SBIR Phase I: Non-Line of Sight Geolocation Using Massive MIMO Antenna Arrays

SBIR 第一阶段：使用大规模 MIMO 天线阵列的非视距地理定位

• 批准号: 1939523
• 负责人: Joseph Farkas
• 金额: $ 22.47万
• 依托单位: SIGNAL PROCESSING TECHNOLOGIES, INC.
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-12-01 至 2020-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1939523&HistoricalAwards=false
• 关键词: SBIR; Phase; Non; Line; Sight

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) project is to pinpoint a mobile device with greater accuracy to aid in emergency situations. The technology will focus on improving geolocation accuracy of mobile devices in rich scattering environments, where current technology suffers significant degradation. In some situations, the location accuracy in these degraded environments results in first responders unable to locate the emergency sufficiently fast, costing lives. The geolocation technology uses the large antenna arrays expected with the onset of 5G and leveraging the attendant rich scattering environments to enhance the location accuracy of current techniques. This level of geolocation accuracy will lead to many new commercial applications, such as augmented reality and autonomous vehicles.This Small Business Innovation Research Phase I project will prove the technical feasibility of the non-line of sight geolocation technology. There are multiple aspects of this project well-grounded theoretically, but requiring demonstration as well as research in algorithms to both improve the performance of the solution and decrease the necessary processing power. The first area of research is RF phenomenology of: 1) the ability to rely on far-field models; and 2) clustered multipath models. The second research area is deconstructing a multipath channel to its individual ray components accurately enough to represent the true electromagnetic reflections, then using that derived information for geolocation. The goal of this project is to advance the technology to proof-of-concept demonstration of both the RF phenomenology and the non-line of sight geolocation algorithms. This will be accomplished through algorithm development in simulation environments and further validated with over-the-air experimentation. It is expected that RF phenomenology models will be refined in this process and fed back into the simulation environment.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.

该小型企业创新研究（SBIR）项目的更广泛影响/商业潜力是以更高的准确性确定移动终端，以在紧急情况下提供帮助。该技术将专注于提高移动的设备在丰富的散射环境中的地理定位精度，在这种环境中，当前技术遭受显著退化。在某些情况下，这些退化环境中的定位精度导致第一响应者无法足够快地定位紧急情况，从而造成生命损失。地理定位技术使用随着5G的出现而预期的大型天线阵列，并利用随之而来的丰富散射环境来提高当前技术的定位精度。 这种地理定位精度将带来许多新的商业应用，例如增强现实和自动驾驶汽车。这个小型企业创新研究第一阶段项目将证明非视线地理定位技术的技术可行性。该项目的多个方面在理论上都有很好的基础，但需要进行演示和算法研究，以提高解决方案的性能并降低必要的处理能力。第一个研究领域是RF现象学：1）依赖远场模型的能力; 2）集群多径模型。第二个研究领域是将多径信道解构为其单独的射线分量，以足够准确地表示真实的电磁反射，然后使用所导出的信息进行地理定位。该项目的目标是将技术推进到RF现象学和非视线地理定位算法的概念验证演示。这将通过仿真环境中的算法开发来实现，并通过空中实验进一步验证。预计RF现象学模型将在此过程中得到完善，并反馈到仿真环境中。该奖项反映了NSF的法定使命，并被认为值得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。