Exoplanets can be detected with various observational techniques. Among them, radial velocity (RV) has the key advantages of revealing the architecture of planetary systems and measuring planetary mass and orbital eccentricities. RV observations are poised to play a key role in the detection and characterization of Earth twins. However, the detection of such small planets is not yet possible due to very complex, temporally correlated instrumental and astrophysical stochastic signals. Furthermore, exploring the large parameter space of RV models exhaustively and efficiently presents difficulties. In this review, we frame RV data analysis as a problem of detection and parameter estimation in unevenly sampled, multivariate time series. The objective of this review is two-fold: to introduce the motivation, methodological challenges, and numerical challenges of RV data analysis to nonspecialists, and to unify the existing advanced approaches in order to identify areas for improvement.

翻译：系外行星可通过多种观测技术进行探测。其中，径向速度法具有揭示行星系统结构、测量行星质量与轨道偏心率的独特优势。径向速度观测在探测和表征类地行星方面将发挥关键作用。然而，由于存在高度复杂且具有时间相关性的仪器与天体物理随机信号，目前尚无法实现对此类小型行星的探测。此外，对径向速度模型庞大参数空间进行穷举且高效的探索亦存在困难。本综述将径向速度数据分析问题重新定义为非均匀采样多变量时间序列中的检测与参数估计问题。本文目标有二：其一，向非专业人士介绍径向速度数据分析的研究动机、方法论挑战及数值计算难点；其二，整合现有先进方法以识别有待改进的领域。