基于Neyman-Pearson准则的空间目标轨道机动检测方法

轨道机动检测是当前空间监视活动的重要需求之一。当卫星在脉冲小推力作用下发生轨道机动时，会引起目标卫星与伴飞卫星相对距离变化率的阶跃突变，由于测量噪声的存在，距离变化率的阶跃突变特征被淹没在测量噪声中，不容易被检测出来。针对该问题，提出了一种基于概率判决模型的轨道机动检测方法。该方法采用独立同分布高斯白噪声模型描述测量噪声，将距离变化率作为特征量用于变轨检测，把距离变化率的阶跃突变检测问题转化为概率判决问题，在虚警概率约束下，基于Neyman-Pearson准则求解序列数据的变轨判决门限，能够自适应地判断目标卫星是否发生轨道机动。通过不同幅度轨道机动下的仿真试验，验证了该方法的可行性与有效性。

Orbital maneuver detection method of space target based onNeyman-Pearson criterion#br#

Orbital maneuvering detection is one of the important demands of current space surveillance activities. When the orbit maneuver of the satellite occurs under the action of low thrust maneuvers, the step mutation feature appears in the relative distance change rate between the target satellite and the accompanying satellite. Because of the measurement noise, the step mutation feature of the distance change rate is submerged in the measurement noise and is difficult to be detected. An orbital maneuvering detection method based on probabilistic decision model was proposed in this paper. The measurement noise was modeled with an independent identical Gaussian white noise distribution. It took the distance change rate as the input data for orbit change detection. Consequently, the step mutation detection problem of the distance change rate was transformed into a probabilistic decision problem. The threshold of the decision based on Neyman-Pearson criterion was generated adaptively according to the false alarm probability constraint and the fluctuation characteristic of the input data. The feasibility and effectiveness of the proposed method were verified by simulation experiments under different parameters.