Optimal Cognitive Beamforming for Target Tracking in MIMO Radar/Sonar

Nathan Sharaga, Joseph Tabrikian, Hagit Messer

Research output: Contribution to journalArticlepeer-review

49 Scopus citations

Abstract

In this paper, a cognitive beamforming method for target tracking by multiple-input multiple-output (MIMO) radar or sonar is proposed. In this method, at each step, the transmit beampattern is sequentially determined based on history observations. The conditional Bayesian Cramér-Rao bound (BCRB) for one-step prediction of the state-vector in target tracking problem was used as the optimization criterion for beampattern design. The proposed method is applied to the problem of target tracking in a shallow underwater environment in the presence of environmental uncertainties. It is shown that the method is able to automatically focus the transmit beampattern toward the target direction within a few steps at very low signal-to-noise ratios (SNRs). The method exhibits much better performance in terms of localization estimation error compared to other methods, such as orthogonal (omnidirectional) transmission.

Original languageEnglish
Article number7185382
Pages (from-to)1440-1450
Number of pages11
JournalIEEE Journal on Selected Topics in Signal Processing
Volume9
Issue number8
DOIs
StatePublished - 1 Dec 2015

Keywords

  • Cognitive beamforming
  • cognitive radar
  • sequential beamforming
  • sequential waveform design
  • target tracking
  • underwater acoustics

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering

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