TY - GEN
T1 - Multipath Ghosts Mitigation for Radar-based Positioning Systems
AU - Wang, Xunze
AU - Jia, Mu
AU - Meng, Xinjie
AU - Zhang, Tingting
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - Due to the existence of numerous scatters and reflectors, the multipath propagation which leads to false alarms (or ghost images) will be challenging for accurate radar sensing systems in complex environments. In this paper, we use the frequency modulated continuous wave radar to obtain the range-Doppler information of targets. Aiming at the ghost images in low signal to noise ratio (SNR) regimes, we try to extend the existing low-complexity multi-target ghost recognition solution in low SNR regimes. Generally, we try to fuse measurements from different radars and observations, respectively, to improve the target detection quality. Since there exist errors in both range/velocity measurements and radar positions, we adopt a particle based clustering algorithm, to guarantee the robustness of the solution. Simulations and numeric results are provided and analyzed.
AB - Due to the existence of numerous scatters and reflectors, the multipath propagation which leads to false alarms (or ghost images) will be challenging for accurate radar sensing systems in complex environments. In this paper, we use the frequency modulated continuous wave radar to obtain the range-Doppler information of targets. Aiming at the ghost images in low signal to noise ratio (SNR) regimes, we try to extend the existing low-complexity multi-target ghost recognition solution in low SNR regimes. Generally, we try to fuse measurements from different radars and observations, respectively, to improve the target detection quality. Since there exist errors in both range/velocity measurements and radar positions, we adopt a particle based clustering algorithm, to guarantee the robustness of the solution. Simulations and numeric results are provided and analyzed.
UR - https://www.scopus.com/pages/publications/85147006221
U2 - 10.1109/VTC2022-Fall57202.2022.10013061
DO - 10.1109/VTC2022-Fall57202.2022.10013061
M3 - 会议稿件
AN - SCOPUS:85147006221
T3 - IEEE Vehicular Technology Conference
BT - 2022 IEEE 96th Vehicular Technology Conference, VTC 2022-Fall 2022 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 96th IEEE Vehicular Technology Conference, VTC 2022-Fall 2022
Y2 - 26 September 2022 through 29 September 2022
ER -