• DocumentCode
    1880920
  • Title

    Extension of ESPRIT method to unknown noise environments

  • Author

    Wu, Qiang ; Reilly, James P.

  • Author_Institution
    Commun. Res. Lab., McMaster Univ., Hamilton, Ont., Canada
  • fYear
    1991
  • fDate
    14-17 Apr 1991
  • Firstpage
    3365
  • Abstract
    With the assumption that noise correlation is spatially limited, it is proposed to use two subarrays to eliminate the effects of unknown noise (UN). To find the estimate of the signal subspace, canonical decomposition is used. Direction-of-arrival (DOA) estimation is then carried out by using the spatial invariance between the two subarrays, which is similar to the methodology of ESPRIT. The method provides a consistent estimator for all spatially band limited noise. Numerical simulations have verified that when the noise spectrum is moderately rough, UN-ESPRIT gives acceptable performance, while ESPRIT fails at even relatively high SNRs. On the other hand, for a given number of sensors, UN-ESPRIT has smaller aperture than ESPRIT
  • Keywords
    matrix algebra; noise; signal processing; DOA estimation; ESPRIT; SNR; UN-ESPRIT; array signal processing; canonical decomposition; direction of arrival; matrix algebra; noise correlation; noise spectrum; numerical simulations; sensors; signal subspace; spatial invariance; spatially band limited noise; subarrays; unknown noise environments; Array signal processing; Direction of arrival estimation; Mathematical model; Mathematics; Matrix decomposition; Sensor arrays; Signal resolution; Spatial resolution; White noise; Working environment noise;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech, and Signal Processing, 1991. ICASSP-91., 1991 International Conference on
  • Conference_Location
    Toronto, Ont.
  • ISSN
    1520-6149
  • Print_ISBN
    0-7803-0003-3
  • Type

    conf

  • DOI
    10.1109/ICASSP.1991.150175
  • Filename
    150175