# 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：https://robotics.hellobike.com/papers/2026-10-07-2610-09323
> 频道：papers | 更新日期：2026-10-07 | 标签：arxiv, cs.RO
> 核心摘要：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。

# 星座任务规划中面向数据稀缺轨道 Monte Carlo 的约束扩散

::: v-pre
> 原文链接：[Constrained Diffusion for Data-Scarce Orbital Monte Carlo in Constellation Tasking](https://arxiv.org/abs/2610.09323)（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
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## 原始参考来源 (Sources)

- [arXiv 2610.09323：Constrained Diffusion for Data-Scarce Orbital Monte Carlo in Constellation Tasking](https://arxiv.org/abs/2610.09323)