Reduction of Space Debris Collision Prediction Uncertainty Based on Q-Sat Precise Orbit

Abstract

Collision probability is employed for evaluating whether there will be a dangerous encounter between 2 space objects. The fidelity of the collision probability mainly depends on the accuracies of orbit prediction and covariance prediction for the space objects. In this paper, the collision probability between the Tsinghua Gravitation and Atmosphere Science Satellite, Q-Sat, and the space debris with a North American Aerospace Defense Command ID of 49863 on 2022 January 18 was calculated. The 2 objects approached each other dangerously close and the event was reported. First, the atmospheric density model is modified by a dynamic approach-based inversion to improve the accuracy of orbit prediction for the Q-Sat. Next, predictions of position error covariance are carried out. Orbits of the next 24 hours are predicted, and the predicted orbits are compared with the actual orbits of the Q-Sat. Backpropagation neural network was trained for predicting the position error covariance. For the space debris, the 2-line element data are employed. Orbit predictions for the space debris are also conducted and compared with the actual orbit. Another backpropagation neural network for predicting the position error covariance for the space debris is trained. Using the covariances from the backpropagation neural network, the error ellipsoids of the 2 objects are established. The error ellipsoids are later projected to the encounter plane to calculate the collision probability. Different from the reports from other institutes, the closest distance between the Q-Sat and the space debris calculated by the current method was 2.71 km. The collision probability was 1.16 × 10 −11 . It was not a dangerous encounter event. The onboard precise orbit determination device enabled improved orbit determination precision and orbit prediction accuracy, which is important for space safety management.

ACP-Based Space Systems: Design, Development, and Operation

“…Furthermore, using high-precision orbital data from the real Q-Sat system and TLE data from space debris, the position error covariance prediction BP neural network within the artificial systems is trained [43]. Taking the space debris with a NORAD ID of 49863 as an example, the trained prediction results are illustrated in Figure 10, along with the relationship between relative distance and collision probability, as shown in Figure 11.…”