2D Millimeter-Wave SAR Imaging with Automotive Radar

Yıl 2024, , 68 - 77, 21.06.2024

Bengisu Yalçınkaya Gökdoğan , Remziye Büşra Çoruk , Elif Aydın , Ali Kara

https://doi.org/10.53525/jster.1456610

Öz

In recent years, millimeter wave (mmWave) frequency modulated continuous wave (FMCW) radars have gained popularity in radar imaging applications, coinciding with the advancement of mmWave technology. However, high cost and integration complexity still remain as issues in cases where the target aperture is large. This work introduces a low-cost, low-complexity, and easy-to-implement two-dimensional (2D) mmWave synthetic aperture radar (SAR) system. A commercial-off-the-shelf (COTS) mmWave FMCW radar sensor operating in the frequency range of 77-81 GHz is employed. A large mechanical scanning system which can move in both vertical and horizontal directions is constructed and integrated with the radar sensor. Developing a graphical user interface (GUI), an automatic movement of the scanner is achieved. Experimental measurements are taken in a laboratory environment and the effectiveness of the system is demonstrated. A cross-shaped metal object and a drone are chosen as targets and the SAR images of targets are obtained. For simplicity, by employing a single transceiver pair, sparse samples are taken in a large scanning aperture. It has been shown that the proposed scanning system has great potential in SAR imaging of large objects such as unmanned aerial vehicles (UAV).

Anahtar Kelimeler

mmWave, frequency modulated continuous wave radar, synthetic aperture radar, sar imaging, drone, unmanned aerial vehicle

Etik Beyan

In the studies carried out within the scope of this article, the rules of research and publication ethics were followed.

Teşekkür

The authors would like to thank the students of Gazi University Furkan Çetinkaya, Erencan Tezel, Oğuz Yalçın, and Berkan Öksüz for their contribution to the construction of the SAR scanner.

Otomotiv Radarı ile 2 Boyutlu Milimetre Dalga SAR Görüntüleme

Öz

Son yıllarda, milimetre dalga (mmWave) frekans modülasyonlu sürekli dalga (FMCW) radarları, mmWave teknolojisinin gelişmesiyle paralel olarak radar görüntüleme uygulamalarında popülerlik kazanmıştır. Ancak hedef açıklığının büyük olduğu durumlarda yüksek maliyet ve entegrasyon karmaşıklığı hala sorun olmaya devam etmektedir. Bu çalışma, düşük maliyetli, düşük karmaşıklığa sahip ve uygulaması kolay iki boyutlu (2D) mmWave sentetik açıklıklı radar (SAR) sistemini tanıtmaktadır. 77-81 GHz frekans aralığında çalışan ticari kullanıma hazır (COTS) mmWave FMCW radar sensörü kullanılmaktadır. Hem dikey hem de yatay yönde hareket edebilen büyük bir mekanik tarama sistemi oluşturulmuş ve radar sensörüne entegre edilmiştir. Grafiksel bir kullanıcı arayüzü (GUI) geliştirerek tarayıcının otomatik hareketi sağlanır. Laboratuvar ortamında deneysel ölçümler alınarak sistemin etkinliği ortaya konulur. Hedef olarak artı şeklinde bir metal nesne ve bir drone seçilerek hedeflerin SAR görüntüleri elde edilmektedir. Basitlik açısından, tek bir alıcı-verici çifti kullanılarak, geniş bir tarama açıklığında seyrek örnekler alınır. Önerilen tarama sisteminin insansız hava araçları (İHA) gibi büyük nesnelerin SAR görüntülemesinde büyük potansiyele sahip olduğu gösterilmiştir.

Anahtar Kelimeler

milimetre dalga, frekans modüleli sürekli dalga radarı, sentetik açıklıklı radar, SAR görüntüleme, drone, insansız hava aracı

