A real-time maneuver detection method for low data rate

The real-time detection of maneuvering space objects is crucial for maintaining Space Situational Awareness (SSA). However, timely detection of a space object’s maneuver while simultaneously avoiding false alarms is challenging under low data rate conditions, as real-time denoising becomes particularly difficult in such cases. To this end, we propose a real-time maneuver detection method based on the maneuver detection parameter for low data rate conditions. Specifically, we first propose a novel Wavelet Transform Combined with Propagation (WTCP) method to process the time series data to better eliminate noise, in which the propagation process is introduced to extend the data boundaries to improve the real-time capability of the Wavelet Transform (WT). To further distinguish maneuver from noise, we then apply the coefficient of variation to construct the comprehensive criterion by fusing the semi-major axis and orbital inclination. After that, the comprehensive criterion is mapped to the $\left(0,1\right)$ interval through a well-designed threshold function to finally obtain the maneuver detection parameter, which can clearly characterize the probability of a maneuver. Furthermore, we introduced a reconfirmation strategy, ensuring that all detection results are reconfirmed and false alarms are corrected promptly in near real-time. The simulation results show that the proposed method can detect the maneuver rapidly while maintaining a low false alarm rate under low data rate conditions. Compared with the Weighted Moving Average Filter (WMAF), the WTCP performs better in extracting the maneuver from noise.