天基监测空间目标被动跟踪定轨技术研究

Space target surveillance is the basis of space situational awareness, spacecraft collision warning. Space-based space target surveillance is an important developing direction of the future space technology.The space target tracking using angle measurements based on autonomous orbit determination is treated as a scientific problem in this project. Firstly, the new observability analysis methods of space target tracking based on using angle measurement directly and noisy measurement error are presented separately. Secondly, through analyzing the autonomous orbit determination information fusion method using multiple sensors based on space-based platform, a new distributed kinematic and static federated filter is designed to realize the autonomous orbit determination of space-based platform, which has the ability of fault detection and isolation. Once again, the space target passive tracking model is established using intermittent measurement. The sparse grid quadrature filter, robust estimation and particle filter are incorporated to design a new adaptive tracking algorithm using intermittent measurement. Finally, the ground hardware-in-loop simulation system of space target tracking and orbit determination is designed, and the feasibility and effectiveness of the algorithms presented in this project are validated. We want to provide ideas and new technical methods for space-based target surveillance under the complicated space environment through this project.

空间目标监测是空间态势感知、航天器碰撞预警的基础，天基空间目标监测是未来空间技术的重要发展方向。本项目以自主定轨天基平台被动跟踪空间目标为科学问题，首先对基于角度量测的空间目标被动跟踪系统的可观测性进行分析，分别给出直接基于角度量测和量测误差下的空间目标可观测性分析新方法；其次，通过基于多敏感器的天基平台自主定轨信息融合方法进行研究，设计具有故障检测和隔离能力的天基平台自主定轨动静态联邦滤波器；再次，通过建立量测数据部分丢失下空间目标被动跟踪模型，结合稀疏网格积分滤波、抗差估计和粒子滤波的优点，提出不完全测量下自适应跟踪定轨滤波算法。最后，研制空间目标跟踪定轨地面半物理仿真实验系统，验证方法的有效性和可行性。通过本项目的研究，期望为复杂空间环境下天基目标监视技术提供新的思路和技术途径。

本项目以自主定轨天基平台被动跟踪空间目标为科学问题，对天基监测空间目标被动跟踪定轨中的若干关键问题进行了深入研究。项目取得研究成果包括：（1）针对天基平台快速轨道机动过程中，定轨精度下降和测量传感器故障问题，设计了具有故障检测和隔离能力的GNSS/XNAV组合导航技术，为天基平台自主定轨的高精度高可靠性工作提供了保障；（2）针对基于天基定向测量数据的空间非合作机动目标跟踪中系统噪声强度的不确定性和量测数据丢失的问题，分别提出了模糊迭代均方根容积卡尔曼滤波算法和基于鲁棒自适应因子的非线性跟踪方法，极大程度上提升了在轨道跟踪的精度；（3）针对多目标跟踪中所存在的目标数目未知和杂波干扰等一系列问题，提出了鲁棒解耦无偏转换自适应门限的CPHD和IMM结合的跟踪方法，有效地实现了复杂环境下多机动目标的可靠跟踪；（4）针对粒子滤波存在的权值退化问题，提出了基于萤火虫优化和蝙蝠优化的粒子滤波方法，有效地解决了粒子的贫化现象，提高了滤波算法的精度和实时性。项目研究达到了预期的目标，取得了多个有创新性的成果，为天基监测空间目标被动跟踪定轨中相关问题的解决提供了理论基础和技术支撑。