Kaynakça

• [1] Wellig, P., Speirs, P., Schuepbach, C., Oechslin, R., Renker, M., Boeniger, U., & Pratisto, H. (2018, June). Radar systems and challenges for C-UAV. In 2018 19th International Radar Symposium (IRS) (pp. 1-8). IEEE.
• [2] Mirbeik-Sabzevari, A., Li, S., Garay, E., Nguyen, H. T., Wang, H., & Tavassolian, N.(2018). Synthetic ultra-high-resolution millimeter-wave imaging for skin cancer detection. IEEE Transactions on biomedical engineering, 66(1), 61-71.
• [3] Ghasr, M. T., Kharkovsky, S., Bohnert, R., Hirst, B., & Zoughi, R. (2013). 30 GHz linear high-resolution and rapid millimeter wave imaging system for NDE. IEEE Transactions on Antennas and Propagation, 61(9), 4733-4740.
• [4] Liu, T., Zhao, Y., Wei, Y., Zhao, Y., & Wei, S. (2019). Concealed object detection for activate millimeter wave image. IEEE Transactions on Industrial Electronics, 66(12), 9909-9917.
• [5] Song, S., Lu, J., Xing, S., Quan, S., Wang, J., Li, Y., & Lian, J. (2022). Near Field 3-D Millimeter-Wave SAR Image Enhancement and Detection with Application of Antenna Pattern Compensation. Sensors, 22(12), 4509.
• [6] Zhuge, X., & Yarovoy, A. G. (2010). A sparse aperture MIMO-SAR-based UWB imaging system for concealed weapon detection. IEEE Transactions on Geoscience and Remote Sensing, 49(1), 509-518.
• [7] Sheen, D. M., McMakin, D. L., & Hall, T. E. (2001). Three-dimensional millimeter-wave imaging for concealed weapon detection. IEEE Transactions on microwave theory and techniques, 49(9), 1581-1592.
• [8] Abbasi, M., Shayei, A., Shabany, M., & Kavehvash, Z. (2018). Fast Fourier-based implementation of synthetic aperture radar algorithm for multistatic imaging system. IEEE Transactions on Instrumentation and Measurement, 68(9), 3339-3349.
• [9] Yanik, M. E., & Torlak, M. (2019). Near-field MIMO-SAR millimeter-wave imaging with sparsely sampled aperture data. Ieee Access, 7, 31801-31819.
• [10] Venon, A., Dupuis, Y., Vasseur, P., & Merriaux, P. (2022). Millimeter wave FMCW radars for perception, recognition and localization in automotive applications: A survey. IEEE Transactions on Intelligent Vehicles, 7(3), 533-555.
• [11] Zhao, Y., Sark, V., Krstic, M., & Grass, E. (2021, October). Multi-Target Vital Signs Remote Monitoring Using mmWave FMCW Radar. In 2021 IEEE Microwave Theory and Techniques in Wireless Communications (MTTW) (pp. 290-295). IEEE.
• [12] Chen, Y. S., Cheng, K. H., Xu, Y. A., & Juang, T. Y. (2022). Multi-Feature Transformer-Based Learning for Continuous Human Motion Recognition with High Similarity Using mmWave FMCW Radar. Sensors, 22(21), 8409.
• [13] Smith, J. W., & Torlak, M. (2022). Efficient 3-D near-field MIMO-SAR imaging for irregular scanning geometries. IEEE Access, 10, 10283-10294.
• [14] Zhang, B., Xu, G., Zhou, R., Zhang, H., & Hong, W. (2022). Multi-channel back-projection algorithm for mmwave automotive MIMO SAR imaging with Doppler-division multiplexing. IEEE Journal of Selected Topics in Signal Processing.
• [15] Yanik, M. E., Wang, D., & Torlak, M. (2020). Development and demonstration of MIMO-SAR mmWave imaging testbeds. IEEE Access, 8, 126019-126038.
• [16] Yanik, M. E., Wang, D., & Torlak, M. (2019, November). 3-D MIMO-SAR imaging using multi-chip cascaded millimeter-wave sensors. In 2019 IEEE global conference on signal and information processing (GlobalSIP) (pp. 1-5). IEEE.
• [17] Batra, A., Hark, T., Schorlemer, J., Pohl, N., Rolfes, I., Wiemeler, M., ... & Barowski, J. (2022, July). Fusion of optical and millimeter wave sar sensing for object recognition in indoor environment. In 2022 Fifth International Workshop on Mobile Terahertz Systems (IWMTS) (pp. 1-5). IEEE.
• [18] Doğanay, B., Arslan, M., Demir, E. C., Çoruk, R. B., Gökdoğan, B. Y., & Aydin, E. (2022, May). UAV Detection and Ranging with 77-81 GHz FMCW Radar. In 2022 30th Signal Processing and Communications Applications Conference (SIU) (pp. 1-4). IEEE.
• [19] Drozdowicz, J., Wielgo, M., Samczynski, P., Kulpa, K., Krzonkalla, J., Mordzonek, M., ... & Jakielaszek, Z. (2016, May). 35 GHz FMCW drone detection system. In 2016 17th International Radar Symposium (IRS) (pp. 1-4). IEEE.
• [20] Zulkifli, S., & Balleri, A. (2020, September). Design and development of K-band FMCW radar for nano-drone detection. In 2020 IEEE Radar Conference (RadarConf20) (pp. 1-5). IEEE.
• [21] Yanik, M. E., & Torlak, M. (2018). Millimeter-wave near-field imaging with two-dimensional SAR data. Proc. SRC Techcon, (P093929).
• [22] Hao, Z., Wang, R., Peng, J., & Dang, X. (2023). Static Hand Gesture Recognition Based on Millimeter-Wave Near-Field FMCW-SAR Imaging. Electronics, 12(19), 4013.
• [23] Zhuge, X., & Yarovoy, A. G. (2012). Three-dimensional near-field MIMO array imaging using range migration techniques. IEEE Transactions on Image Processing, 21(6), 3026-3033.
• [24] Patole, S., & Torlak, M. (2013). Two dimensional array imaging with beam steered data. IEEE transactions on image processing, 22(12), 5181-5189.