卫星微振动响应机理与振源定量识别方法研究

The micro-vibration of sensitive load area is a key factor which affects the performance of high precision satellite, such as the pointing precision and imaging resolution. Quantitative identification of the main vibration sources and contribution evaluation of the sources to the sensitive load area can provide the basis for the anti-vibration design of the satellite and the vibration suppression of the on-orbit satellite. The satellite source signals have the characteristics of many harmonics and strong overlapping, and there is few study on quantitative identification of vibration sources of on-orbit satellites both at home and abroad. Therefore this research project aims to seek improvements in the following aspects. Through the study on the non-linear characterization method of the micro-vibration transmission in aluminum honeycomb panel and joint surface, the dynamic model of the typical compartment structure of the satellite is constructed to reveal the mechanism of dynamic response and transmission characteristics of the micro-vibration. To realize the separation and extraction of overlapped harmonic source signals, the spatially constrained blind deconvolution algorithm with reference signal (SCBD-R) is built through exploring the influence of reference signal and transmission characteristics on the performance of the algorithm. Contribution evaluation method based on vector mapping is presented through exploring the superposition mechanism of the response signals and contribution representation method, to realize accurate contribution evaluation of vibration sources of the satellite. This research project is intend for providing the basic theory and key technology for the quantitative identification of the main vibration sources of satellites. This research project, focusing on the innovations of both academic research and engineering applications, is promising for the micro-vibration suppression of satellite sensitive load area and the improvement of the satellite performance, such as positioning accuracy and imaging resolution.

卫星敏感载荷区的微振动是制约卫星定位精度、分辨率等性能提高的关键因素。定量识别和评估主要振源及其对敏感载荷区的贡献量，可为卫星减振设计和在轨运行卫星的振动抑制提供基础和依据。针对卫星振源信号谐波多、交叠强的特点，以及目前国内外对在轨运行卫星多振源定量评估研究很少的不足，本项目研究微振动在铝蜂窝夹层板和结合面传递的非线性表征方法，构建卫星典型舱段结构的动力学模型，揭示微振动的动态响应机理和传递特性；研究基于空间约束的盲解卷积算法，探究源参考信号和结构传递特性对算法性能的影响机制，实现多源谐波交叠的振动源信号的分离和提取；研究基于向量映射的贡献量计算方法，探究源响应信号的叠加耦合机理和贡献量表征方法，实现卫星振动源贡献量的准确评估。本项目可为卫星主要振源的定量识别和评估提供基础理论和关键技术，对于卫星敏感载荷区微振动抑制，提高卫星定位精度、分辨率等性能，具有重要的学术意义和工程应用价值。

卫星敏感载荷区的微振动是制约卫星定位精度、分辨率等性能提高的一个关键因素。识别卫星各振源并评估其对敏感载荷区的贡献量，可为微振动抑制提供基础和依据，对提高卫星性能具有重要意义。本项目开展卫星微振动源定量识别的研究，主要研究内容和成果如下：. (1) 基于芯层等效法和虚拟材料法构建了卫星舱段结构有限元模型，采用舱段结构激励实验验证了模型有效性。利用模型仿真分析了舱段结构的模态、谐响应及瞬态响应，揭示了其动态响应机理和非线性传递特性，为卫星振源识别提供理论基础和先验信息。. (2) 针对卫星振源难以严格满足独立性条件的问题，提出了频域卷积有界成分分析算法，有效解决了卷积混合的相关源分离问题。研究提出了基于向量投影的相关源贡献量评价方法，建立振源定量识别方法，准确实现机械系统相关源的定量识别。. (3) 针对卫星振源信号谐波交叠特点，提出了参考稀疏盲解卷积算法，解决了卷积混合情况下谐波信号分离效果不佳的问题。研究提出频域稀疏贡献量计算方法，建立振源定量识别方法，实现谐波交叠振源对敏感载荷点贡献量的定量评估。. (4) 针对信道非线性特性引起信号非线性畸变的问题，研究提出基于谱稀疏化补偿的后非线性盲解卷积算法，可稳定高效地实现后非线性混合信号的分离。建立基于谱稀疏化补偿的振动源定量识别方法，为卫星地面接收信号的振源定量识别提供有效手段。. (5) 针对卫星在轨期间对振源实时定量识别的需求，提出了基于非线性相关性的步长自适应在线分离算法，提高了在线分离的速度和精度。提出了基于实时分离矩阵的贡献量在线评估方法，为振源的在线定量识别提供了有效方法。. 通过铝蜂窝板舱段结构激励实验验证了以上源识别方法的有效性。基于提出的定量识别方法开发了卫星振动源定量识别应用软件，将其应用于某桁架式结构星地面实验，源贡献误差小于8%，初步验证了其实用性。本项目研究成果为卫星微振动源信号的定量识别提供了基础理论和关键技术，具有重要学术意义和工程应用前景。