ICASSP 2021accepted0 citations

Riemannian Geometric Optimization Methods for Joint Design of Transmit Sequence and Receive Filter of MIMO Radar

Jie Li, Guisheng Liao, Yan Huang, Arye Nehorai

Abstract

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 multipleinput 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.

BibTeX
@inproceedings{icassp2021_riemanniangeomet,
  title = {Riemannian Geometric Optimization Methods for Joint Design of Transmit Sequence and Receive Filter of MIMO Radar},
  author = {Jie Li and Guisheng Liao and Yan Huang and Arye Nehorai},
  booktitle = {ICASSP 2021},
  year = {2021}
}
Riemannian Geometric Optimization Methods for Joint Design of Transmit Sequence and Receive Filter of MIMO Radar · ICASSP 2021