AI 中文总结
针对地月空间任务中不确定性传播难题，提出自适应多保真度不确定性传播方法，依位置动态调整扰动力，集成到多目标跟踪框架，降低计算成本，在模拟测试中验证其有效性，相比非自适应方法显著降低成本且精度相当或更高。
AI 中文摘要
随着地月空间任务数量的增加，该区域空间物体数量预计将增长，高效的不确定性传播对空间态势感知至关重要。但地月领域广阔、动力学环境混沌且测量有限，使这一过程复杂。本文提出一种自适应多保真度不确定性传播方法，根据地月空间位置动态调整扰动力，在保持建模精度的同时最小化计算时间。该方法被集成到多目标跟踪框架中，在不牺牲精度的情况下降低轨道预测计算成本。在与即将到来的地月任务和空间态势感知应用相关的模拟测试案例中证明了该方法的有效性，与非自适应方法相比，计算成本显著降低，同时精度相当或更高。
英文摘要
As the number of missions to cislunar space increases, the population of space objects in this region is expected to grow, making efficient uncertainty propagation essential for space situational awareness (SSA). This is complicated by the cislunar domain's vastness, chaotic dynamical environment, and limited availability of measurements. This paper presents an adaptive multi-fidelity uncertainty propagation method that dynamically adjusts the included perturbing forces based on position in cislunar space, minimizing computation time while maintaining a prescribed modeling accuracy. The proposed adaptive method is then integrated into a multi-target tracking framework to reduce the computational cost of track prediction without sacrificing accuracy, which is important for managing the growing number of objects in cislunar space. The effectiveness of the approach is demonstrated in simulated test cases relevant to upcoming cislunar missions and SSA applications, resulting in a significant reduction in computational cost compared to a non-adaptive approach while achieving equivalent or superior accuracy.
