Browse > Article
http://dx.doi.org/10.6109/jkiice.2021.25.3.456

Adaptive CFAR implementation of UWB radar for collision avoidance in swarm drones of time-varying velocities  

Lee, Sae-Mi (Department of Electronic and Information Engineering, Korea aerospace university)
Moon, Min-Jeong (Department of Electronic and Information Engineering, Korea aerospace university)
Chun, Hyung-Il (Department of Electronic and Information Engineering, Korea aerospace university)
Lee, Woo-Kyung (Department of Electronic and Information Engineering, Korea aerospace university)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.25, no.3, 2021 , pp. 456-463 More about this Journal
Abstract
In this paper, Ultra Wide-Band(UWB) radar sensor is employed to detect flying drones and avoid collision in dense clutter environments. UWB signal is preferred when high resolution range measurement is required for moving targets. However, the time varying motion of flying drones may increase clutter noises in return signals and deteriorates the target detection performance, which lead to the performance degradation of anti-collision radars. We adopt a dynamic clutter suppression algorithm to estimate the time-varying distances to the moving drones with enhanced accuracy. A modified Constant False Alarm Rate(CFAR) is developed using an adaptive filter algorithm to suppress clutter while the false detection performance is well maintained. For this purpose, a velocity dependent CFAR algorithm is implemented to eliminate the clutter noise against dynamic target motions. Experiments are performed against flying drones having arbitrary trajectories to verify the performance improvement.
Keywords
Clutter rejection; UWB radar; LMS filter; Velocity dependent CFAR; Drone detection;
Citations & Related Records
연도 인용수 순위
  • Reference
1 J. Drozdowicz, M. Wielgo, P. Samczynski, K. Kulpa, J. Krzonkalla, M. Mordzonek, and Z. Jakielaszek, "35 GHz FMCW drone detection system," In 2016 17th International Radar Symposium (IRS), IEEE, pp. 1-4, 2016.
2 R. Nakamura, H. Hadama, and A. Kajiwara, "Ultra-wideband radar reflectivity of a drone in millimeter wave band," IEICE Communications Express, vol. 13, no. 4, pp. 341-346. 2018.
3 Y. Yoon, S. Lee, B. Lee, S. Kim, and C. Lee, "Enhanced clutter removal and peak detection methods for localization using IR-UWB radar," International Conference on Information and Communication Technology Convergence (ICTC), pp. 313-317, 2017.
4 G. Lee, S. Gang, and U Lee, "Radar image interfering signal removed using the LMS adaptive filter," The Proceeding of the Korean Institute of Electromagnetic Engineering and Science, vol. 25, no. 2, pp. 3-9, 2014.
5 S. Yoo, S. Chung, D. Seol, and S. H. Cho, "Adaptive Clutter Suppression Algorithm for Detection and Positioning using IR-UWB Radar," 9th International Conference on Ultrawideband and Ultrashort Impulse Signals (UWBUSIS), Odessa, pp. 40-43, 2019.
6 S. Chen and X. Li, "A new CFAR algorithm based on variable window for ship target detection in SAR images," Signal, Image and Video Processing, vol. 13, no. 4, pp. 779-786, 2019.   DOI
7 M. Ezuma, O. Ozdemir, C. K. Anjinappa, W. A. Gulzar, and I. Guvenc, "Micro-UAV Detection with a Low-Grazing Angle Millimeter Wave Radar," 2019 IEEE Radio and Wireless Symposium (RWS), Orlando, FL, USA, pp. 1-4, 2019.
8 B. Lee, S. Lee, Y. Yoon, K. Park, and S. Kim, "Adaptive clutter suppression algorithm for human detection using IR-UWB radar," 2017 IEEE SENSORS, Glasgow, pp. 1-3, 2017.
9 A. D. de Quevedo, F. I. Urzaiz, J. G. Menoyo, and A. A. Lopez, "Drone detection and radar-cross-section measurements by RADAR," in IET Radar, Sonar & Navigation, vol. 13, no. 9, pp. 1437-1447, 2019.   DOI
10 B. K Kim, J. Park, S. J. Park, T. W. Kim, D. H. Jung, D. H. Kim, T. Kim, and S. O. Park, "Drone Detection with Chirp‐Pulse Radar Based on Target Fluctuation Models," ETRI Journal, vol. 40, no. 2, pp. 188-196, 2018.   DOI