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.

航天飞行器经常依靠光学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。姿态估计、轨道确定、地理定位、相对机动和避障都随着潜在传感能力的提高而提高。这项提案研究了如何利用光学传感器设计的最新进展来显著提高制导、导航和控制(GNC)的能力。许多新兴的光学技术为高性能航空航天GNC应用带来了巨大的希望。近年来，全光学相机、多光谱传感器、高帧频成像和机器学习都有了重大创新。对它们在四个关键领域的潜在应用进行了评估--即航天器GNC、移动机器人、逆向成像以及校准和生产--这些技术将使行星漫游车和轨道航天器的新型飞行任务成为可能。技术创新在几个方面使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提供了对车辆运动的更完整的描述。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，可以增加系统的健壮性和导出导航解决方案的质量。这三个性能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，但本提案中强调的技术表明，相机设计和图像处理方面的进步可以极大地提高许多航空航天器上的光学传感器的性能。在地面机器视觉应用的推动下，这些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。随着这些系统能力的增长，从工业自动化到自然资源管理，给社会带来的更大好处是巨大的，而且还在不断增长。