Range compression and waveform optimization for MIMO radar: A Cramér-Rao bound based study

Jian Li, Luzhou Xu, Petre Stoica, Keith W. Forsythe, Daniel W. Bliss

Research output: Contribution to journalArticle

227 Scopus citations

Abstract

A multi-input multi-output (MIMO) radar system, unlike standard phased-array radar, can transmit via its antennas multiple probing signals that may be correlated or uncorrelated with each other. This waveform diversity offered by MIMO radar enables superior capabilities compared with a standard phased-array radar. One of the common practices in radar has been range compression. We first address the question of "to compress or not to compress" by considering both the Cramér-Rao bound (CRB) and the sufficient statistic for parameter estimation. Next, we consider MIMO radar waveform optimization for parameter estimation for the general case of multiple targets in the presence of spatially colored interference and noise. We optimize the probing signal vector of a MIMO radar system by considering several design criteria, including minimizing the trace, determinant, and the largest eigenvalue of the CRB matrix. We also consider waveform optimization by minimizing the CRB of one of the target angles only or one of the target amplitudes only. Numerical examples are provided to demonstrate the effectiveness of the approaches we consider herein.

Original languageEnglish (US)
Pages (from-to)218-232
Number of pages15
JournalIEEE Transactions on Signal Processing
Volume56
Issue number1
DOIs
StatePublished - Jan 1 2008
Externally publishedYes

Keywords

  • Cramér &-Rao bound (CRB)
  • Cramér-Rao bound (CRB)
  • MIMO radar
  • Space-time adaptive processing (STAP)
  • Waveform optimization

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering

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