TY - GEN
T1 - ANM-Based Low-Complexity STAP Method for Off-Grid Clutter Spectrum Estimation
AU - Yu, Fei
AU - Li, Zhongyu
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Space-time adaptive processing(STAP) based on sparse recovery(SR-STAP) is a high-efficiency method for clutter suppression, which can obtain excellent suppression performance with a small number of snapshots. However, using the discrete dictionary in SR-STAP will cause the off-grid problem, that is, the dictionary atoms do not match the clutter ridge, which will degrade the clutter suppression performance. In this paper, a low-complexity STAP method based on atomic norm minimization(ANM) method is proposed to overcome this issue. In the proposed method, the ANM method is used to avoid off-grid problem, and the dimension of the constraint matrix is reduced under the inspiration of the decoupling ANM(DANM) method. Then, a fast iterative algorithm based on augmented lagrange multiplier(ALM) method is derived to further reduce the computational complexity. Finally, the simulation proves the effectiveness of proposed method.
AB - Space-time adaptive processing(STAP) based on sparse recovery(SR-STAP) is a high-efficiency method for clutter suppression, which can obtain excellent suppression performance with a small number of snapshots. However, using the discrete dictionary in SR-STAP will cause the off-grid problem, that is, the dictionary atoms do not match the clutter ridge, which will degrade the clutter suppression performance. In this paper, a low-complexity STAP method based on atomic norm minimization(ANM) method is proposed to overcome this issue. In the proposed method, the ANM method is used to avoid off-grid problem, and the dimension of the constraint matrix is reduced under the inspiration of the decoupling ANM(DANM) method. Then, a fast iterative algorithm based on augmented lagrange multiplier(ALM) method is derived to further reduce the computational complexity. Finally, the simulation proves the effectiveness of proposed method.
KW - atomic norm minimization(ANM)
KW - augmented lagrange multiplier(ALM)
KW - off-grid
KW - space-time adaptive processing(STAP)
KW - sparse recovery(SR)
UR - https://www.scopus.com/pages/publications/85169936487
U2 - 10.1109/ICET58434.2023.10211628
DO - 10.1109/ICET58434.2023.10211628
M3 - 会议稿件
AN - SCOPUS:85169936487
T3 - 2023 6th International Conference on Electronics Technology, ICET 2023
SP - 1462
EP - 1466
BT - 2023 6th International Conference on Electronics Technology, ICET 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 6th International Conference on Electronics Technology, ICET 2023
Y2 - 12 May 2023 through 15 May 2023
ER -