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6D Radar Sensing and Tracking in Monostatic Integrated Sensing and Communications System

Published 27 Dec 2023 in eess.SP | (2312.16441v1)

Abstract: In this paper, we propose a novel scheme for sixdimensional (6D) radar sensing and tracking of dynamic target based on multiple input and multiple output (MIMO) array for monostatic integrated sensing and communications (ISAC) system. Unlike most existing ISAC studies believing that only the radial velocity of far-field dynamic target can be measured based on one single base station (BS), we find that the sensing echo channel of MIMO-ISAC system actually includes the distance, horizontal angle, pitch angle, radial velocity, horizontal angular velocity, and pitch angular velocity of the dynamic target. Thus we may fully rely on one single BS to estimate the dynamic target's 6D motion parameters from the sensing echo signals. Specifically, we first propose the long-term motion and short-term motion model of dynamic target, in which the short-term motion model serves the single-shot sensing of dynamic target, while the long-term motion model serves multiple-shots tracking of dynamic target. As a step further, we derive the sensing channel model corresponding to the short-term motion. Next, for singleshot sensing, we employ the array signal processing methods to estimate the dynamic target's horizontal angle, pitch angle, distance, and virtual velocity. By realizing that the virtual velocities observed by different antennas are different, we adopt plane fitting to estimate the radial velocity, horizontal angular velocity, and pitch angular velocity of dynamic target. Furthermore, we implement the multiple-shots tracking of dynamic target based on each single-shot sensing results and Kalman filtering. Simulation results demonstrate the effectiveness of the proposed 6D radar sensing and tracking scheme.

