| Paper ID | SAM-3.6 |
| Paper Title |
Riemannian Geometric Optimization Methods for Joint Design of Transmit Sequence and Receive Filter of MIMO Radar |
| Authors |
Jie Li, Nanjing University of Aeronautics and Astronautics, China; Guisheng Liao, Xidian University, China; Yan Huang, Southeast University, China; Arye Nehorai, Washington University in St. Louis, United States |
| Session | SAM-3: MIMO Radar Array Processing |
| Location | Gather.Town |
| Session Time: | Wednesday, 09 June, 16:30 - 17:15 |
| Presentation Time: | Wednesday, 09 June, 16:30 - 17:15 |
| Presentation |
Poster
|
| Topic |
Sensor Array and Multichannel Signal Processing: [RAS-MIMO] MIMO Radar and waveform design |
| IEEE Xplore Open Preview |
Click here to view in IEEE Xplore |
| Virtual Presentation |
Click here to watch in the Virtual Conference |
| Abstract |
To maximize the signal-to-interference-plus-noise ratio (SINR) under a constant-envelope (CE) constraint, efficient joint design of the transmit waveform and the receive filter for colocated multiple-input multiple-output (MIMO) radars is essential. In this paper, we propose a novel optimization framework for solving the resultant non-convex problem over a Riemannian product manifold. Based on the Riemannian structure of the formulated manifold, three Riemannian product manifold-based optimization algorithms are proposed to solve the reformulated problem efficiently. The proposed algorithms provably converge to an approximate local optimum from an arbitrary initialization point. Numerical experiments demonstrate the algorithmic advantages and performance gains of the proposed algorithms. |
