by Simon Mansfield
Sydney, Australia (SPX) Mar 11, 2024
Researchers at the Beijing Institute of Technology have made significant strides in tracking non-cooperative space targets through maneuvering, unveiling a novel methodology that substantially boosts tracking accuracy. Their study, focusing on maneuvering trajectories, introduces a dual-model approach for real-time and precise tracking, marking a leap in space surveillance capabilities.
The study initially presents two foundational models for capturing the intricate movements of space targets: the relative dynamics model and the indirect measurement model. The former tackles the challenge of maneuvering trajectory tracking by dissecting short time intervals, while the latter converts radar measurements into the Local Vertical Local Horizontal (LVLH) system for immediate applicability.
Addressing the complexity and high-frequency observations inherent in space target tracking, the researchers propose a groundbreaking real-time method predicated on swiftly estimating maneuver parameters. By analyzing high-frequency data points, the algorithm successfully predicts the target's future position, utilizing a combination of historical data and current maneuver estimates to refine accuracy.
The research team also introduces a novel filtering approach to counteract the influence of historical measurement inaccuracies on acceleration identification. A mean filtering technique smooths past data, enhancing the precision of maneuver parameter estimation. This method incorporates a shooting method for parameter estimation, ensuring a balanced spread within acceleration constraints, which is critical for accurate tracking.
An advanced differential algebra technique is employed to reduce the computational load, enabling the efficient handling of real-time data. This approach is complemented by the Jet Transport algorithm, which facilitates rapid numerical calculations for the real-time tracking of non-cooperative space targets.
Comparative simulations with the interactive multimodel (IMM) method revealed the new algorithm's superiority in tracking accuracy. The results demonstrated significant improvements in the Root Mean Square Error (RMSE) of position estimates across all directions, confirming the method's enhanced performance over traditional IMM approaches.
In conclusion, this study not only advances the field of space target tracking with its innovative maneuver parameter estimation method and trajectory prediction capabilities but also sets a new benchmark in tracking accuracy, promising substantial improvements for real-time space surveillance applications.
Research Report:Space Noncooperative Target Trajectory Tracking Based on Maneuvering Parameter Estimation
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