基于预报误差分布拟合的卫星历史机动检测方法

轨道机动会引起在轨卫星的轨道异常，是空间态势感知的重点关注对象之一。为此，提出一种从卫星的两行轨道要素编目数据中检测历史机动的方法。通过分析预报误差检测轨道参数的异常编目值，进而获得相应的历史机动信息。对卫星的两行轨道要素编目数据两两预报求差得到预报误差的样本数据后，利用期望最大化算法可以拟合得到以高斯混合模型表达的预报误差的概率分布模型；以此为基础，可以确定利用预报误差检测轨道参数异常编目值的门限；利用轨道机动与异常编目值之间的对应关系，最终实现机动检测。对典型活动卫星的机动检测结果表明，所提方法能够在准确检出历史机动事件的同时保持较低的误检率。

Method to Detect Satellite Orbit Maneuver Based on Fitting of Prediction error Distribution

Orbit maneuvers can cause satellite orbital anomalies and are one of the key concerns of the space situational awareness. This paper presents a method of detecting historical orbital maneuvers from satellite TLE data. By analyzing the prediction errors, abnormal cataloging values of the selected orbital parameter are detected, and corresponding historical maneuvering information is obtained. First, a large number of sample data of prediction error are obtained from the historical TLE data, and the probability distribution model of the prediction error expressed by the Gaussian mixture model is fitted from these sample data by the EM algorithm. Then, based on the fitted distribution model, the threshold of the prediction error that is used to detect outliers of the orbital parameter is determined, so as to establish the detection method of the orbital parameter outlier. Finally, taking into account the noise interference and the relationship between orbital maneuvers and abnormal cataloging values of the orbital parameter, the method to detect orbital maneuver from the cataloging sequence of the orbital parameter is determined. The maneuver detection results on typical active satellites show that the proposed method can detect historical maneuvers accurately while maintaining a low false detection rate.