Book Chapters

• S. Sun, “MIMO Radar Technology,” Chapter in the book of Modern Radar for Automotive Applications (edited by Z. Peng, C. Li and F. Uysal), IET 2022.
• S. Sun, “Automotive MIMO Radar,” Chapter in the book of Radar for Fully Autonomous Vehicles (edited by Matt Markel), Artech House 2022.
• S. Sun, D. Smith and M. Markel, “Design Considerations for Automotive Radar,” Chapter in the book of Radar for Fully Autonomous Vehicles (edited by Matt Markel), Artech House 2022.
• ​S. Z. Gurbuz, S. Sun and D. Tahmoush,  ‘‘Radar Systems, Signals, and Phenomenology,” Chapter 1 in the book of Deep Neural Network Design for Radar Applications (edited by ​S. Z. Gurbuz), IET 2020.

Manuscript Under Review

• R. Zheng, S. Sun, H. Liu and T. Wu, ​‘‘Deep neural networks-enabled high-resolution automotive radar imaging and object detection for fully autonomous driving​,’’ IEEE Transactions on Aerospace and Electronic Systems, submitted in 2022.
• L. Xu, S. Sun, K. V. Mishra and Y. D. Zhang, ​‘‘Automotive FMCW radar with difference co-chirps​,’’ IEEE Transactions on Aerospace and Electronic Systems, submitted in 2022.

Journal Publications

• S. Zhang, A. Ahmed, Y. D. Zhang and S. Sun, ‘‘Enhanced DOA estimation exploiting multi-frequency sparse array,” IEEE Transactions on Signal Processing, vol. 69, pp. 5935-5946, 2021.
• S. Sun and Y. D. Zhang, ‘‘4D automotive radar sensing for autonomous vehicles: A sparsity-oriented approach,” IEEE Journal of Selected Topics in Signal Processing, vol. 15, no. 4, pp. 879-891, 2021.
• S. Sun, A. P. Petropulu and H. V. Poor, “MIMO radar for advanced driver-assistance systems and autonomous driving: Advantages and challenges,” IEEE Signal Processing Magazine, vol. 37, no. 4, pp. 98-117, 2020. (Feature Article)
• S. Sun and A. P. Petropulu, ‘‘Waveform design for MIMO radars with matrix completion,’’ IEEE Journal of Selected Topics in Signal Processing, vol. 9, no. 8, pp. 1400-1414, 2015.
• S. Sun, W. U. Bajwa, and A. P. Petropulu, ‘‘MIMO-MC radar: A MIMO radar approach based on matrix completion,’’ IEEE Transactions on Aerospace and Electronic Systems, vol. 51, no. 3, pp. 1839-1852, 2015.
• ​Y. Yu, S. Sun, R. N. Madan, and A. P. Petropulu, ‘‘Power allocation and waveform design for the compressive sensing based MIMO radar,’’ IEEE Transactions on Aerospace and Electronic Systems, vol. 50, no. 2, pp. 898-909, 2014.

