Target localization accuracy gain in MIMO radar-based systems

Hana Godrich, Alexander M. Haimovich, Rick S. Blum

Research output: Contribution to journalArticlepeer-review

364 Scopus citations

Abstract

This paper presents an analysis of target localization accuracy, attainable by the use of multiple-input multiple-output (MIMO) radar systems, configured with multiple transmit and receive sensors, widely distributed over an area. The Cramer-Rao lower bound (CRLB) for target localization accuracy is developed for both coherent and noncoherent processing. Coherent processing requires a common phase reference for all transmit and receive sensors. The CRLB is shown to be inversely proportional to the signal effective bandwidth in the noncoherent case, but is approximately inversely proportional to the carrier frequency in the coherent case. We further prove that optimization over the sensors' positions lowers the CRLB by a factor equal to the product of the number of transmitting and receiving sensors. The best linear unbiased estimator (BLUE) is derived for the MIMO target localization problem. The BLUE's utility is in providing a closed-form localization estimate that facilitates the analysis of the relations between sensors locations, target location, and localization accuracy. Geometric dilution of precision (GDOP) contours are used to map the relative performance accuracy for a given layout of radars over a given geographic area.

Original languageEnglish (US)
Article number2046246
Pages (from-to)2783-2803
Number of pages21
JournalIEEE Transactions on Information Theory
Volume56
Issue number6
DOIs
StatePublished - Jun 2010

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Computer Science Applications
  • Library and Information Sciences

Keywords

  • Adaptive array
  • Cramer-Rao bound
  • Multiple-input multiple-output (MIMO) radar
  • Spatial processing
  • Target localization

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