Award Abstract # 2033433
MIMO Radar With Sparse Linear Arrays - Theory, Implementation and Applications

NSF Org: ECCS
Div Of Electrical, Commun & Cyber Sys
Recipient: RUTGERS, THE STATE UNIVERSITY
Initial Amendment Date: August 17, 2020
Latest Amendment Date: August 4, 2022
Award Number: 2033433
Award Instrument: Standard Grant
Program Manager: Huaiyu Dai
hdai@nsf.gov
 (703)292-4568
ECCS
 Div Of Electrical, Commun & Cyber Sys
ENG
 Directorate For Engineering
Start Date: September 1, 2020
End Date: August 31, 2024 (Estimated)
Total Intended Award Amount: $450,000.00
Total Awarded Amount to Date: $500,000.00
Funds Obligated to Date: FY 2020 = $450,000.00
FY 2022 = $50,000.00
History of Investigator:
  • Athina Petropulu (Principal Investigator)
    athinap@rutgers.edu
  • Yingying Chen (Co-Principal Investigator)
  • Chung-Tse Wu (Co-Principal Investigator)
Recipient Sponsored Research Office: Rutgers University New Brunswick
3 RUTGERS PLZ
NEW BRUNSWICK
NJ  US  08901-8559
(848)932-0150
Sponsor Congressional District: 12
Primary Place of Performance: Rutgers University
94 Brett Road
Piscataway
NJ  US  08854-3925
Primary Place of Performance
Congressional District:
06
Unique Entity Identifier (UEI): M1LVPE5GLSD9
Parent UEI:
NSF Program(s): CCSS-Comms Circuits & Sens Sys
Primary Program Source: 01002223DB NSF RESEARCH & RELATED ACTIVIT
01002021DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s): 120Z, 153E, 6194
Program Element Code(s): 7564
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.041

ABSTRACT

Multiple-input multiple-output (MIMO) radars have several advantages as compared to traditional phased arrays. They can achieve higher resolution with the same number of antennas. They can also achieve wide field of view, illuminating multiple targets at the same time, which translates to faster detection time. Reduction of the number of active antennas without hurting the radar performance would reduce the cost of the radar, while a low-cost, high resolution radar would advance the state-of-art of autonomous driving, smart environment, smart home, and IoT sensing, and would enable applications such as smart patient care, elderly monitoring, fitness assistant, etc., that rely on sensing. In an era where COVID-19 forced home isolation with limited supervision of vulnerable segments of the population, a radar device could provide information on vital signs, or detect falls without invading people's privacy in the way surveillance cameras would. MIMO radar using specially designed Sparse Linear Arrays (SLAs) can enjoy reduced hardware cost without losing the MIMO radar advantages. An SLA can be thought of as a uniform linear array with only a small number of active antennas. By careful selection of the active antennas and optimal design of transmit waveforms, one can maintain a radar performance close to that of the fully populated array. However, finding an optimal sparse array geometry in terms of the fewest antennas is a difficult combinatorial problem. The proposed project will advance the state-of-art of SLA based MIMO radar as a cost-effective imaging radar by (i) providing a novel framework for antenna selection, (ii) developing an SLA MIMO radar prototype based on frequency-scanning metamaterial (MTM) antennas, and (iii) developing real-time activity monitoring and user identification schemes that leverage the high resolution and wide field of view of MIMO SLA radar.

There are several novel aspects in the proposed work. (i) A novel machine learning approach for antenna selection is proposed, which offers a unifying framework for dealing with any performance metric. The novelty of the proposed approach lies in its ability to get multiple softmax models to work together. (ii) The use of MTM antennas brings in the added advantage of allowing for easy change of the beam elevation by varying the antenna frequency. That advantages will be exploited to look for targets in the 3-D space while still using a linear array. By varying the frequency of the MTM antennas, one can select the elevation direction of the transmit beam, and by applying the proposed SLA design method, one can design the beam pattern in the 2-D space corresponding to the selected elevation direction. The frequency scanning capability resulting from the dispersive nature of MTM allows a real time and low complexity beam scanning mechanism, whereas the SLA MIMO radar with proper waveform engineering will generate a large scale virtual array with enhanced angular resolution. As such, the combination of SLA MIMO radar with MTM antennas will enable an unprecedented radar architecture with larger field of view, finer resolution, and small number of antenna RF fronts. (iii) Low-latency signal processing algorithms will be developed for leveraging the large field of view and high angle resolution, that will have the capability to construct 3D user models and identify multiple targets simultaneously. Innovative neural network structures will be devised to enable device-free user activity monitoring. It is expected that the multi-user identification mechanisms will reveal unique user-specific activity characteristics embedded in the movements of high-resolution point clouds, facilitating a broad range of emerging mobile 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.

PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH

Note:  When clicking on a Digital Object Identifier (DOI) number, you will be taken to an external site maintained by the publisher. Some full text articles may not yet be available without a charge during the embargo (administrative interval).

Some links on this page may take you to non-federal websites. Their policies may differ from this site.

(Showing: 1 - 10 of 20)
Shi, Cong and Zhang, Tianfang and Xu, Zhaoyi and Li, Shuping and Yuan, Yichao and Petropulu, Athina and Wu, Chung Tse and Chen, Yingying "Speech privacy attack via vibrations from room objects leveraging a phased-MIMO radar" MobiSys '22: Proceedings of the 20th Annual International Conference on Mobile Systems, Applications and Services , 2022 https://doi.org/10.1145/3498361.3538790 Citation Details
Xu, Zhaoyi and Liu, Fan and Petropulu, Athina "Cramér-Rao Bound and Antenna Selection Optimization for Dual Radar-Communication Design" IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) , 2022 https://doi.org/10.1109/ICASSP43922.2022.9747651 Citation Details
Mishra, Kumar Vijay and Chattopadhyay, Arpan and Acharjee, Siddharth Sankar and Petropulu, Athina P. "Optm3sec: Optimizing Multicast Irs-Aided Multiantenna Dfrc Secrecy Channel With Multiple Eavesdroppers" IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) , 2022 https://doi.org/10.1109/ICASSP43922.2022.9747551 Citation Details
Petropulu, Athina "On Dual-Use Information Technology [President?s Message]" IEEE Signal Processing Magazine , v.39 , 2022 https://doi.org/10.1109/MSP.2022.3148638 Citation Details
Xu, Zhaoyi and Petropulu, Athina P. "DFRC with Improved Communication-Sensing Trade-off via Private Subcarrier Permutations and Pairing with Antennas" 2022 IIEEE Wireless Communications and Networking Conference (WCNC)) , 2022 https://doi.org/10.1109/WCNC51071.2022.9771743 Citation Details
Xu, Zhaoyi and Shi, Cong and Zhang, Tianfang and Li, Shuping and Yuan, Yichao and Wu, Chung-Tse Michael and Chen, Yingying and Petropulu, Athina "Simultaneous Monitoring of Multiple People?s Vital Sign Leveraging a Single Phased-MIMO Radar" IEEE Journal of Electromagnetics, RF and Microwaves in Medicine and Biology , 2022 https://doi.org/10.1109/JERM.2022.3143431 Citation Details
Petropulu, Athina "Signal Processing in Our Digital Era [President?s Message]" IEEE Signal Processing Magazine , v.39 , 2022 https://doi.org/10.1109/MSP.2021.3118525 Citation Details
Zhang, J. Andrew and Liu, Fan and Masouros, Christos and Heath, Robert W. and Feng, Zhiyong and Zheng, Le and Petropulu, Athina "An Overview of Signal Processing Techniques for Joint Communication and Radar Sensing" IEEE Journal of Selected Topics in Signal Processing , v.15 , 2021 https://doi.org/10.1109/JSTSP.2021.3113120 Citation Details
Masouros, Christos and Heath, Robert and Zhang, J. Andrew and Feng, Zhiyong and Zheng, Le and Petropulu, Athina "Editorial: Introduction to the Issue on Joint Communication and Radar Sensing for Emerging Applications" IEEE Journal of Selected Topics in Signal Processing , v.15 , 2021 https://doi.org/10.1109/JSTSP.2021.3119395 Citation Details
Xu, Zhaoyi and Liu, Fan and Diamantaras, Konstantinos and Masouros, Christos and Petropulu, Athina "Learning to Select for Mimo Radar Based on Hybrid Analog-Digital Beamforming" IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) , 2021 https://doi.org/10.1109/ICASSP39728.2021.9413904 Citation Details
Petropulu, Athina "IEEE Signal Processing Society PROGRESS: Support for Underrepresented Talent in the Field of Signal Processing [Conference Highlights]" IEEE Signal Processing Magazine , v.38 , 2021 https://doi.org/10.1109/MSP.2021.3067588 Citation Details
(Showing: 1 - 10 of 20)

Please report errors in award information by writing to: awardsearch@nsf.gov.

Print this page

Back to Top of page