Conference Publications

• R. Zheng, H. Liu, and S. Sun, ‘‘A deep learning approach for Doppler unfolding in automotive TDM MIMO radar,’’ in Proc. 56th Annual Asilomar Conference on Signals, Systems, and Computers (Asilomar), Pacific Grove, CA, Oct. 30 - Nov. 2, 2022.
• R. Zheng, S. Sun, D. Scharff and T. Wu, ‘‘SpectraNet: A High resolution imaging radar deep neural network for autonomous vehicles,’’ in Proc. IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM), Trondheim, Norway, June 20-23, 2022. 
• L. Xu, R. Zheng and S. Sun, ‘‘A deep reinforcement learning approach for integrated automotive radar sensing and communication,’’ in Proc. IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM), Trondheim, Norway, June 20-23, 2022. 
• R. Zheng, S. Sun, D. Scharff and T. Wu, ‘‘Beyond point clouds: A knowledge-aided high resolution imaging radar deep detector for autonomous driving,” arXiv preprint, arXiv:2111.01246, 2021.  
• L. Xu, S. Sun and K. V. Mishra,  ‘‘Difference co-chirps-based non-uniform PRF automotive FMCW radar,’’ in Proc. IEEE International Conference on Autonomous Systems (ICAS), Montréal, Québec, Canada, Aug. 11-13, 2021. 
• S. Sun and Y. D. Zhang,  ‘‘Four-dimensional high-resolution automotive radar imaging exploiting joint sparse-frequency and sparse-array design,’’ in Proc. IEEE 46th International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Toronto, Canada, June 6-11, 2021.
• S. Sun, L. Xu and N. S. Jeong,  ‘‘Sparse step-frequency MIMO radar design for autonomous driving,’’ in Proc. IEEE Radar Conference, Atlanta, GA, May 10-14, 2021. 
• S. Sun and Y. D. Zhang,  ‘‘Multi-frequency sparse array-based massive MIMO radar for autonomous driving,’’ in Proc. 54th Annual Asilomar Conference on Signals, Systems, and Computers (Asilomar), Pacific Grove, CA, Nov. 1-4, 2020. (Invited)
• X. Zhao, A. P. Petropulu and S. Sun, ‘‘A joint design of MIMO-OFDM dual-function radar communication system using generalized spatial modulation,” in Proc. IEEE Radar Conference, Florence, Italy, Sept. 21-25, 2020. 
• S. Zhang, A. Ahmed, Y. D. Zhang, and S. Sun, “DOA estimation exploiting interpolated multi-frequency sparse array,” in Proc. IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM), Hangzhou, China, June 8-11, 2020. (The Best Student Paper Award)
• S. Sun and A. P. Petropulu,  ‘‘A sparse linear array approach in automotive radars using matrix completion,’’ in Proc. IEEE 45th International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Barcelona, Spain, May 4-8, 2020.
• S. Sun, K. V. Mishra and A. P. Petropulu, ‘‘Target estimation by exploiting low rank structure in widely separated MIMO radar,’’ in Proc. IEEE Radar Conference, Boston, MA, April 22-26, 2019.
• S. Sun and A. P. Petropulu, ‘‘On waveform conditions in MIMO radars using matrix completion,’’ in Proc. 49th Annual Asilomar Conference on Signals, Systems, and Computers (Asilomar), Pacific Grove, CA, Nov. 8-11, 2015. (Invited)
• S. Sun and A. P. Petropulu, ‘‘On transmit beamforming in MIMO radar with matrix completion,’’ in Proc. IEEE 40th International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Brisbane, Australia, April 2015.
• S. Sun and A. P. Petropulu, ‘‘On waveform design for MIMO radar with matrix completion,’’ in Proc. IEEE Global Conference on Signal and Information Processing (GlobalSIP), Information Processing for Big Data Symposium, Atlanta, GA, Dec. 3-5, 2014.
• S. Sun and A. P. Petropulu, ‘‘On the applicability of matrix completion on MIMO radars,’’ in Proc. 48th Annual Asilomar Conference on Signals, Systems, and Computers (Asilomar), Pacific Grove, CA, Nov. 2-5, 2014. (Invited)
• D. S. Kalogerias, S. Sun, and A. P. Petropulu, ‘‘Sparse sensing in colocated MIMO radar: A matrix completion approach,’’ in Proc. IEEE 13th International Symposium on Signal Processing and Information Technology (ISSPIT), Athens, Greece, Dec. 12-15, 2013. (Invited)
• S. Sun, A. P. Petropulu, and W. U. Bajwa, ‘‘High-resolution networked MIMO radar based on sub-Nyquist observations,’’ in Signal Processing with Adaptive Sparse Structured Representations Workshop (SPARS), EPFL, Lausanne, Switzerland, July 8-11, 2013.
• S. Sun, A. P. Petropulu, and W. U. Bajwa, ‘‘Target estimation in colocated MIMO radar via matrix completion,’’ in Proc. IEEE 38th International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Vancouver, Canada, May 2013.
• Y. Yu, S. Sun and A. P. Petropulu, ‘‘A Capon beamforming method for clutter suppression in colocated compressive sensing based MIMO radar,’’ SPIE Defense, Security, and Sensing, Baltimore, MD, April 29-May 3, 2013.
• S. Sun and A. P. Petropulu, ‘‘Robust beamforming via matrix completion,’’ in Proc. 47th Annual Conference on Information Sciences and Systems (CISS) , Baltimore, MD, March 20-22, 2013.
• S. Sun, W. Ni and Y. Zhu, ‘‘Robust power control in cognitive radio networks: A distributed way,’’ in Proc. IEEE International Conference on Communications (ICC), Kyoto, Japan, June 5-9, 2011. (Student Travel Grant)
• S. Sun, W. Ni and Y. Zhu, ‘‘Robust distributed power control in cognitive radio networks,’’ in Proc. the 30th IEEE International Conference on Computer Communications (INFOCOM), Shanghai, China, April 10-15, 2011. (The Third Prize Best Poster Award)
• S. Sun, J. Di and W. Ni, ‘‘Distributed power control based on convex optimization in cognitive radio networks,’’ in Proc. 2nd International Conference on Wireless Communications and Signal Processing (WCSP), Suzhou, China, Oct. 21-23, 2010.

