Abstract: 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. 

Key words: orbit maneuver, space target, Neyman-Pearson criterion, false alarm probability, detection probability