استفاده از روش‌های مبتنی بر تکرار در رادار با ضربه و روزنه مصنوعی با چند ورودی – چند خروجی جهت تفکیک هدف از تصویر آن

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی دکتری، دانشگاه صنعتی شریف، تهران، ایران

2 استاد، دانشگاه صنعتی شریف، تهران، ایران

چکیده

تخمین زاویه ورود موج در حالت ارتفاع پست، یک مسئله چالشی در زمینه انواع رادار‌های آرایه فازی است. این مسئله به‌صورت کلی زمانی رخ می‌دهد که هدف در ارتفاع پست حرکت کرده و سیگنال دریافتی از خود هدف با سیگنال دریافتی از بازتاب آن از زمین، با یکدیگر و به‌صورت هم‌زمان وارد گیرنده شده و زاویه سنجی را خراب ‌کنند. خیلی از مقالات با استفاده از روش‌های تفکیک بسیار بالا (Super Resolution)، اقدام به بررسی و حل این مسئله در رادار‌های آرایه فازی کرده‌اند. در این مقاله به حل این مشکل در رادار‌های چند ورودی - چند خروجی می‌پردازیم. در این زمینه، تمرکز بر روی رادار‌های با ضربه و روزنه مصنوعی است. روش ارائه‌شده در اینجا، دارای دو گام است، ابتدا برد و زاویه سمت و حدود زاویه ارتفاع هدف با استفاده از فیلتر منطبق تخمین زده می‌شوند و سپس در اطراف زاویه ارتفاع تشخیص‌داده‌شده، با استفاده از روش پیشنهادی، به تفکیک هدف و تصویر از یکدیگر خواهیم پرداخت. منظور از تصویر یک هدف، بازتاب آن از سطح زمین است که باعث ایجاد هدف جعلی در گیرنده خواهد شد. نتایج به‌دست‌آمده نشان می‌دهند که روش پیشنهادی توانایی جداسازی مناسب هدف از تصویر آن را در شرایط مختلف داراست.

کلیدواژه‌ها


عنوان مقاله [English]

Using Iterative-Based Methods in Multiple-Input Multiple-Output Synthetic Aperture Radar for Target-Image Separation

نویسندگان [English]

  • Mohsen Pourjoula 1
  • Mohamad Mahdi Nayebi 2
  • mohammad karbasi 2
1 PhD student, Sharif University of Technology, Tehran, Iran
2 Professor, Sharif University of Technology, Tehran, Iran
چکیده [English]

Estimating the angle of arrival of waves in the low-altitude scenario is a challenging issue in the field of phased array radars. This problem generally occurs when a target moves at low altitude, and the signal received directly from the target coincides with the signal received from its reflection off the ground, simultaneously entering the receiver and disrupting the angle estimation. Many articles have investigated and addressed this issue in phased array radars using high-resolution separation methods. In this paper, we focus on solving this problem in multiple-input multiple-output radars. Specifically, we concentrate on impulse and synthetic aperture radars. The proposed method consists of two steps: first, the range, azimuth angle, and approximate elevation angle of the target are estimated using a matched filter; then, the proposed method is applied around the detected elevation angle to separate the target from its image. The term "image" refers to the reflection of a target from the ground surface, which creates a false target in the receiver. The results obtained demonstrate that the proposed method is capable of effectively separating the target from its image under various conditions.

