TY - GEN
T1 - A Novel Multi-Scan Joint Method for Slow-Moving Target Detection in the Strong Clutter via RPCA
AU - Su, Jia
AU - Cui, Guonan
AU - Li, Tao
AU - Fan, Yifei
AU - Tao, Mingliang
AU - Wang, Haitao
AU - Zhang, Xiang
N1 - Publisher Copyright:
© 2021 IEEE
PY - 2021
Y1 - 2021
N2 - Slow-moving target detection in strong clutter background is a critical issue for the ground-based radar system. To detect the slow-moving target effectively, a novel multi-scan joint target detection method via principal component analysis (RPCA) is proposed. For radar echoes, there are two useful properties: 1) Stationary ground clutters have low-rank property, since the clutters in adjacent scan intervals are almost similar; 2) Moving targets have the sparse characteristic, due to their variation of position and sparsely distributed. Thanks to these two properties, moving targets can be separated from the stationary clutters via RPCA. Compared with the moving target indicator (MTI) method, the experimental results demonstrate that the proposed algorithm not only can suppress clutters effectively, but also preserve the moving target as much as possible.
AB - Slow-moving target detection in strong clutter background is a critical issue for the ground-based radar system. To detect the slow-moving target effectively, a novel multi-scan joint target detection method via principal component analysis (RPCA) is proposed. For radar echoes, there are two useful properties: 1) Stationary ground clutters have low-rank property, since the clutters in adjacent scan intervals are almost similar; 2) Moving targets have the sparse characteristic, due to their variation of position and sparsely distributed. Thanks to these two properties, moving targets can be separated from the stationary clutters via RPCA. Compared with the moving target indicator (MTI) method, the experimental results demonstrate that the proposed algorithm not only can suppress clutters effectively, but also preserve the moving target as much as possible.
KW - clutter suppression
KW - robust principal component analysis(RPCA)
KW - Slow-moving target detection
UR - https://www.scopus.com/pages/publications/85129814675
U2 - 10.1109/IGARSS47720.2021.9554191
DO - 10.1109/IGARSS47720.2021.9554191
M3 - 会议稿件
AN - SCOPUS:85129814675
T3 - International Geoscience and Remote Sensing Symposium (IGARSS)
SP - 4787
EP - 4789
BT - IGARSS 2021 - 2021 IEEE International Geoscience and Remote Sensing Symposium, Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2021 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2021
Y2 - 12 July 2021 through 16 July 2021
ER -