Human micro-doppler detection and classification studies at Mersin University using real outdoor experiments via C-band FMCW radar

Yıl 2024, , 211 - 220, 28.07.2024

Onur Tekir , Caner Özdemir

https://doi.org/10.26833/ijeg.1380658

Öz

In this work, a unique radar hardware is introduced for human-gait micro-Doppler studies. The developed radar sensor operates in C-band microwave frequencies. We share several outdoor experiments at Mersin University facilities to detect and characterize human walking and running movements. In these experiments, various walking and running movements were performed with different people. To examine the Doppler properties of human motion, raw data gathered is transformed onto 2D joint-time-frequency plane. The generation of micro-Doppler signatures in the transformed data is the first step in the extraction of features of the walking/running human motion. It is shown that the directions, durations, range distances as well as torso and limb velocities of walking and running human movements in each experiment are successfully obtained from these micro-Doppler signatures.

Anahtar Kelimeler

Micro-doppler radar, Radar imaging, Spectrogram, Human detection and classification

Etik Beyan

The authors declare that there is no conflict of interests regarding the publication of this paper.

Destekleyen Kurum

Mersin University Scientific Research Unit

Proje Numarası

Mersin University Scientific Research Unit under Project No. 2018-2-TP3-2924.

Teşekkür

Authors would like to thank Gökhan Karabacak for his help during experiments.

Kaynakça

• Ağca, M. (2020). PALS, ICESat/GLAS ve ICESat-2 lazer sistemleri ve kullanım alanları. Geomatik, 5(1), 27-35. https://doi.org/10.29128/geomatik.560344
• Navruz, M. (2017). Airborne LİDAR Ve Dted2 verilerinde yükseklik (H) karşılaştırması. Geomatik, 2(3), 112-117. https://doi.org/10.29128/geomatik.319270
• Sevgen, S. C., & Karsli, F. (2020). Automatic ground extraction for urban areas from airborne lidar data. Turkish Journal of Engineering, 4(3), 113-122. https://doi.org/10.31127/tuje.641501
• Yılmaz, B., & Özdemir, C. (2017). Design and prototype of a compact, ultra wide band double ridged horn antenna for behind obstacle radar applications. Turkish Journal of Engineering, 1(2), 76-81. https://doi.org/10.31127/tuje.316696
• Demirci, Ş., & Özdemir, C. (2021). An investigation of the performances of polarimetric target decompositions using GB-SAR imaging. International Journal of Engineering and Geosciences, 6(1), 9-19. https://doi.org/10.26833/ijeg.665175
• Demirci, Ş., & Özdemir, C. (2020). Anechoic chamber measurements for circular isar imaging at Mersin University’s Meatrc Lab. International Journal of Engineering and Geosciences, 5(3), 150-159. https://doi.org/10.26833/ijeg.649961
• Akgül, M. A. (2018). Sentetik açıklıklı radar verilerinin taşkın çalışmalarında kullanılması: Berdan Ovası Taşkını. Geomatik, 3(2), 154-162. https://doi.org/10.29128/geomatik.378123
• Özdemir, C. (2020). Radar cross section analysis of unmanned aerial vehicles using predics. International Journal of Engineering and Geosciences, 5(3), 144-149. https://doi.org/10.26833/ijeg.648847
• Gurbuz, S. Z., Melvin, W. L., & Williams, D. B. (2011). A nonlinear-phase model-based human detector for radar. IEEE Transactions on Aerospace and Electronic Systems, 47(4), 2502-2513. https://doi.org/10.1109/TAES.2011.6034647
• Ozdemir, C. (2021). Inverse synthetic aperture radar imaging with MATLAB algorithms. John Wiley & Sons.
• Chen, V. C. (2019). The micro-Doppler effect in radar. Artech house.
• Kim, Y., & Ling, H. (2009). Human activity classification based on micro-Doppler signatures using a support vector machine. IEEE Transactions on Geoscience and Remote Sensing, 47(5), 1328-1337. https://doi.org/10.1109/TGRS.2009.2012849
• Heuel, S., & Rohling, H. (2012, May). Pedestrian classification in automotive radar systems. 13th International Radar Symposium, 39-44. https://doi.org/10.1109/IRS.2012.6233285
• van Dorp, P., & Groen, F. C. (2010). Human motion estimation with multiple frequency modulated continuous wave radars. IET Radar, Sonar & Navigation, 4(3), 348-361. https://doi.org/10.1049/iet-rsn.2009.0015
• Chen, V. C., & Ling, H. (2002). Time-frequency transforms for radar imaging and signal analysis. Artech house.
• Hurmuzlu, Y., Basdogan, C., & Carollo, J. J. (1994). Presenting joint kinematics of human locomotion using phase plane portraits and Poincaré maps. Journal of Biomechanics, 27(12), 1495-1499. https://doi.org/10.1016/0021-9290(94)90199-6
• Boulic, R., Thalmann, N. M., & Thalmann, D. (1990). A global human walking model with real-time kinematic personification. The Visual Computer, 6, 344-358. https://doi.org/10.1007/BF01901021
• Boulic, R., Ulicny, B., & Thalmann, D. (2004). Versatile walk engine. Journal of Game Development, 1(1), 29-50.
• Chen, V. C. (2000). Analysis of radar micro-Doppler with time-frequency transform. In Proceedings of the Tenth IEEE Workshop on Statistical Signal and Array Processing (Cat. No. 00TH8496), 463-466. https://doi.org/10.1109/SSAP.2000.870167
• Geisheimer, J. L., Greneker III, E. F., & Marshall, W. S. (2002). High-resolution Doppler model of the human gait. In Radar Sensor Technology and Data Visualization, 4744, 8-18. https://doi.org/10.1117/12.488286
• Tekir, O., Yılmaz, B., & Özdemir, C. (2023). Signal preprocessing routines for the detection and classification of human micro‐Doppler radar signatures. Microwave and Optical Technology Letters, 65(8), 2132-2149. https://doi.org/10.1002/mop.33684
• Persico, A. R., Clemente, C., Gaglione, D., Ilioudis, C. V., Cao, J., Pallotta, L., ... & Soraghan, J. J. (2017). On model, algorithms, and experiment for micro-Doppler-based recognition of ballistic targets. IEEE Transactions on Aerospace and Electronic Systems, 53(3), 1088-1108. https://doi.org/10.1109/TAES.2017.2665258
• Ozdemir, C., & Ling, H. (1997). Joint time-frequency interpretation of scattering phenomenology in dielectric-coated wires. IEEE Transactions on Antennas and Propagation, 45(8), 1259-1264. https://doi.org/10.1109/8.611245