کلیدواژه‌ها [English]

  • SIAR
  • MIMO
  • Super resolution
  • Low angle

Smiley face

  1. Fishler, A. Haimovich, R. Blum, D. Chizhik, L. Cimini, and R. Valenzuela, “MIMO radar: an idea whose time has come,” in Proceedings of the 2004 IEEE Radar Conference (IEEE Cat. No.04CH37509), 2004.
  2. Wasim, D. J. Malik, and C. J. Edwards, “Ultra wideband multiple-input multiple-output radar,” in IEEE International Radar Conference, IEEE, 2005, pp. 900–904.
  3. S. Bliss, “ultiple-input multiple-output (mimo) radar: Performance issues,” in Conference Record of the Thirty-Eighth Asilomar Conference on Signals, Systems and Computers, vol. 1, IEEE, 2004, pp. 310–315.
  4. S. Daniel and R. Fuhrmann, “Transmit beamforming for mimo radar systems using signal cross-correlation,” IEEE Transactions on Aerospace and Electronic Systems, vol. 44, no. 1, pp. 171–186, 2008.
  5. Frank, S. Robey, D. Coutts, C. Jeffrey, and K. Mcharg, “Mimo radar theory and experimental results,” in Conference Record of the Thirty-Eighth Asilomar Conference on Signals, Systems and Computers, vol. 1, IEEE, 2004, pp. 300–304.
  6. W. Bliss and K. W. Forsythe, “Multiple-input multiple-output (MIMO) radar and imaging: degrees of freedom and resolution,” in The Thrity-Seventh Asilomar Conference on Signals, Systems & Computers, 2003, 2004.
  7. Alexander, R. S. Haimovich, and L. J. Blum, “Mimo radar with widely separated antennas,” IEEE signal processing magazine, vol. 25, no. 1, pp. 116–129, 2007.
  8. Nikolaus et al., “Evaluation of transmit diversity in mimo-radar direction finding,” IEEE transactions on signal processing, vol. 55, no. 5, pp. 2215–2225, 2007.
  9. S. Daniel and R. Fuhrmann, “Transmit beamforming for mimo radar systems using partial signal correlation,” in Conference Record of the ThirtyEighth Asilomar Conference on Signals, Systems and Computers, vol. 1, IEEE, 2004, pp. 295–299.
  10. F. Sammartino, C. J. Baker and H. D. Griffiths, “Frequency Diverse MIMO Techniques for Radar,” IEEE Trans. Aerosp. Electron. Syst., vol. 49, no. 1, pp. 201–222, 2013.
  11. Chen and J. Wu, Synthetic impulse and aperture radar (SIAR): a novel multi-frequency MIMO radar. John Wiley & Sons, 2014.
  12. Y. Chen and P. P. Vaidyanathan, “MIMO radar space–time adaptive processing using prolate spheroidal wave functions,” IEEE Trans. Signal Process., vol. 56, no. 2, pp. 623–635, 2008.
  13. Xu, G. Liao, S. Zhu, L. Huang, and H. C. So, “Joint range and angle estimation using MIMO radar with frequency diverse array,” IEEE Trans. Signal Process., vol. 63, no. 13, pp. 3396–3410, 2015.
  14. Chen, M. Yang, Y. Wang, X. Dang, and B. Wu, “The applications and future of synthetic impulse and aperture radar,” in 2016 CIE International Conference on Radar (RADAR), 2016.
  15. Baixiao, Z. Shouhong, W. Yajun, and W. Jun, “Analysis and experimental results on sparse-array synthetic impulse and aperture radar,” in 2001 CIE International Conference on Radar Proceedings (Cat No.01TH8559), 2002.
  16. Wang, G. Zhou, and T. Kirubarajan, “Track-beforedetect technique in mixed coordinates,” in 21st International Conference on Information Fusion (FUSION), IEEE, 2018, pp. 1–6.
  17. Pal and P. P. Vaidyanathan, “Frequency invariant MVDR beamforming without filters and implementation using MIMO radar,” in 2009 IEEE International Conference on Acoustics, Speech and Signal Processing, 2009.
