太阳是太阳系中唯一的能量源, 拥有着极为宽阔的连续谱以及数以万计的吸收线和发射线, 是一个非常丰富的光谱信息宝藏。 太阳电磁辐射的能量主要集中在可见光区和红外光区, 其中, 具有多普勒红移特征的太阳红外光谱可作为天文测速导航的信息源。 太阳光谱多普勒红移测速是天文测速导航的重要环节, 它通过计算接收太阳光谱相对于标准太阳光谱的多普勒红移反推出航天器和太阳之间的相对径向速度。 然而, 太阳黑子、 日冕、 耀斑等太阳活动引发的光谱畸变会造成太阳光谱的不稳定, 这将影响着太阳光谱的测速精度, 进而影响导航精度。 为了提高太阳光谱测速导航性能, 依据太阳光谱测速原理, 探索改进太阳光谱多普勒红移测速的信号处理方法。 提出了一种面向太阳光谱测速导航的自适应 EMD-NDFT多普勒红移测速方法, 该方法针对太阳光谱的多普勒效应计算得到红移, 进而反推得到航天器相对于光源的径向速度。 该方法由EMD处理、 NDFT变换、 相关匹配三部分构成。 即： 首先运用EMD算法对非平稳的接收太阳光谱信号进行自适应分层, 再根据每一层本征模态信号进行自适应阈值滤波降噪, 以获得平稳的重构信号; 然后根据太阳光谱非均匀采样的特点, 对标准太阳光谱和接收光谱分别进行NDFT变换将光谱由时域转换到频域, 再选择两者的低频特征谱线进行泰勒匹配以获得相位差, 从而得到航天器相对于太阳的径向速度。 该方法将信号的时域降噪和频域稀疏相结合, 可更快速、 更准确地得到径向速度。 分析了太阳黑子活动的一个周期中, 不同年份的光谱变化情况, 并分别对其进行多普勒红移测速计算和分析。 仿真实验结果表明, 针对不同时间段和不同噪声下的太阳光谱数据, 采用自适应EMD-NDFT方法可以有效提高测速精度, 并能较大程度地降低计算复杂度。

As the only energy source in the solar system, the sun is a rich treasure of spectral information for having a very wide continuous spectrum and tens of thousands of absorption and emission lines. The energy of solar electromagnetic radiation is mainly concentrated in the visible and infrared regions, among which the solar infrared spectrum with Doppler redshift characteristics can be used as the information source for astronomical velocity measurement and navigation. As an important part of astronomical velocity measurement navigation, Solar spectral Doppler redshift velocity measurement can deduce the relative radial velocity between spacecraft and the sun by calculating the Doppler redshift of the received solar spectrum relative to the standard solar spectrum. However, the spectral distortion caused by such solar activities as sunspots, corona, or flares will lead to the instability of the solar spectrum, which will affect the velocity measurement accuracy of the solar spectrum and in turn, the navigation accuracy. In order to improve the navigation performance of solar spectral velocity measurement, based on the principle of solar spectral velocity measurement, the signal processing method of solar spectral Doppler redshift velocity measurement is explored in this paper. This paper proposes an adaptive EMD-NDFT Doppler redshift velocity measurement method for solar spectral velocity measurement navigation. By this method, the redshift is calculated according to the Doppler effect of the solar spectrum and the radial velocity of the spacecraft relative to the light source is derived. The method consists of EMD processing, NDFT and correlation matching. First, the non-stationary received solar spectral signals are stratified adaptively by using the EMD algorithm, and the adaptive threshold filtering and noise reduction are carried out according to each layer of intrinsic mode signal to obtain a stable reconstructed signal. Second, according to the characteristics of non-uniform sampling of the solar spectrum, the standard solar spectrum and the received spectrum respectively are transformed by NDFT to convert the spectrum from the time domain to the frequency domain. Thirdly, Taylor matching is performed on the low-frequency characteristic spectral lines of the two spectra and the phase difference to obtain the radial velocity of spacecraft relative to the Sun. This method combines time-domain denoising and frequency-domain sparsity to obtain radial velocity more quickly and accurately. This paper analyses the spectral changes of sunspot activity in different years within a cycle, and their doppler redshift velocities are calculated and analyzed. The simulation results show that the adaptive EMD-NDFT method can effectively improve the accuracy of velocity measurement and greatly reduce the computational complexity for the solar spectral data in different periods and under different noises.