从动力学观测反演小行星阿波菲斯内部质量分布参数的框架
Inversion Framework of Internal Mass Distribution Parameters of Asteroid Apophis from Dynamical Observations
AI总结：
本研究提出一种基于粒子群优化的反演框架，利用阿波菲斯近距离飞掠的动力学观测数据反演其内部质量分布，经验证可高精度区分不同内部结构，为小行星探测观测提供指导。
AI中文摘要：
探测小行星的内部质量分布对于理解其起源、演化以及制定探测任务规划具有重要意义。此前的方法依赖间接的密度估计或近距离航天器重力反演，适用范围有限。本文提出一个概念验证框架，用于在2029年小行星(99942)阿波菲斯（Apophis）近距离飞掠地球期间，利用飞掠过程中收集的动力学观测数据反演其内部质量属性。我们建立了从轨道和旋转状态演化到内部结构参数的动力学映射，将其表述为一个反问题，并使用粒子群优化（Particle Swarm Optimization）算法求解。该算法首先在规则椭球模型上进行验证，随后应用于基于阿波菲斯实际形状构建的三种质量分布模型。在理想观测条件下，反演得到的转动惯量比的相对误差可低于0.001%，质心位置的绝对误差达到10^-5米量级，该算法能够成功区分不同的内部结构。当引入实际测量噪声时，反演精度会下降。敏感性分析表明，转动惯量张量反演的精度主要受限于角速度测量噪声，而质心确定对位置和速度数据的精度高度敏感。本研究为在近距离飞掠期间反演小行星内部结构提供了一种技术上可行且成本效益高的方法的概念验证，同时强调了实际应用对数据精度的关键要求，为未来的观测活动提供了指导。
英文摘要：
The detection of the internal mass distribution of asteroids is of great significance for understanding their origin, evolution, and mission planning for exploration. Previous approaches rely on indirect density estimates or close-range spacecraft gravity inversion, which have limited applicability. This paper presents a proof-of-concept framework to infer the internal mass properties of asteroid (99942) Apophis during its close Earth flyby in 2029 using dynamical observations collected during the encounter. We establish a dynamical mapping from the evolution of orbital and rotational states to internal structural parameters, formulate it as an inverse problem, and solve it using Particle Swarm Optimization. The algorithm is first validated on a regular ellipsoidal model and then applied to three mass distribution models based on the actual shape of Apophis. Under ideal observation conditions, the relative error of the inverted moment of inertia ratios can be below 0.001%, and the absolute error of the center-of-mass position reaches the order of 10-5 meters. The algorithm successfully distinguishes among different internal structures. When realistic measurement noise is introduced, the inversion accuracy degrades. A sensitivity analysis reveals that the accuracy of the inertia tensor inversion is primarily limited by angular velocity measurement noise, whereas center-of-mass determination is highly sensitive to the precision of position and velocity data. This study provides a proof-of-concept for a technically feasible and cost-effective approach to infer asteroid internal structure during close encounters, and also highlights the critical data accuracy requirements for practical application, offering guidance for future observation campaigns.
