为解决传统的旋转卫星激光测距数据频谱分析方法运算量大、耗时长的问题，提出一种基于快速Lomb-Scargle算法的卫星激光测距数据处理方法。首先用经验模式分解方法来自适应地去除O-C残差中代表卫星轨道运动的低频趋势项；然后采用快速Lomb-Scargle算法对预处理后的数据进行频谱分析，得到相对应的周期图，进而分析卫星的自转速率。采用该方法处理了奥地利Graz站千赫兹测距系统测量得到的Ajisai卫星的数据，分析得出2010年5月Ajisai卫星自转的速率约为0.472 Hz。并对4圈激光测距资料进行处理，结果表明，该方法可以将频谱分析运算量降低两个数量级，节省大量处理时间，为快速高效地处理大量的旋转卫星激光测量数据提供了新思路。

The traditional spectral analysis methods of processing spinning satellites laser ranging data have the disadvantages of large computational cost and long processing time. A new satellites laser ranging (SLR) data processing algorithm based on fast Lomb-Scargle algorithm is proposed to solve these problems. Firstly, empirical mode decomposition method is used to adaptively remove the low frequency trend term in the O-C residuals of SLR data, which represents the satellite orbital motion. The preprocessed SLR data is then processed for spectral analysis with fast Lomb-Scargle algorithm to get its periodogram and thus analyze the spinning rate of satellites. Processing the kilohertz SLR data of satellite Ajisai from Graz station of Austria, we can get that the spinning rate of satellite Ajisai during May 2010 is about 0.472 Hz. Further data processing of four passes also have been done by proposed fast algorithm. Results show that the computational cost of spectral analysis is reduced by roughly two orders of magnitude and the processing time is greatly saved by using the fast algorithm. It provides a new way to process large amount of SLR data of spinning satellite fast and efficiently.