TY - JOUR
T1 - Riemannian geometric optimization methods for joint design of transmit sequence and receive filter of MIMO radar
AU - Li, Jie
AU - Liao, Guisheng
AU - Huang, Yan
AU - Nehorai, Arye
N1 - Funding Information:
This work was supported in part by National NSF of China under Grant 61631020, 61931011, 61827801.
Publisher Copyright:
© 2021 IEEE
PY - 2021
Y1 - 2021
N2 - To maximize the signal-to-interference-plus-noise ratio (SINR) under a constant-envelope constraint, an efficient joint design of the transmit waveform and the receive filter for multiple-input multiple-output (MIMO) radars is essential. In this paper, we propose a novel optimization framework to solve the resultant non-convex problem on a Riemannian product manifold. Based on the Riemannian structure of the formulated manifold, three Riemannian gradient-based methods are proposed to deal with the reformulated problem efficiently. The proposed algorithms provably converge to a local optimum from an arbitrary initialization point. Numerical experiments demonstrate the algorithmic advantages and performance gains of the proposed algorithms.
AB - To maximize the signal-to-interference-plus-noise ratio (SINR) under a constant-envelope constraint, an efficient joint design of the transmit waveform and the receive filter for multiple-input multiple-output (MIMO) radars is essential. In this paper, we propose a novel optimization framework to solve the resultant non-convex problem on a Riemannian product manifold. Based on the Riemannian structure of the formulated manifold, three Riemannian gradient-based methods are proposed to deal with the reformulated problem efficiently. The proposed algorithms provably converge to a local optimum from an arbitrary initialization point. Numerical experiments demonstrate the algorithmic advantages and performance gains of the proposed algorithms.
KW - Constant-envelope constraint
KW - Joint design
KW - Multiple-input multiple-output (MIMO) radar
KW - Product manifold
KW - Riemannian optimization
UR - http://www.scopus.com/inward/record.url?scp=85114964072&partnerID=8YFLogxK
U2 - 10.1109/ICASSP39728.2021.9413665
DO - 10.1109/ICASSP39728.2021.9413665
M3 - Conference article
AN - SCOPUS:85114964072
SN - 1520-6149
VL - 2021-June
SP - 4430
EP - 4434
JO - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
JF - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
T2 - 2021 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2021
Y2 - 6 June 2021 through 11 June 2021
ER -