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

这个小型企业创新研究（SBIR）第一阶段项目的更广泛/商业影响是开发一种通用的，负担得起的和可持续的传感解决方案，以实现在所有天气条件下的周边安全和运输安全。目前可用的传感解决方案基于单一模态，部署成本高，并且对恶劣天气条件不稳定。 目前的解决方案还采用专有的传感器处理接口，不提供通过持续学习进行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，所提出的技术利用了单一、融合、开放式计算平台上多种传感模式的优势，在恶劣天气条件下实现强大的感知，同时为总拥有成本提供显著优势。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。该项目下开发的解决方案有可能通过减少道路事故数量、改善驾驶员反应时间、保护行人和骑自行车者等弱势道路使用者、减少航运公司的停机时间、最大限度地降低碰撞索赔和维修相关成本以及检测、分类、警报和跟踪地面和空中威胁来挽救生命。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，集中式传感平台和多光谱传感器原型，以实现超精细分辨率的范围，多普勒，方位角和仰角域使用商业，现成的处理元件。采用先进的压缩算法，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，以实现多模态传感器处理、早期传感器融合和高维感知，从而实现更高级别的决策。解耦的传感和处理架构产生了对测量级数据的前所未有的访问，以实现基于人工智能和机器学习的算法发现。假警报约束的全球目标检测算法，使定位，导航和映射的操作在恶劣的天气条件下。通过实验室和现场实验开发概念验证传感器硬件，以验证架构，技术，算法和软件。该提案中涉及的一些关键技术风险是毫米频率及以上的天线设计和制造，多个射频收发器的级联以实现大量空间信道，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价值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.