MIMO radars with orthogonal waveforms: A novel approach for enhanced performance under swerling targets

Faran Awais Butt, Ijaz Haider Naqvi, Usman Riaz

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

MIMO radar technology has recently attracted attention of large number of research scientists and engineers. Over the last decade, phased array radars have been quite popular because of their beam forming capabilities. In this paper, we propose a novel scheme for an improved performance of radar systems by transmitting orthogonal waveforms from different antennas. We first investigate MIMO radar systems, with orthogonal transmitted waveforms, with regards to their utility for low SNR fluctuating targets. The results show that the conventional mono-static radars are incapable of dealing with low observable fluctuating targets. The highly sophisticated vehicular targets pose great challenge to the ground based radar systems. Thereafter, we propose an algorithm that exploits the time diversity in addition to inherent spatial diversity order of MIMO systems, thereby exploiting the target scintillations and improving the detection performance. The proposed scheme transmits waveforms separated in time such that they experience un-correlated channels. The proposed scheme outperforms monostatic radar and gives a gain of 12 dB with a 2 X 2 MIMO radar system.

Original languageEnglish
Title of host publication2017 IEEE 86th Vehicular Technology Conference, VTC Fall 2017 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-5
Number of pages5
ISBN (Electronic)9781509059355
DOIs
StatePublished - 2 Jul 2017
Externally publishedYes

Publication series

NameIEEE Vehicular Technology Conference
Volume2017-September
ISSN (Print)1550-2252

Bibliographical note

Publisher Copyright:
© 2017 IEEE.

Keywords

  • MIMO radars
  • Orthogonal waveforms
  • Radar cross section (RCS)
  • Swerling targets

ASJC Scopus subject areas

  • Computer Science Applications
  • Electrical and Electronic Engineering
  • Applied Mathematics

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