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| Funder | National Science Foundation (US) |
|---|---|
| Recipient Organization | Georgia Tech Research Corporation |
| Country | United States |
| Start Date | Jul 01, 2022 |
| End Date | Dec 31, 2023 |
| Duration | 548 days |
| Number of Grantees | 1 |
| Roles | Principal Investigator |
| Data Source | National Science Foundation (US) |
| Grant ID | 2227380 |
The broader impact/commercial potential of this I-Corps project is the potential development of a scanless RADAR (RAdio Detection And Ranging) technology. This scanless sensor has the potential to possibly integrate large areas, perform faster scanning, focus on objects longer during tracking (especially in the near field), and image with a multi-frequency system without the need for a moving system.
The ability to have multiple frequencies incorporated could be useful to maintain the ability to image in degraded environments without compromising high resolution. This innovation is expected to serve as a possible platform technology and could provide enhanced sensing capabilities for markets including autonomous vehicles, and medical devices for rural areas.
This I-Corps project is based on the development of a novel remote sensing technique that leverages the benefits of both RADAR (RAdio Detection And Ranging) and LIDAR (Light Detection and Ranging). It provides a technology that could provide a wide field of view, without the need for a moving platform, at comparable resolutions to the current most advanced RADAR techniques.
Current solutions for high-resolution imaging include digital beamforming and LIDAR. While digital beamforming can yield high-resolution scans, it requires multiple pulses to scan an entire scene. Multiple sweeps of the scene of interest are required for digital beamforming as narrow directed beams must be used to get enhanced resolution.
Digital beamforming contains a blind spot close to the RADAR (i.e., in the near field) due to certain assumptions that are made in its signal processing. LIDAR, which uses light waves instead of radio waves, delivers high resolution due to its small wavelength; however, these small wavelengths do not propagate through environments as well as radio waves and thus perform poorly in atmospheric conditions such as rain and fog.
The proposed technology seeks to potentially process waves of any wavelength simultaneously and presents a needed solution for the integration of data obtained from different sensor types (e.g., RADAR, LIDAR, and SONAR).
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.
Georgia Tech Research Corporation
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