Building a baseband signal processing algorithm for unmanned aerial vehicle detection radar
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https://doi.org/10.54939/1859-1043.j.mst.85.2023.18-25Keywords:
UAV detection radar; Continuous linear frequency modulation (FMCW); Baseband signal processor; Micro Doppler signature; FPGA; ZynQ Z-7045.Abstract
In this paper, the construction of a baseband signal processing algorithm for unmanned aerial vehicle (UAV) detection radar by using continuous linear frequency modulation (FMCW) signal is presented. On the basis of the built algorithm, the article presents the contents of simulation research in Matlab environment, and conducts experimental research by designing and deploying signal processors on the technology platform FPGA. The results of the study show that FMCW radar can be used to distinguish UAV targets from normal targets by the micro Dopple signature. The signal processor is the basis for building a complete UAV detection radar in the future.
References
[1]. Florin-Lucian Chiper, Alexandru Martian, “Drone Detection and Defense Systems: Survey and a Software-Defined Radio-Based Solution”, Sensors (2022).
[2]. M. Nijim and N. Mantrawadi, “Drone Classification and Identification System by Phenome Analysis Using Data Mining Techniques,” 2016 IEEE Symp. Technologies for Homeland Security, pp. 1–5, (2016). DOI: https://doi.org/10.1109/THS.2016.7568949
[3]. M. A. Ma’sum et al., “Simulation of Intelligent Unmanned Aerial Vehicle (UAV) for Military Surveillance” 2013 Int’l. Conf. Advanced Computer Science and Inf. Systems, pp. 161–66, (2013). DOI: https://doi.org/10.1109/ICACSIS.2013.6761569
[4]. Blyakhman A.B., Burov V.N., Myakinkov A.V. & Ryndyk A.G. “Detection of unmanned aerial vehicles via multistatic forward scattering radar with airborne transmit positions”. Int. Radar Conf, (2014). DOI: https://doi.org/10.1109/RADAR.2014.7060334
[5]. Krátký, M. & Fuxa, L. (2015). “Mini UAVs Detection by Radar”. IEEE Conf. Pub., pp. 1–5, (2014). DOI: https://doi.org/10.1109/MILTECHS.2015.7153647
[6]. Ochodnický, J., Matousek, Z., Babjak, M., & Kurty, J. “Drone detection by Ku-band battlefield radar”. Int. Conf. Military Tech. (ICMT), pp. 613–616, (2017). DOI: https://doi.org/10.1109/MILTECHS.2017.7988830
[7]. Rzewuski, S., Kulpa, K., Member, S., Salski, B., Kopyt, P., Borowiec, K. & Member, S. (2018). “Drone RCS estimation using simple experimental measurement in the WIFI band". 22nd Int. Microwave Radar Conf. (MIKON). pp. 695–698, (2018). DOI: https://doi.org/10.23919/MIKON.2018.8405329
[8]. Nuss, B., Sit, L., Fennel, M., Mayer, J., Mahler, T. & Zwick, T. “MIMO OFDM radar system for drone detection.” 18th Int. Radar Symp. IEEE Conf. Pub., pp. 1–9, (2017). DOI: https://doi.org/10.23919/IRS.2017.8008141
[9]. Jian, M., Lu, Z. & Chen, V. C. (2018). “Drone detection and tracking based on phase-interferometric Doppler radar”. 2018 IEEE Radar Conf., pp. 1146–1149, 2018. DOI: https://doi.org/10.1109/RADAR.2018.8378723
[10]. Yang, X., Huo, K., Jiang, W., Zhao, J. & Qiu, Z. “A passive radar system for detecting UAV based on the OFDM communication signal”. Prog. Electromag. Research Sympo., (PIERS) Proc. 2016. pp. 2757–2762, (2016).
[11]. Gaigals, G., Vavilina, E. & Carlo, M. “Simulation of compressed sensing based passive radar for drone detection”. 5th IEEE Workshop Adv. Infor. Elect. Elect. Engr. (AIEEE), 2017. pp. 1–5, (2017). DOI: https://doi.org/10.1109/AIEEE.2017.8270552
[12]. Sung, J. L., Jae, H. J. & Bonghyuk, P. “Possibility verification of drone detection radar based on pseudo random binary sequence”. IEEE Conf. Pub., pp. 291–292, (2016).
[13]. M.Jankiraman, “FMCW radar design”, Artech House (2018).
[14]. Pasi Koivumäki, Aalto university, “Triangular and Ramp Waveforms in Target Detection with a Frequency Modulated Continuous Wave Radar”, (2017).
[15]. Victor C.Chen, Hao Ling, “Time-Frequency Transforms for Radar Imaging and Signal Analysis” Artech House (2002).