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.

航空航天飞行器经常依靠光学传感器来确定系统状态。这些仪器提供一系列自主能力所需的直接外部测量。姿态估计、轨道确定、地理定位、相对机动和避障都会随着其基础传感能力的提高而得到改善。该提案探讨了如何利用光学传感器设计的最新进展来显着提高制导、导航和控制 (GNC) 的能力。许多新兴光学技术为高性能航空航天 GNC 应用带来了巨大前景。近年来，全光相机、多光谱传感器、高帧率成像和机器学习取得了重大创新。这些技术在四个关键领域（即航天器 GNC、移动机器人、逆向成像以及校准和生产）的潜在应用进行了评估，将为行星漫游者和轨道航天器执行新型任务提供支持。技术创新在多个方面使 GNC 传感器受益。提高测量精度、减少噪声和偏差是提高性能的明显途径。然而，其他高级指标也同样重要。更高的传感器更新率可以更完整地描述车辆运动。提高传感器的可用性，即对运动、噪声、照明等不利环境的容忍度，可以提高系统的稳健性和衍生导航解决方案的质量。这三个绩效指标将定义本研究计划中用于评估新技术的框架。 尽管看似不同，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能够极大地提高许多航空航天器上的光学传感器的性能。这些由地面机器视觉应用驱动的创新仍然是目前航空航天 GNC 研究重点的技术能力的强大推动者。随着这些系统功能的增强，从工业自动化到自然资源管理，社会所获得的利益将是巨大且不断增长的。