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Mitigating Automotive Radar Interference using Onboard Intelligent Reflective Surface

Published 24 Apr 2024 in eess.SP | (2404.16253v1)

Abstract: The use of automotive radars is gaining popularity as a means to enhance a vehicle's sensing capabilities. However, these radars can suffer from interference caused by transmissions from other radars mounted on nearby vehicles. To address this issue, we investigate the use of an onboard intelligent reflective surface (IRS) to artificially increase a vehicle's effective radar cross section (RCS), or its "electromagnetic visibility." Our proposed method utilizes the IRS's ability to form a coherent reflection of the incident radar waveform back towards the source radar, thereby improving radar performance under interference. We evaluated both passive and active IRS options. Passive IRS, which does not support reflection amplification, was found to be counter-productive and actually decreased the vehicle's effective RCS instead of enhancing it. In contrast, active IRS, which can amplify the reflection power of individual elements, effectively combats all types of automotive radar interference when the reflective elements are configured with a 15-35 dB reflection gain.

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References (22)
  1. SAE International, “Surface Vehicle Information Report Active Safety System Sensors,” J3088, Rev. Nov 2017.
  2. C. Waldschmidt, J. Hasch and W. Menzel, “Automotive Radar — From First Efforts to Future Systems,” in IEEE Journal of Microwaves, vol. 1, no. 1, Jan. 2021.
  3. M. Kunert, “The EU project MOSARIM: A general overview of project objectives and conducted work,” 9th European Radar Conference, 2012.
  4. E. Basar and I. Yildirim, “SimRIS Channel Simulator for Reconfigurable Intelligent Surface-Empowered Communication Systems,” IEEE Latin-American Conference on Communications (LATINCOM), 2020.
  5. Z. Zhang, L. Dai, X. Chen, C. Liu, F. Yang, R. Schober and H. Vincent Poor, “Active RIS vs. Passive RIS: Which Will Prevail in 6G?,” IEEE Transactions on Communications, vol. 71, no. 3, March 2023.
  6. C. Aydogdu, N. Garcia, L. Hammarstrand and H. Wymeersch, “Radar Communications for Combating Mutual Interference of FMCW Radars,” IEEE Radar Conference (RadarConf), 2019.
  7. C. Fischer, H. L. Blöcher, J. Dickmann and W. Menzel, “Robust detection and mitigation of mutual interference in automotive radar,” 2015 16th International Radar Symposium (IRS), 2015.
  8. J. Wang, “CFAR-Based Interference Mitigation for FMCW Automotive Radar Systems,” IEEE Transactions on Intelligent Transportation Systems, vol. 23, no. 8, Aug. 2022.
  9. F. Jin and S. Cao, “Automotive Radar Interference Mitigation Using Adaptive Noise Canceller,” IEEE Transactions on Vehicular Technology, vol. 68, no. 4, April 2019.
  10. F. Uysal and S. Sanka, “Mitigation of automotive radar interference,” IEEE Radar Conference (RadarConf18), 2018.
  11. J. Rock, M. Toth, P. Meissner and F. Pernkopf, “Deep Interference Mitigation and Denoising of Real-World FMCW Radar Signals,” IEEE International Radar Conference (RADAR), 2020.
  12. C. Jiang, Z. Zhou and B. Yang, “Unsupervised Deep Interference Mitigation for Automotive Radar,” 2022 IEEE 12th Sensor Array and Multichannel Signal Processing Workshop (SAM), 2022.
  13. J. Rock, M. Toth, E. Messner, P. Meissner and F. Pernkopf, “Complex Signal Denoising and Interference Mitigation for Automotive Radar Using Convolutional Neural Networks,” 22th International Conference on Information Fusion, 2019.
  14. A. M. Elbir, K. V. Mishra, M. R. B. Shankar and S. Chatzinotas, “The Rise of Intelligent Reflecting Surfaces in Integrated Sensing and Communications Paradigms,” arXiv preprint arXiv:2204.07265, April 2022.
  15. M. Rihan, E. Grossi, L. Venturino and S. Buzzi, “Spatial Diversity in Radar Detection via Active Reconfigurable Intelligent Surfaces,” arXiv preprint arXiv:2202.01616, May 2022.
  16. A. Shafie, G. N. Yang, C. Han, J. M. Jornet, M. Juntti and T. Kurner, “Terahertz Communications for 6G and Beyond Wireless Networks: Challenges, Key Advancements, and Opportunities,” arXiv preprint arXiv:2207.11021, July 2022.
  17. S. K. Dehkordi and G. Caire, “Making Vulnerable Road Users More Visible to Radar: A Communications Inspired Approach,” 21st International Radar Symposium (IRS), 2021.
  18. V. Winkler, “Range Doppler detection for automotive FMCW radars,” 2007 European Microwave Conference, 2007.
  19. B. M. Keel, “Principles of Modern Radar: Basic principles”, Chap. 16, IET Digital Library, 2010.
  20. R. Amar, M. Alaee-Kerahroodi and M. R. Bhavani Shankar, “FMCW-FMCW Interference Analysis in mm-Wave Radars; An indoor case study and validation by measurements,” 2021 21st International Radar Symposium (IRS), 2021.
  21. https://in.mathworks.com/help/driving/ref/vehicledimensions.html
  22. E. Bel Kamel, A. Peden and P. Pajusco, “RCS modeling and measurements for automotive radar applications in the W band,” 11th European Conference on Antennas and Propagation (EUCAP), 2017.

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