Advanced Optical Sensing for Aerospace Guidance, Navigation and Control

用于航空航天制导、导航和控制的先进光学传感

• 批准号: RGPIN-2022-03815
• 负责人: Enright, John
• 金额: $ 1.97万
• 依托单位: Ryerson University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=743239
• 关键词: Advanced; Optical; Sensing; Aerospace; Guidance

Aerospace vehicles frequently rely on optical sensors to determine system state. These instruments provide the direct external measurements necessary for a range of autonomous competencies. Attitude estimation, orbit determination, geolocation, relative maneuvering and obstacle avoidance all improve as their underlying sensing capabilities improve. This proposal examines how recent advances in the design of optical sensors can be leveraged to dramatically improve capabilities for guidance, navigation and control (GNC). A number of emerging optical technologies hold significant promise for high performance aerospace GNC applications. Plenoptic cameras, multispectral sensors, high-frame-rate imaging, and machine learning have seen significant innovation over recent years. Evaluated for their potential application in four key areas - i.e., spacecraft GNC, mobile robotics, adverse imaging, and calibration and production - these technologies will enable new types of missions for both planetary rovers and orbiting spacecraft. Technological innovations benefit GNC sensors in several ways. Improving measurement accuracy and reducing noise and bias are obvious pathways to enhanced performance. However, other high level metrics can be just as important. Higher sensor update rates provide a more complete description of vehicle motion. Improving sensor availability, i.e., the tolerance to adverse circumstances such as motion, noise, lighting, etc., can increase system robustness and the quality of the derived navigation solution. These three performance metrics will define the framework used in this research program for evaluating new technologies. Although seemingly disparate, the technologies highlighted in this proposal illustrate how advances in camera design and image processing can greatly enhance the performance of the optical sensors found on many aerospace vehicles. These innovations, driven by terrestrial machine vision applications, are nonetheless powerful enablers of the technical capabilities currently the focus of aerospace GNC research. As the capabilities of these systems grow the larger benefits to society, from industrial automation to natural resources management, are vast and growing.

航空航天车经常依靠光传感器来确定系统状态。这些工具提供了一系列自主能力所需的直接外部测量。态度估计，轨道确定，地理位置，相对操纵和避免障碍物都会随着其潜在的感应能力的改善而有所改善。该建议研究了如何利用光学传感器设计的最新进展，以显着提高指导，导航和控制（GNC）的能力。许多新兴的光学技术对高性能航空GNC应用具有巨大的希望。近年来，元素摄像机，多光谱传感器，高率速率成像和机器学习已有大量创新。这些技术评估了它们在四个关键领域的潜在应用 - 即航天器GNC，移动机器人技术，不良成像以及校准和生产 - 这些技术将为行星流浪者和轨道飞船提供新型的任务。技术创新通过多种方式使GNC传感器受益。提高测量精度并降低噪声和偏差是提高性能的明显途径。但是，其他高级指标也可能同样重要。更高的传感器更新率提供了对车辆运动的更完整描述。提高传感器的可用性，即对不利环境（例如运动，噪声，照明等）的容忍度可以提高系统的鲁棒性和派生导航解决方案的质量。这三个性能指标将定义该研究计划中用于评估新技术的框架。 尽管看似截然不同，但该提案中强调的技术说明了相机设计和图像处理的进步如何极大地增强许多航空航天车上的光学传感器的性能。这些创新是由地面机器视觉应用驱动的，但是目前是航空航天GNC研究重点的技术能力的强大推动力。随着这些系统的能力增长，从工业自动化到自然资源管理，对社会的益处更大，而且越来越大。