Advanced Optical Sensing for Aerospace Guidance, Navigation and Control

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底层感知能力的提高而提高。本提案探讨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。许多新兴光学技术对高性能航空航天GNC应用具有重要的前景。近年来，全光相机、多光谱传感器、高帧率成像和机器学习都取得了重大创新。评估了它们在四个关键领域的潜在应用-即航天器GNC，移动机器人，不利成像以及校准和生产-这些技术将使行星漫游者和轨道航天器的新型任务成为可能。技术创新在几个方面有利于GNC传感器。提高测量精度，降低噪声和偏置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更完整的车辆运动描述。提高传感器的可用性，即对运动、噪声、光照等不利环境的容忍度，可以提高系统的鲁棒性和衍生导航解决方案的质量。这三个性能指标将定义本研究项目中用于评估新技术的框架。虽然看起来完全不同，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提高了许多航空航天飞行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，给社会带来的更大利益是巨大的，而且还在不断增长。

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.