2021 IEEE International Conference on Acoustics, Speech and Signal Processing

6-11 June 2021 • Toronto, Ontario, Canada

Extracting Knowledge from Information

2021 IEEE International Conference on Acoustics, Speech and Signal Processing

6-11 June 2021 • Toronto, Ontario, Canada

Extracting Knowledge from Information
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Paper Detail

Paper IDSAM-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
SessionSAM-3: MIMO Radar Array Processing
LocationGather.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
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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.