Advanced Optical Sensing for Aerospace Guidance, Navigation and Control

航空航天器经常依赖于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其基本传感能力的提高而提高。该提案研究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，全光相机、多光谱传感器、高帧率成像和机器学习都出现了重大创新。评估了它们在四个关键领域的潜在应用，即，航天器GNC、移动的机器人、逆向成像、校准和生产--这些技术将使行星漫游者和轨道航天器都能执行新型任务。技术创新在几个方面使GNC传感器受益。提高测量精度、降低噪声和偏差是增强性能的明显途径。然而，其他高级别指标可能同样重要。更高的传感器更新速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、噪音、照明等不利环境的耐受性，可以增加系统鲁棒性和导出的导航解的质量。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。 虽然看似不同，但本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大大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力。随着这些系统能力的增长，从工业自动化到自然资源管理，对社会的更大好处是巨大的，而且还在增长。

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.