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access icon free Extraction of Doppler signature of micro-to-macro rotations/motions using continuous wave radar-assisted measurement system

© The Institution of Engineering and Technology
Received 12/10/2018, Accepted 09/03/2020, Revised 21/11/2019, Published 12/03/2020

Mechanical–structural vibration and/or rotational parts of the targets will induce micro-Doppler frequency in addition to the main Doppler components. In the today's military era, detections, measurements and decision making have to be made after the thorough analysis of main and micro-Doppler signatures of the targets to get their full profile particularly for defence applications. In addition, few of the low radar cross-section targets can be detected only by extracting and processing the micro-Doppler signatures corresponding to the rotations of their propellant rotor blades. Therefore, experimental studies to measure the micro-to-macro rotation/motion generated Doppler frequency and performing its associated measurements become significant. The authors built a C-band (5.3 GHz) continuous wave radar and used it to measure the Doppler frequency generated by micro-to-macro rotations/motions. The detection and measurement accuracy of the developed radar is assessed by series of different open-environment experimental case studies: revolution per minute measurement of rotating blades, separation of multiple rotating blades, oscillation per minute measurement of a swinging pendulum, detection of approaching/receding motion and the Doppler signature extraction of walking/jogging/cycling person. All these measurement values are validated against the standard master instrument readings and theoretical calculations. Finally, the limitations of this system and required near-future research works to enhance its performance are listed.

Inspec keywords: microwave measurement; frequency measurement; blades; motion measurement; rotation measurement; CW radar; Doppler radar; microwave detectors; radar detection

Other keywords: multiple rotating blades; standard master instrument readings; approaching-receding motion detection; micro-to-macro rotation-motion; frequency 5.3 GHz; mechanical–structural vibration; swinging pendulum measurement; continuous wave radar-assisted measurement system; microDoppler signature extraction; decision making; defence applications; low radar cross-section targets; Doppler signature extraction; microDoppler frequency measurement

Subjects: Microwave circuits and devices; Sensing and detecting devices; Signal detection; Frequency measurement; Microwave measurement techniques; Velocity, acceleration and rotation measurement; Spatial variables measurement; Velocity, acceleration and rotation measurement; Radar equipment, systems and applications; Time and frequency measurement; Sensing devices and transducers; Spatial variables measurement