  18. Yasmine and M. Tabra, “Hybrid mvdr-lms beamforming for massive mimo,” Indonesian Journal of Electrical Engineering and Computer Science, vol. 16, no. 2, pp. 715–723, 2019.
  19. -W. Chen, C.-L. Meng, and A.-C. Chang, “DOA and DOD estimation based on double 1-D root-MVDR estimators for bistatic MIMO radars,” Wirel. Pers. Commun., vol. 86, no. 3, pp. 1321–1332, 2016.
  20. D. Naveen, N. Venkategowda, and A. K. Tandon, “Mvdrbased multicell cooperative beamforming techniques for unicast/multicast mimo networks with perfect/imperfect csi,” IEEE Transactions on Vehicular Technology, vol. 64, no. 11, pp. 5160–5176, 2014.
  21. -T. Chen, Y.-T. Hwang, and C.-Y. Huang, “Design and chip implementation of a SMI/MVDR dual-mode beamformer for wireless MIMO communication systems,” IEEE Access, vol. 8, pp. 67940–67954, 2020
  22. Hong, J. Li, Y. Ai, Y. Dong, Z. Zhao, and Y. Wang, “Biiterative mvdr beamforming based on beamspace preprocessing for mimo radars,” in 12th International Symposium on Antennas, Propagation and EM Theory (ISAPE), IEEE, 2018, pp. 1–4.
  23. L. Sit, C. Sturm, J. Baier, and T. Zwick, “Direction of arrival estimation using the MUSIC algorithm for a MIMO OFDM radar,” in 2012 IEEE Radar Conference, 2012.
  24. Li, X. Zhang, R. Cao, and M. Zhou, “Reduced-dimension MUSIC for angle and array gain-phase error estimation in bistatic MIMO radar,” IEEE Commun. Lett., vol. 17, no. 3, pp. 443–446, 2013
  25. Feng, Z. Cui, Y. Yang, and Q. Shu, “A reduced-dimension MUSIC algorithm for monostatic FDA-MIMO radar,” IEEE Commun. Lett., vol. 25, no. 4, pp. 1279–1282, 2021.
  26. Zheng, Y. Song, and C. Chen, “Height measurement with meter wave polarimetric MIMO radar: Signal model and MUSIC-like algorithm,” Signal Processing, vol. 190, no. 108344, p. 108344, 2022.
  27. Yardibi, J. Li, P. Stoica, M. Xue, and A. B. Baggeroer, “Source localization and sensing: A nonparametric iterative adaptive approach based on weighted least squares,” IEEE Trans. Aerosp. Electron. Syst., vol. 46, no. 1, pp. 425–443, 2010.
  28. Tang, J. Liu, H. Wang, and Y. Hu, “Constrained radar waveform design for range profiling,” IEEE Trans. Signal Process., vol. 69, pp. 1924–1937, 2021.
  29. Vahdani, R., H. Khaleghi, and M. Fallah. "Transmit Covariance Matrix Signal Design in Correlated MIMO Radar with High Probability in Target Detection." Radar. Vol. 8. No. 1. pp.15-20. 2020.https://dor.isc.ac/dor/20.1001.1.23454024.1399.8.1.2.7
  30. Zarie, Majid, et al. "Improvement of Positioning in MIMO Radar Using Prior Information." Radar. Vol. 7. No. 1. pp.93-101, 2019.https://dor.isc.ac/dor/20.1001.1.23454024.1398.7.1.8.6
  31. Masnadi, Shirazi MA. "A Comparison of the Tracking Performance of Cognitive Co-Located MIMO and Phased-Array Radars." Vol.5.No.3, (2017): 51-60.https://dor.isc.ac/dor/20.1001.1.23454024.1396.5.3.5.3
  32. Moghaddasi, S. A., H. Khaleghi, and M. Fallah. "Beam pattern design in phased MIMO radars for known target locations." Journal Of Radar, Vol.3,No4. (2016): 25-32.
دوره 10، شماره 2 - شماره پیاپی 28
شماره پیاپی 28، فصلنامه پاییز و زمستان
دی 1401
صفحه 31-38
  • تاریخ دریافت: 02 آبان 1401
  • تاریخ بازنگری: 23 آذر 1401
  • تاریخ پذیرش: 10 دی 1401
  • تاریخ انتشار: 01 بهمن 1401