Abstract

A minimum dispersion based beamformer is developed for multiple-input multiple-output (MIMO) radar. In statistics, dispersion is defined as the expectation of the pth power of the modulus of a random variable, which can be considered as a generalization of variance with p = 2. By noticing that the linear combination of the transmitted waveforms at the target location exhibits non-Gaussian property, we adopt the minimum dispersion criterion at the receiver instead of the widely used minimum variance criterion, which implicitly exploits non-Gaussianity and hence improves the performance of the beamformer. Simulation results are provided to demonstrate the robustness and accuracy of the proposed method compared with the conventional beamforming techniques.

Original languageEnglish (US)
Title of host publication2016 IEEE Radar Conference, RadarConf 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509008636
DOIs
StatePublished - Jun 3 2016
Event2016 IEEE Radar Conference, RadarConf 2016 - Philadelphia, United States
Duration: May 2 2016May 6 2016

Other

Other2016 IEEE Radar Conference, RadarConf 2016
CountryUnited States
CityPhiladelphia
Period5/2/165/6/16

Keywords

  • Beamforming
  • MIMO radar
  • non-Gaussian signal
  • statistical dispersion

ASJC Scopus subject areas

  • Signal Processing
  • Computer Networks and Communications
  • Instrumentation

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  • Cite this

    Jiang, X., & Bliss, D. (2016). Minimum statistical dispersion beamforming for MIMO radar. In 2016 IEEE Radar Conference, RadarConf 2016 [7485161] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/RADAR.2016.7485161