References

    1. 1)
      • 22. Rahman, A., Lubecke, V., Yavari, E., et al: ‘High dynamic range DC coupled CW Doppler radar for accurate respiration characterization and identification’. 89th ARFTG Microwave Measurement Conf. (ARFTG), Honololu, HI, USA, June 2017.
    2. 2)
      • 18. Narayanan, R.M., Zenaldin, M.: ‘Radar micro-Doppler signatures of various human activities’, IET Radar Sonar Navig., 2015, 9, (9), pp. 1202–1215.
    3. 3)
      • 4. Ding, Y., Tang, J.: ‘Micro-Doppler trajectory estimation of pedestrians using a continuous-wave radar’, IEEE Trans. Geosci. Remote Sens., 2014, 52, (9), pp. 5807–5819.
    4. 4)
      • 26. Raja Abdullah, R.S.A., Salah, A.A., Alnaeb, A.A., et al: ‘Micro-Doppler detection in forward scattering radar: theoretical analysis and experiment’, Electron. Lett., 2017, 53, (6), pp. 426–428.
    5. 5)
      • 21. Wang, Y., Liu, Q., Fathy, A.E.: ‘CW and pulse–Doppler radar processing based on FPGA for human sensing applications’, IEEE Trans. Geosci. Remote Sens., 2013, 51, (5), pp. 3097–3107.
    6. 6)
      • 33. Anthonisamy, A.B.A., Durairaj, P., Paul, L.J.: ‘Performance analysis of free space optical communication in open-atmospheric turbulence conditions with beam wandering compensation control’, IET Commun., 2016, 10, (9), pp. 1096–1103.
    7. 7)
      • 9. Chen, V.C., Li, F., Ho, S.-S., et al: ‘Analysis of micro-Doppler signatures’, IEE Proc. Radar Sonar Navig., 2003, 150, (4), pp. 271–276.
    8. 8)
      • 35. Raj, A.A., Vijaya Selvi, J.A., Kumar, D., et al: ‘Mitigation of beam fluctuation due to atmospheric turbulence and prediction of control quality using intelligent decision-making tools’, Appl. Opt., 2014, 53, (17), pp. 3796–3806.
    9. 9)
      • 16. Muñoz-Ferreras, J.M., Peng, Z., Tang, Y.: ‘Short-range Doppler-radar signatures from industrial wind turbines: theory, simulations and measurements’, IEEE Trans. Instrum. Meas., 2016, 65, (9), pp. 2108–2119.
    10. 10)
      • 12. Tivive, F.H.C., Phung, S.L., Bouzerdoum, A.: ‘Classification of micro-Doppler signatures of human motions using log-Gabor filters’, IET Radar Sonar Navig., 2015, 9, (9), pp. 1188–1195.
    11. 11)
      • 20. Singh, A.K., Kim, Y.H.: ‘Automatic measurement of blade length and rotation rate of drone using W-band micro-Doppler radar’, IEEE Sens. J., 2018, 18, (5), pp. 1895–1902.
    12. 12)
      • 31. Bazil Raj, A.A., Vijaya Selvi, J.A., Raghavan, S.: ‘Real-time measurement of meteorological parameters for estimating low altitude atmospheric turbulence strength (Cn2)’, IET Sci. Meas. Technol., 2014, 8, (6), pp. 459–469.
    13. 13)
      • 13. Ritchie, M., Fioranelli, F., Borrion, H., et al: ‘Multistatic micro-Doppler radar feature extraction for classification of unloaded/loaded micro-drones’, IET Radar Sonar Navig.., 2017, 11, (1), pp. 116–124.
    14. 14)
      • 7. Roberto, R., Balleri, A.: ‘Recognition of humans based on radar micro-Doppler shape spectrum features’, IET Radar Sonar Navig., 2015, 9, (9), pp. 1216–1223.
    15. 15)
      • 25. Zuo, L., Li, M., Zhang, X., et al: ‘Two helicopter classification methods with a high pulse repetition frequency radar’, IET Radar Sonar Navig., 2013, 7, (3), pp. 312–320.
    16. 16)
      • 37. Bazil Raj, A.A., Vijaya Selvi, J.A., Kumar, D., et al: ‘A direct and neural controller performance study with beam wandering mitigation control in free space optical link’, Opt. Memory Neural Netw. (Inf. Opt.), 2014, 23, (3), pp. 111–129.
    17. 17)
      • 14. Wu, J., Zuo, L., Li, M.: ‘Micro-Doppler of helicopter with different blade shapes’, Electron. Lett., 2018, 54, (17), pp. 1053–1054.
    18. 18)
      • 6. Vignaud, L., Ghaleb, A., Le Kernec, J., et al: ‘Radar high resolution range & micro-Doppler analysis of human motions’. Int. Radar Conf. ‘Surveillance for a Safer World’, Bordeaux, France, October 2009.
    19. 19)
