SBIR-STTR Award

The broader impact/commercial potential of this project is significant. The research results will address the resolution and detection speed requirements of autonomous driving in complex environments such as urban scenarios. The next major revolution of transportation is undoubtedly autonomous driving which will bring great potential benefits in terms of safety, mobility and related productivity. With the proposed advanced sensing system and intelligent algorithms, it is expected that future autonomous driving vehicle could eliminate mistakes due to human error which is the main cause of traffic accidents. Moreover, it may lead to reduced traffic jam, higher energy efficiency and much enhanced mobility for the aging and disabled population. The proposed effort will also have great commercial impact. In 2015, the global market size of automotive millimeter wave (30 ? 300 GHz) radars hit about $1.936 billion; it is expected to reach $2.46 billion in 2016 and $5.12 billion in 2020, having the most remarkable growth potentials in the field of electronic products. In addition, the expected research outcome may lead to advancement in a number of important market sectors including wireless communication, sensing, mobile internet, assistive technology, and additive manufacturing. This Small Business Technology Transfer (STTR) Phase I project attempts to realize a high performance automotive radar using 3D printed Luneburg Lens for autonomous driving. The existing automotive radar products do not have enough angular coverage and resolution for classifying and locating dense targets, which is critical for achieving autonomous driving. As a result, the current autonomous driving tests utilize LiDAR systems which are expensive and less reliable than radar especially under certain conditions such as heavy rain, snow, fog, smoke and sandstorms. Compared to conventional manufacturing techniques, this project utilizes 3D printing technique, which is much more convenient, fast, inexpensive and capable of implementing millimeter wave Luneburg lenses. Based on the Luneburg lens?s ability to form multiple beams with high gain and broadband behavior, novel automotive radar will be designed by mounting radar detectors around the lens. Moreover, with wide bandwidth and natural beam forming capabilities of Luneburg lens, an adaptive sensing approach is proposed to improve the scanning efficiency and avoid interference from nearby or intruder radar systems. With these proposed approaches, the objective is to achieve a high performance and low cost millimeter-wave sensing system which will be suitable for autonomous transportation applications.

The broader impact/commercial potential of this project will be that this research will address the resolution and detection range requirements of autonomous driving in complex environments such as urban scenarios. The next major revolution of transportation is undoubtedly autonomous driving, which will increase safety, mobility and productivity. Fully autonomous transportation may eliminate human error, the leading cause of traffic accidents, and could also lead to reduced traffic congestion, higher energy efficiency, and enhanced mobility for the aging and disabled population. The proposed advanced sensing system with intelligent algorithms is expected to help enable and advance the autonomous driving revolution. The proposed effort will also have great commercial impact. The global market size of autonomous sensors is expected to grow from $5.2 billion in 2018 to $11.9 billion in 2023, with the radar-based sensor segment representing $2.9 billion in 2023. In addition, the expected research outcome may lead to advancements in a number of important market sectors including wireless communications, sensing, mobile internet, assistive technology, and additive manufacturing.This Small Business Innovation Research (SBIR) Phase 2 project aims to realize a 3D-printed Luneburg lens-based high performance automotive radar for autonomous driving. Existing automotive radars do not have enough distance detection, field of view, and angular resolution for classifying and locating dense targets, which is critical for achieving fully autonomous driving. As a result, current autonomous driving tests utilize LiDAR ((Light Detection And Ranging) systems which are more expensive and less reliable than radar especially under adverse weather conditions such as rain, snow, fog, and smoke. Compared to conventional manufacturing techniques, this project utilizes 3D printing, which is convenient, fast, inexpensive and capable of implementing millimeter wave Luneburg lenses. Based on the Luneburg lens?s ability to form multiple beams with high gain and broad bandwidth, a novel automotive radar will be designed by mounting radar detectors around the lens. Moreover, with the wide bandwidth and natural beam forming capabilities of the Luneburg lens, an adaptive sensing approach is proposed to improve the scanning efficiency and avoid interference from nearby or intruder radar systems. With these proposed approaches, the objective is to achieve a high performance and high value millimeter-wave sensing system suitable for autonomous transportation applications.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.