数据对比分析的方法，从观测数据计数统计、光子能量响应、计时性能三方面介绍了XPNAV-1卫星发布数据的性能。分析结果表明，我国自主研发的探测器观测结果与国外天文卫星载荷观测结果的一致性较好，未来进一步深入发展将有望应用于脉冲星导航。     

一种高精度的X射线脉冲星导航TOA估计方法

针对X射线脉冲星导航（XPNAV）系统的基本观测量--脉冲到达时间（TOA）的估计问题,提出一种高精度的TOA估计方法。该方法基于特征子空间分解类算法的高精度的参数估计特性,首先通过细致分析标准轮廓与折叠轮廓之间的互相关结果,构造新的观测方程;然后对该方程进行特征值分解得到两个相互正交的特征矢量;最后利用两个特征矢量之间的正交性完成TOA估计。数值仿真结果有效校验了算法的性能。