      • 5. Misans, P., Terauds, M.: ‘CW Doppler radar based land vehicle speed measurement algorithm using zero crossing and least squares method’. 13th Biennial Baltic Electronics Conf., Tallinn, Estonia, October 2012, pp. 161–164.
    20. 20)
      • 34. Bazil Raj, A.A., Vijaya Selvi, J.A., Durai, K.D., et al: ‘Intensity feedback-based beam wandering mitigation in free-space optical communication using neural control technique’, EURASIP J. Wirel. Commun. Netw., 2014, 160, (1), pp. 1–18.
    21. 21)
      • 28. Karabacak, C., Gurbuz, S.Z., Gurbuz, A.C., et al: ‘Knowledge exploitation for human micro-Doppler classification’, IEEE Geosci. Remote Sens. Lett., 2015, 12, (10), pp. 2125–2129.
    22. 22)
      • 27. Singh, A.K., Kim, Y.H.: ‘Analysis of human kinetics using millimeter-wave micro-Doppler radar’, Procedia Comput. Sci., 2016, 84, pp. 36–40.
    23. 23)
      • 24. Available at https://people.wku.edu/david.neal/117/Unit2/AngVel.pdf.
    24. 24)
      • 17. Li, C.J., Bhalla, R., Ling, H.: ‘Investigation of the dynamic radar signatures of a vertical-axis wind turbine’, IEEE Antenna Wirel. Propag. Lett., 2015, 14, pp. 763–766.
    25. 25)
      • 11. Kim, Y., Ha, S., Kwon, J.: ‘Human detection using Doppler radar based on physical characteristics of targets’, IEEE Geosci. Remote Sens. Lett., 2015, 12, (2), pp. 289–293.
    26. 26)
      • 36. Raj, A.A., Selvi, J.A., Kumar, D., et al: ‘Design of cognitive decision making controller for autonomous online adaptive beam steering in free space optical communication system’, Wirel. Pers. Commun., 2015, 84, (1), pp. 765–799.
    27. 27)
      • 32. Bazil Raj, A.A., Darusalam, U.: ‘Performance improvement of terrestrial free-space optical communications by mitigating the focal-spot wandering’, J. Mod. Opt., 2016, 63, pp. 2339–2347.
    28. 28)
      • 38. Bazil Raj, A.A.: ‘Mono-pulse tracking system for active free space optical communication’, Optik – Int. J. Light Electr. Opt., 2016, 127, (19), pp. 7752–7761.
    29. 29)
      • 1. Skolnik, M.I.: ‘Introduction to radar system’ (McGraw Hill Education, New York, 2001, 3rd edn.).
    30. 30)
      • 29. Available at https://en.wikipedia.org/wiki/Pendulum.
    31. 31)
      • 39. Kumawat, H.C., Bazil Raj, A.A.: ‘Data acquisition and signal processing system for CW radar’. 5th Int. Conf. on Computing Communication Control and Automation (ICCUBEA), Pune, India, September 2019.
    32. 32)
      • 2. Charvat, G.L.: ‘Small and short-range radar systems’ (CRC Press, USA, 2014).
    33. 33)
      • 10. Fei, L., Binke, H., Hang, Z., et al: ‘Human gait recognition using micro-Doppler features’. 5th Global Symp. on Millimeter-Waves, Harbin, China, May 2012, pp. 331–335.
    34. 34)
      • 23. Bazil Raj, A.A.: ‘FPGA- based embedded system developer's guide’ (CRC Press, USA, 2018).
    35. 35)
      • 15. Gurbuz, S.Z., Clemente, C., Balleri, A., et al: ‘Micro-Doppler-based in-home aided and unaided walking recognition with multiple radar and sonar systems’, IET Radar Sonar Navig., 2017, 11, (1), pp. 107–115.
    36. 36)
      • 3. Ritchie, M., Fioranelli, F., Balleri, A., et al: ‘Measurement and analysis of multiband bistatic and monostatic radar signatures of wind turbines’, Electron. Lett., 2015, 51, (14), pp. 1112–1113.
    37. 37)
      • 8. Ding, Y., Lei, C., Xu, X., et al: ‘Human micro-Doppler frequency estimation approach for Doppler radar’, IEEE Access, 2018, 6, pp. 6149–6159.
    38. 38)
      • 30. Yamamota, K., Toyoda, K., Ohtsuki, T.: ‘Spectrogram-based non-contact RRI estimation by accurate peak detection algorithm’, IEEE Access, 2018, 6, pp. 60369–60379.
    39. 39)
      • 19. Reznicek, M.: ‘Doppler CW radar signal processing, implementation and analysis’. 59thInt. Symp. ELMAR, Zadar, Croatia, September 2017, pp. 103–106.
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