Open Access
ITM Web Conf.
Volume 48, 2022
The 4th International Conference on Computing and Wireless Communication Systems (ICCWCS 2022)
Article Number 01010
Number of page(s) 8
Section Antennas & Propagation
Published online 02 September 2022
  1. O. Bialer, A. Jonas, and T. Tirer "Code Optimization for Fast Chirp FMCW Automotive MIMO Radar", IEEE Transactions on Vehicular Technology 70 (8), 7582-7593, July, 2021. [CrossRef] [Google Scholar]
  2. M. Gottinger, M. Hoffmann, M. Christmann, M. Schutz, F. Kirsch, P. Gulden, and M. Vossiek Coherent Automotive Radar Networks: The Next Generation of Radar-Based Imaging and Mapping. IEEE Journal of Microwaves, vol. 1, no. 1, pp. 149 - 163, Januar, 2021. [CrossRef] [Google Scholar]
  3. B. Li, S. Wang, Z. Feng, J. Zhang, X. Cao, and C. Zhao. Fast Pseudospectrum Estimation for Automotive Massive MIMO Radar. arXiv: 1911.07434v3, Dec 2021. [Google Scholar]
  4. M. Gottinger, M. Hoffmann, M. Christmann, M. Schutz, F. Kirsch, P. Gulden, and M. Vossiek Coherent Automotive Radar Networks: The Next Generation of Radar-Based Imaging and Mapping. IEEE Journal of Microwaves, vol. 1, no. 1, pp. 149 - 163, Januar, 2021. [CrossRef] [Google Scholar]
  5. C. Pfeffer, R. Feger, C. Wagner and A. Stelzer. FMCW MIMO Radar System for Frequency-Division Multiple TX-Beamforming. IEEE transactions on microwavetheory and techniques vol. 61, no. 12, decembre 2013 [Google Scholar]
  6. A. Bose, B. Tang, M. Soltanalian and J. Li. Mutual Interference Mitigation for Multiple Connected Automotive Radar Systems. IEEE Transactions on Vehicular Technology [Google Scholar]
  7. N. Amani, F. Jansen, A. Filippi, M.V. Ivashina, and Rob Maaskant. Sparse Automotive MIMO Radar for Super-Resolution Single Snapshot DOA Estimation With Mutual Coupling IEEE Access, vol. 9, 2021 [Google Scholar]
  8. P. Sévigny, “MIMO Radar: Literature survey of papers between 2003 and September 2008,” DRDC, Ottawa, ON, TM 2008-333, Mar. 2009. [Google Scholar]
  9. J. Li and P. Stoica, MIMO Radar Signal Processing. Hoboken, NJ: Wiley-IEEE Press, 2008. [Google Scholar]
  10. P. W. Moo and Z. Ding, “Tracking Performance of MIMO Radar for Accelerating Targets,” IEEE Trans. Signal Process., vol. 61, no. 21, pp. 5205–5216, Nov. 2013. [CrossRef] [Google Scholar]
  11. I. Bekkerman and J. Tabrikian, “Target Detection and Localization Using MIMO Radars and Sonars,” IEEE Trans. Signal Process., vol. 54, no. 10, pp. 3873–3883, Oct. 2006. [CrossRef] [Google Scholar]
  12. E. Fishler, A. Haimovich, R. Blum, D. Chizhik, L. Cimini, and R. Valenzuela, ``MIMO radar: An idea whose time has come,'' in Proc. IEEE Radar Conf., Apr. 2004, pp. 71-78. [Google Scholar]
  13. F. C. Robey, S. Coutts, D. Weikle, J. C. McHarg, and K. Cuomo, ``MIMO radar theory and experimental results,'' in Proc. 28th Asilomar Conf. Signals, Syst. Comput., Nov. 2004, pp. 300-304. [Google Scholar]
  14. M. Hefnawi, J. Bray, J. Bathurst, and Y. Antar, “MIMO Radar Using a Vector Network Analyzer,” Electronics, vol. 8, no. 12, Art. no. 12, Dec. 2019, doi: 10.3390/electronics8121447. [Google Scholar]
  15. J. Bergin and J. R. Guerci, MIMO Radar Theory and Application. Boston, MA, USA: Artech House, 2008. [Google Scholar]
  16. H. Sun, F. Brigui, and M. Lesturgie, “Analysis and comparison of MIMO radar waveforms,” in 2014 International Radar Conference, 2014, pp. 1–6. [Google Scholar]
  17. Olivier Rabaste, Laurent Savy, Mathieu Cattenoz, and Jean-Paul Guyvarch. Signal waveforms and range/angle coupling in coherent colocated MIMO radar. In Radar (Radar), 2013 International Conference on, pages 157–162. IEEE, 2013. [CrossRef] [Google Scholar]
  18. Ming Xue, Jian Li, and Peter Stoica. MIMO radar waveform design. In Fulvio Gini, Antonio DeMaio, and Lee Patton, editors, Waveformdesign and diversity for advanced radar systems, pages 89–120. IET Press, 2012. [CrossRef] [Google Scholar]
