Skip to content

论文arXiv 2610.0932321 天前

星座任务规划中面向数据稀缺轨道 Monte Carlo 的约束扩散 ​

原文链接:Constrained Diffusion for Data-Scarce Orbital Monte Carlo in Constellation Tasking(arXiv 2610.09323 · 发布日期:2026-10-07)

Constrained Diffusion for Data-Scarce Orbital Monte Carlo in Constellation Tasking

该文针对参考轨迹稀缺下星座任务策略评估的轨道群体增强,采用力条件约束扩散并在传播样本和 GoDSAT 兼容活动中验证。

核心要点 ​

  • 参考轨迹稀缺时,重放缺少几何多样性,轨道元素抖动可能违背物理约束。
  • 力条件扩散学习13维轨道先验,并由近地点高度和偏心率恢复半长轴。
  • 用800条参考轨迹比较多种生成器,评估分布保真、支持偏移和天体力学诊断。
  • 扩散支持局部、支持内增强,但不能替代轨道动力学或作为运行后验。

验证范围与局限:验证范围包括 Basilisk 五级力模型传播、4000个配对 GoDSAT 兼容活动和固定16卫星配置。

英文摘要 (Abstract) ​

Constellation Monte Carlo results depend on the orbital population used to evaluate a tasking policy. With scarce reference trajectories, replay limits geometric diversity, while independent orbital-element jitter can violate physical constraints. We study constrained diffusion for orbital-population augmentation. A force-conditioned diffusion model learns a 13-dimensional orbital prior, recovering semimajor axis from perigee altitude and eccentricity; Basilisk propagates each sample under one of five force-model tiers. Using 800 reference trajectories, we compare diffusion with jittered bootstrap, per-tier Gaussian mixtures, and a conditional variational autoencoder, and evaluate distributional fidelity, support shift, classical astrodynamics diagnostics, and 4,000 paired GoDSAT-compatible campaigns. The largest diffusion model achieves held-out trajectory MMD of 0.0171 +/- 0.0239, similar to bootstrap (0.0170) and the mixture (0.0198), but samples farther from training priors (median nearest-training distance 2.7 versus 0.10 standardized units). All generators fail to match the shifted-blind population (classifier AUC 0.991-0.998). Endpoint-conditioned samples satisfy Lambert boundaries but have greater interior error than the matched Lambert reference (29.2 versus 5.7 km mean RMSE). Residual diffusion improves selected sparse forecasts and catalog-mode recall but does not outperform classical estimators on custody ranking. In a fixed 16-satellite configuration, diffusion yields similar mean custody to replay and bootstrap, while the force-tier mixture shifts custody by about 5.5 percentage points. Constrained diffusion supports local, in-support augmentation but cannot replace orbital dynamics or serve as an operational posterior. Orbital-population construction is a consequential source of uncertainty in constellation analysis.

作者:Omar Ramadan, Sam Siavoshian, Amir K. Saeed, Benjamin Johnson, A.M.E.-A. Diab, Benjamin M. Rodriguez

来源

本页事实对应的公开页面,以原文为准。

  1. arXiv 2610.09323:Constrained Diffusion for Data-Scarce Orbital Monte Carlo in Constellation Tasking访问 2026-10-21