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References (34)
  1. A. Hassanien, M. G. Amin, E. Aboutanios, and B. Himed, “Dual-function radar communication systems: A solution to the spectrum congestion problem,” IEEE Signal Process. Mag., vol. 36, no. 5, pp. 115–126, Sep. 2019.
  2. F. Liu, C. Masouros, A. P. Petropulu, H. Griffiths, and L. Hanzo, “Joint radar and communication design: Applications, state-of-the-art, and the road ahead,” IEEE Trans. Commun., vol. 68, no. 6, pp. 3834–3862, Feb. 2020.
  3. F. Liu, Y. Cui, C. Masouros, J. Xu, T. X. Han, Y. C. Eldar, and S. Buzzi, “Integrated sensing and communications: Toward dual-functional wireless networks for 6G and beyond,” IEEE J. Sel. Areas Commun., vol. 40, no. 6, pp. 1728–1767, Jun. 2022.
  4. M. Giordani, M. Polese, M. Mezzavilla, S. Rangan, and M. Zorzi, “Toward 6G networks: Use cases and technologies,” IEEE Commun. Mag., vol. 58, no. 3, pp. 55–61, Mar. 2020.
  5. Y. Cui, F. Liu, X. Jing, and J. Mu, “Integrating sensing and communications for ubiquitous IoT: Applications, trends, and challenges,” IEEE Network, vol. 35, no. 5, pp. 158–167, Nov. 2021.
  6. C. Chaccour, M. N. Soorki, W. Saad, M. Bennis, P. Popovski, and M. Debbah, “Seven defining features of terahertz (THz) wireless systems: A fellowship of communication and sensing,” IEEE Commun. Surveys Tuts., vol. 24, no. 2, pp. 967–993, Jan. 2022.
  7. Z. Wei, F. Liu, C. Masouros, N. Su, and A. P. Petropulu, “Toward multi-functional 6G wireless networks: Integrating sensing, communication, and security,” IEEE Commun. Mag., vol. 60, no. 4, pp. 65–71, Apr. 2022.
  8. S. Lu, F. Liu, and L. Hanzo, “The degrees-of-freedom in monostatic ISAC channels: NLoS exploitation vs. reduction,” IEEE Trans. Veh. Technol., vol. 72, no. 2, pp. 2643–2648, Feb. 2023.
  9. Z. Han, L. Han, X. Zhang, Y. Wang, L. Ma, M. Lou, J. Jin, and G. Liu, “Multistatic Integrated Sensing and Communication System in Cellular Networks,” arXiv e-prints, p. arXiv:2305.12994, May 2023.
  10. X. Chen, Z. Feng, Z. Wei, X. Yuan, P. Zhang, J. Andrew Zhang, and H. Yang, “Multiple signal classification based joint communication and sensing system,” IEEE Trans. Wireless Commun., pp. 1–1, 2023.
  11. W. Jiang, D. Ma, Z. Wei, Z. Feng, and P. Zhang, “ISAC-NET: Model-driven deep learning for integrated passive sensing and communication,” arXiv e-prints, p. arXiv:2307.15074, July 2023.
  12. F. Liu, W. Yuan, C. Masouros, and J. Yuan, “Radar-assisted predictive beamforming for vehicular links: Communication served by sensing,” IEEE Trans. Wireless Commun., vol. 19, no. 11, pp. 7704–7719, Nov. 2020.
  13. Z. Du, F. Liu, W. Yuan, C. Masouros, Z. Zhang, S. Xia, and G. Caire, “Integrated sensing and communications for v2i networks: Dynamic predictive beamforming for extended vehicle targets,” IEEE Trans. Wireless Commun., vol. 22, no. 6, pp. 3612–3627, Jun. 2023.
  14. S. Sun and Y. D. Zhang, “4D automotive radar sensing for autonomous vehicles: A sparsity-oriented approach,” IEEE J. Sel. Topics Signal Process., vol. 15, no. 4, pp. 879–891, Jun. 2021.
  15. M. Lei, D. Yang, and X. Weng, “Integrated sensor fusion based on 4D MIMO radar and camera: A solution for connected vehicle applications,” IEEE Veh. Technol. Mag., vol. 17, no. 4, pp. 38–46, Dec. 2022.
  16. J. A. Nanzer, “Millimeter-wave interferometric angular velocity detection,” IEEE Trans. Microw. Theory Techn., vol. 58, no. 12, pp. 4128–4136, Dec. 2010.
  17. J. A. Nanzer, K. Kammerman, and K. S. Zilevu, “A 29.5 GHz radar interferometer for measuring the angular velocity of moving objects,” in Proc. IEEE Int. Microwave Symp. Digest, pp. 1–3, Jun. 2013.
  18. J. A. Nanzer and K. S. Zilevu, “Time-frequency measurement of moving objects using a 29.5GHz dual interferometric-Doppler radar,” in Proc. IEEE Antennas and Propagation Soc. Int. Symp., pp. 830–831, Jul. 2013.
  19. J. A. Nanzer, “On the resolution of the interferometric measurement of the angular velocity of moving objects,” IEEE Trans. Antennas Propag., vol. 60, no. 11, pp. 5356–5363, Nov. 2012.
  20. X. Wang, P. Wang, and V. C. Chen, “Simultaneous measurement of radial and transversal velocities using a dual-frequency interferometric radar,” in Proc. IEEE RadarConf, pp. 1–6, Apr. 2019.
  21. X. Wang, P. Wang, and V. C. Chen, “Simultaneous measurement of radial and transversal velocities using interferometric radar,” IEEE Trans. Aerosp. Electron. Syst., vol. 56, no. 4, pp. 3080–3098, Aug. 2020.
  22. P. Wang, H. Liang, X. Wang, and E. Aboutanios, “Transversal velocity measurement of multiple targets based on spatial interferometric averaging,” in Proc. IEEE Int. Radar Conf. (RADAR), pp. 709–713, Apr. 2020.
  23. Z. Gao, Z. Wan, D. Zheng, S. Tan, C. Masouros, D. W. K. Ng, and S. Chen, “Integrated sensing and communication with mmWave massive MIMO: A compressed sampling perspective,” IEEE Trans. Wireless Commun., vol. 22, no. 3, pp. 1745–1762, Mar. 2023.
  24. H. Chen, H. Sarieddeen, T. Ballal, H. Wymeersch, M.-S. Alouini, and T. Y. Al-Naffouri, “A tutorial on terahertz-band localization for 6G communication systems,” IEEE Commun. Surveys Tuts., vol. 24, no. 3, pp. 1780–1815, May 2022.
  25. H. Luo, F. Gao, W. Yuan, and S. Zhang, “Beam squint assisted user localization in near-field integrated sensing and communications systems,” IEEE Trans. Wireless Commun., pp. 1–1, Oct. 2023.
  26. Z. Lin, T. Lv, J. A. Zhang, and R. P. Liu, “3D wideband mmwave localization for 5G massive MIMO systems,” in Proc. IEEE Global Commun. Conf. (GLOBECOM), Waikoloa, HI, USA, Dec. 2019, pp. 1–6.
  27. H. Luo, Y. Wang, J. Zhao, H. Wu, S. Ma, and F. Gao, “Integrated sensing and communications in clutter environment,” arXiv e-prints, p. arXiv:2311.01674, Nov. 2023.
  28. H. Luo, F. Gao, H. Lin, S. Ma, and H. V. Poor, “YOLO: An efficient terahertz band integrated sensing and communications scheme with beam squint,” arXiv e-prints, p. arXiv:2305.12064, May 2023.
  29. 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.
  30. R. Roy, A. Paulraj, and T. Kailath, “ESPRIT–a subspace rotation approach to estimation of parameters of cisoids in noise,” IEEE Trans. Acoust., Speech, Signal Process., vol. 34, no. 5, pp. 1340–1342, Oct. 1986.
  31. A. Paulraj, R. Roy, and T. Kailath, “Estimation of signal parameters via rotational invariance techniques- esprit,” in Nineteeth Asilomar Conference on Circuits, Systems and Computers, 1985., pp. 83–89, Nov. 1985.
  32. M. Wax and T. Kailath, “Detection of signals by information theoretic criteria,” IEEE Trans. Acoust., Speech, Signal Process., vol. 33, no. 2, pp. 387–392, Apr. 1985.
  33. A. Barron, J. Rissanen, and B. Yu, “The minimum description length principle in coding and modeling,” IEEE Trans. Inf. Theory, vol. 44, no. 6, pp. 2743–2760, Oct. 1998.
  34. Singapore: Springer Singapore, 2020.
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