U.S. Patents

• S. Sun, ‘‘Sparse linear array approach in automotive radars using matrix completion,’’ U.S. Patent No. US 2021/0311182 A1 , issued on Oct. 7, 2021. 
• S. Sun and C. Alcalde, ‘‘Removing interference from signals received by detectors supported on a vehicle,’’ U.S. Patent No. US 2020/0284871 A1, issued on Sep. 10, 2020. 

Presentations

• Invited Talk on 4D automotive radar sensing for autonomous vehicles, Seminar at GM Cruise, Feb. 3, 2022.
• ​​Invited Seminar on​ 4D automotive radar sensing for autonomous vehicles, Seminar at The University of Alabama, Jan. 26, 2022.
• RadarConf 2019  — Target estimation by exploiting low rank structure in widely separated MIMO radar
• Invited talk on ‘‘The Advantages and Challenges of MIMO Radar for Autonomous Driving’’ at California State University, Long Beach, Mar. 29, 2019
• Invited IEEE Communications Society (ComSoc) webinar on ‘‘MIMO Radar and Its Role in Autonomous Driving’’, July 24, 2018
• Invited to give a talk on ‘‘Make Self-Driving Cars See! The Key MIMO Radar Technology for Autonomous Driving’’ at Michigan State University, East Lansing, MI, Mar. 19, 2018
• Invited talk on ‘‘MIMO Radar: Fundamentals, Sparse Sensing and its Application in Autonomous Driving (Part II)’’ at IEEE Buenaventura Section Seminar, Skyworks Solutions, Newbury Park, CA, Nov. 28, 2017
• Invited talk on ‘‘MIMO Radar: Fundamentals, Sparse Sensing and its Application in Autonomous Driving (Part I)’’ at IEEE Buenaventura Section Seminar, Skyworks Solutions, Newbury Park, CA, Sept. 26, 2017
• Asilomar 2015  — On waveform conditions in MIMO radars using matrix completion
• SPIE 2013 Compressive Sensing for Radar  — A Capon beamforming method for clutter suppression in colocated compressive sensing based MIMO radar
• CISS 2013  —  Robust beamforming via matrix completion
• SAM 2012  —  Power allocation for CS-based colocated MIMO radar systems
• ICC 2011  —  Robust power control in cognitive radio networks: A distributed way
• WCSP 2010  —  Distributed power control based on convex optimization in cognitive radio networks​​

PhD Dissertation

Shunqiao Sun, ‘‘MIMO Radars with Sparse Sensing,’’ Rutgers University, New Brunswick, NJ, Jan. 2016. 
IEEE Aerospace and Electronic Systems Society Robert T. Hill Best Dissertation Award

Research Profile and Citations

Google Scholar

IEEE Disclaimer

This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.