SBIR Phase I: Software-Defined Sub-Terahertz Imaging Radar for Algorithmic Agility and All-Weather Transportation Safety

小型企业创新研究(SBIR)第一阶段项目的更广泛/商业影响是开发一种通用、负担得起的可持续传感解决方案，以确保在任何天气条件下的周边安全和交通安全。目前可用的传感解决方案基于单一模式，部署成本很高，而且对不利天气条件的适应性不强。目前的解决方案还使用专有的传感器处理接口，无法通过持续学习提供决策所需的数据质量，难以升级，并且尺寸、重量和功率规格较差。相比之下，建议的技术利用单一、融合、开放的计算平台上的多种传感模式的优势，在恶劣天气条件下实现强大的感知，同时提供显著的总拥有成本优势。该技术在汽车、机器人、企业、航空航天和国防等领域有着广泛的应用。根据该项目开发的解决方案有可能通过以下方式拯救生命：减少道路事故数量，改善驾驶员反应时间，保护行人和骑自行车等易受伤害的道路使用者，减少航运公司的停机时间，最大限度地减少与碰撞索赔和维修相关的成本，以及检测、分类、警报和跟踪地面和空中的威胁。这个小型企业创新研究第一阶段项目开发了一个新颖的、可扩展的集中式传感平台和一个多光谱传感器原型，以使用商用的现成处理元件在距离、多普勒、方位和仰角领域实现超精细分辨率。先进的压缩算法用于通过安全、开放、低成本和低延迟的接口将传感器测量传输到中央处理单元，以实现多模式传感器处理、早期传感器融合和用于更高级别决策的高维感知。去耦合的传感和处理架构产生了前所未有的对测量级别数据的访问，以实现基于人工智能和机器学习的算法发现。采用受虚警约束的全局目标检测算法来实现定位、导航和测绘，以便在恶劣天气条件下运行。通过实验室和现场实验，开发了概念验证传感器硬件，以验证体系结构、技术、算法和软件。本提案中涉及的一些关键技术风险包括毫米频率及以上频率的天线设计和制造、多个射频收发器的级联以实现大量空间通道以及传感器之间的硬件级同步。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase I project is the development of a universal, affordable, and sustainable sensing solution to enable perimeter security and transportation safety under all weather conditions. Current sensing solutions available today are based on a single modality, expensive to deploy, and not robust to adverse weather conditions. Current solutions also employ proprietary sensor processing interfaces, do not provide the quality of data needed for decision-making by continuous learning, are hard to upgrade, and have poor size, weight, and power specifications. In contrast, the proposed technology leverages the strengths of multiple sensing modalities on a single, converged, open compute platform to enable robust perception in adverse weather conditions while offering significant advantages to the total cost of ownership. The technology has a wide range of applications in sectors as diverse as automotive, robotics, enterprise, aerospace, and defense. The solution developed under this project has the potential to save lives by reducing the number of road accidents, improving the driver reaction time, protecting vulnerable road users such as pedestrians and bicyclists, reducing the downtime for a shipping company, minimizing the costs associated with collision claims and repairs, and detecting, classifying, alerting, and tracking threats on the ground and in the air. This Small Business Innovation Research Phase I project develops a novel, scalable, centralized sensing platform and a multi-spectral sensor prototype to realize ultra-fine resolution in range, Doppler, azimuth, and elevation domains using commercial, off-the-shelf processing elements. Advanced compression algorithms are employed to transport sensor measurements over secure, open, low-cost, and low-latency interfaces to the centralized processing unit to enable multi-modal sensor processing, early sensor fusion, and high-dimensional perception for higher-level decision-making. The de-coupled sensing and processing architecture produces unprecedented access to measurement-level data to enable artificial intelligence and machine learning-based algorithmic discovery. False-alarm-constrained global object detection algorithms are employed to enable localization, navigation, and mapping for operation under adverse weather conditions. Proof-of-concept sensor hardware is developed with laboratory and field experiments to validate the architecture, technology, algorithms, and software. Some of the key technology risks addressed in this proposal are antenna design and fabrication at millimeter frequencies and above, cascading of multiple radio frequency transceivers to realize a large number of spatial channels, and hardware-level synchronization across the sensors.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.