TY - JOUR
T1 - Unique Decomposition and a New Model for the Ground Moving Target Indication Problem
AU - Li, Qingna
AU - He, Li
AU - Qi, Lijuan
AU - Wang, Robert
N1 - Publisher Copyright:
© 2017, Springer Science+Business Media New York.
PY - 2017/4/1
Y1 - 2017/4/1
N2 - In wide-area surveillance radar systems, ground moving target indication is the main task. The underlying mathematical problem is to decompose a complex matrix into a low rank matrix and a structured sparse matrix. In this paper, we show that such decomposition has a unique solution under reasonable assumptions. We propose a phase-based model to fully describe the special sparse structure. An alternating direction method of multipliers is implemented to solve the resulting nonconvex complex matrix problem. Simulation results verify the superior efficiency and the improvement of the new model.
AB - In wide-area surveillance radar systems, ground moving target indication is the main task. The underlying mathematical problem is to decompose a complex matrix into a low rank matrix and a structured sparse matrix. In this paper, we show that such decomposition has a unique solution under reasonable assumptions. We propose a phase-based model to fully describe the special sparse structure. An alternating direction method of multipliers is implemented to solve the resulting nonconvex complex matrix problem. Simulation results verify the superior efficiency and the improvement of the new model.
KW - Alternating direction method
KW - Ground moving target indication
KW - Robust principal component analysis
KW - Surveillance radar system
UR - http://www.scopus.com/inward/record.url?scp=85008698632&partnerID=8YFLogxK
U2 - 10.1007/s10957-016-1052-5
DO - 10.1007/s10957-016-1052-5
M3 - Article
AN - SCOPUS:85008698632
SN - 0022-3239
VL - 173
SP - 297
EP - 312
JO - Journal of Optimization Theory and Applications
JF - Journal of Optimization Theory and Applications
IS - 1
ER -