Measurement matrix design for compressive sensing-based MIMO radar

Yao Yu, Athina P. Petropulu, H. Vincent Poor

Research output: Contribution to journalArticle

127 Scopus citations

Abstract

In colocated multiple-input multiple-output (MIMO) radar using compressive sensing (CS), a receive node compresses its received signal via a linear transformation, referred to as a measurement matrix. The samples are subsequently forwarded to a fusion center, where an 1-optimization problem is formulated and solved for target information. CS-based MIMO radar exploits target sparsity in the angle-Doppler-range space and thus achieves the high localization performance of traditional MIMO radar but with significantly fewer measurements. The measurement matrix affects the recovery performance. A random Gaussian measurement matrix, typically used in CS problems, does not necessarily result in the best possible detection performance for the basis matrix corresponding to the MIMO radar scenario. This paper considers optimal measurement matrix design with the optimality criterion depending on the coherence of the sensing matrix (CSM) and/or signal-to-interference ratio (SIR). Two approaches are proposed: the first one minimizes a linear combination of CSM and the inverse SIR, and the second one imposes a structure on the measurement matrix and determines the parameters involved so that the SIR is enhanced. Depending on the transmit waveforms, the second approach can significantly improve the SIR, while maintaining a CSM comparable to that of the Gaussian random measurement matrix (GRMM). Simulations indicate that the proposed measurement matrices can improve detection accuracy as compared to a GRMM.

Original languageEnglish (US)
Article number5955141
Pages (from-to)5338-5352
Number of pages15
JournalIEEE Transactions on Signal Processing
Volume59
Issue number11
DOIs
StatePublished - Nov 1 2011

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Electrical and Electronic Engineering

Keywords

  • Compressive sensing
  • direction of arrival (DOA) estimation
  • measurement matrix
  • multiple-input multiple-output (MIMO) radar

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