  19. Hongbo Sun, Frédéric Brigui, and Marc Lesturgie. Analysis and comparison of MIMO radar waveforms. In 2014 International Radar Conference. IEEE, 2014. [Google Scholar]
  20. Ralpph O. Acmidt, "Multiple Emitter Location and Signal Parameter Estimation," IEEE Trans. Antennas & Prop., vol. AP-34, no. 3, Mar. 1986, pp. 276-280 [Google Scholar]
  21. R. Roy and T. Kailath, “ESPRIT-estimation of signal parameters via rotational invariance techniques,” IEEE Trans. Acoust. Speech Signal Process., vol. 37, no. 7, pp. 984–995, Jul. 1989. [CrossRef] [Google Scholar]
  22. J. Capon, “High-resolution frequency-wavenumber spectrum analysis,” Proc. IEEE, vol. 57, no. 8, pp. 1408-1418, Aug. 1969. [CrossRef] [Google Scholar]
  23. Jiho Seo, Yunji Yang, Yong‐gi Hong, Jaehyun Park, “Transfer learning‐based radar imaging with deep convolutional neural networks for distributed frequency modulated continuous waveform multiple‐input multiple‐output radars,” IET Radar, Sonar & Navigation, 2021;15:1209–1220; doi: 10.1049/rsn2.12105. [CrossRef] [Google Scholar]
  24. M. S. Seyfioglu, A. M. Ozbayoglu, and S. Z. Gurbuz, “Deep convolutional autoencoder for radar-based classification of similar aided and unaided human activities,” IEEE Transaction on Aerospace and Electronic Systems. Vol. 54, no. 4 Aug. 2018. [Google Scholar]
  25. Ramakrishna Sai Annaluru, Khurram Usman Mazher, Robert W. Heath, “Deep Learning Based Range and Doa Estimation using low Resolution FMCW Radars,” 2021 IEEE Statistical Signal Processing Workshop (SSP), DOI: 10.1109/SSP49050.2021.9513759. [Google Scholar]
  26. Woosuk Kim 1, Hyunwoong Cho, Jongseok Kim, Byungkwan Kim, and Seongwook Lee, “YOLO-Based Simultaneous Target Detection and Classification in Automotive FMCW Radar Systems,” Sensors 2020, 20(10), 2897. [Google Scholar]
  27. Pérez, R.; Schubert, F.; Rasshofer, R.; Biebl, E. Deep learning radar object detection and classification for urban automotive scenarios. In Proceedings of the 2019 Kleinheubach Conference, Miltenberg, Germany, 23–25 September 2019. [Google Scholar]
  28. Jin-Cheol Kim, Hwi-Gu Jeong, and Seongwook Lee, "Simultaneous Target Classification and Moving Direction Estimation in Millimeter-Wave Radar System," Sensors 2021, 21(15), 5228. [CrossRef] [Google Scholar]
  29. Support Vector Machine (SVM) MATLAB, [Online]. Available: [Google Scholar]
  30. F. N. Iandola, S. Han, M. W. Moskewicz, K. Ashraf, W. J. Dally, and K. Keutzer. SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and < 0.5 MB model size. arXiv preprint arXiv:1602.07360, 2016. [Google Scholar]
  31. SqueezeNet, [Online]. Available: [Google Scholar]
  32. Radar Target Classification Using Machine Learning and Deep Learning-MATLAB, [Online]. Available: [Google Scholar]
  33. T.Cheng, B.Wang, Z.Wang, R.Dong, and B.Cai. Lightweight CNNs-Based Interleaved Sparse Array Design of Phased-MIMO Radar, IEEE sensors journal, vol. 21, no. 12, june 15, 2021 [Google Scholar]
  34. T.Wan, X.Fu, K.Jiang, Y.Zhao and B.Tang. Radar Antenna Scan Pattern Intelligent Recognition Using Visibility Graph, IEEE access, volume 7, 2019 [Google Scholar]
  35. F.Meng, K.Tian, and C.Wu Deep Reinforcement Learning-Based Radar Network Target Assignment, Electronics, vol. 11, no. 3, January 2022, doi: 10.3390/electronics11030311 [Google Scholar]
  36. Increasing Angular Resolution with Virtual Arrays-MATLAB, [Online]. Available: [Google Scholar]
  37. Automotive Adaptive Cruise Control Using FMCW Technology [Online].Available: [Google Scholar]
  38. Karnfelt, Camilla, et al. “77 GHz ACC Radar Simulation Platform.” 9th International Conference on Intelligent Transport Systems Telecommunications, (ITST), IEEE, 2009, pp. 209–14. [Google Scholar]
  39. Barton, David. “Land Clutter Models for Radar Design and Analysis,” Proceedings of the IEEE. Vol. 73, Number 2, February, 1985, pp. 198–204 [CrossRef] [Google Scholar]

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