高空平台组合成像与振动抑制的实验验证
Experimental Validation of Combined Imaging and Vibration Mitigation for High-Altitude Platforms
- HUN-REN SZTAKI（匈牙利科学院研究网络系统与技术知识研究所）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
针对高空伪卫星轻量化结构易受低频振动影响的问题，提出结合分布式相机网络、超分辨率图像处理与H∞主动振动控制的方案，实验验证显著提升图像质量。
AI中文摘要：
对连续、高分辨率航空监测的需求正推动对高空伪卫星（HAPS）的兴趣，与卫星相比，高空伪卫星提供了一种更具成本效益且更灵活的替代方案。虽然高空伪卫星平台提供了宝贵的地球观测潜力，但鉴于其轻量化结构，选择光学传感器需要在分辨率和有效载荷限制之间进行权衡。我们提出了一种多学科概念，利用商用、重量高效的分布式相机网络，结合先进的图像处理和主动振动控制，来增强高空伪卫星的地球观测能力。引入了一种超分辨率流程，其中来自各个相机的图像经过预处理后输入超分辨率算法。高空伪卫星平台的低结构刚度增加了其对低频振动的敏感性，必须通过主动控制来抑制这些振动，以保持成像性能。设计了一个标称H∞混合灵敏度控制器，以抑制相机位置处的共振峰。该方法在专为实时测试设计的简化机翼平台上进行了实验验证。基于九个指标的定量评估显示了显著的图像质量提升，突出了H∞控制在抑制低频弹性模态和稳定平台以实现超分辨率方面的有效性。这些结果表明，轻量级商用传感器结合先进的图像处理和控制在未来高空伪卫星遥感任务中能够提供高质量成像。
英文摘要：
The demand for continuous, high-resolution aerial monitoring is driving interest in High- Altitude Pseudo-Satellites (HAPS), which offer a cost-effective alternative to satellites with greater flexibility. While HAPS platforms provide valuable Earth observation potential, se- lecting an optical sensor requires balancing resolution and payload constraints, given their lightweight structures. We propose a multidisciplinary concept to enhance the Earth obser- vation capabilities of HAPS using a commercially available, weight-efficient distributed camera network, combined with advanced image processing and active vibration control. A super- resolution pipeline is introduced, where images from individual cameras are preprocessed and fed into a super-resolution algorithm. The low structural rigidity of HAPS platforms increases their sensitivity to low-frequency vibrations, which must be mitigated through active control to preserve imaging performance. A nominal H-infinity mixed-sensitivity controller is designed to suppress resonance peaks at camera locations. The methodology is experimentally validated on a simplified wing platform designed for real-time testing. Quantitative evaluation based on nine metrics demonstrates significant image quality improvements, highlighting the effectiveness of H-infinity control in mitigating low-frequency elastic modes and stabilizing the platform for super- resolution. These results show that lightweight commercial sensors, combined with advanced image processing and control, can deliver high-quality imaging for future HAPS remote sensing missions.
