Riemannian geometric optimization methods for joint design of transmit sequence and receive filter of MIMO radar

Jie Li, Guisheng Liao, Yan Huang, Arye Nehorai

Research output: Contribution to journalConference articlepeer-review

1 Scopus citations

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 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.

Original languageEnglish
Pages (from-to)4430-4434
Number of pages5
JournalICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume2021-June
DOIs
StatePublished - 2021
Event2021 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2021 - Virtual, Toronto, Canada
Duration: Jun 6 2021Jun 11 2021

Keywords

  • Constant-envelope constraint
  • Joint design
  • Multiple-input multiple-output (MIMO) radar
  • Product manifold
  • Riemannian optimization

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