http://iet.metastore.ingenta.com
1887

High resolution estimation for sub-Gaussian stable signals in a linear array model

High resolution estimation for sub-Gaussian stable signals in a linear array model

For access to this article, please select a purchase option:

Buy article PDF
$19.95
(plus tax if applicable)
Buy Knowledge Pack
10 articles for $120.00
(plus taxes if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend Title Publication to library

You must fill out fields marked with: *

Librarian details
Name:*
Email:*
Your details
Name:*
Email:*
Department:*
Why are you recommending this title?
Select reason:
 
 
 
 
 
IET Signal Processing — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

The authors describe a high resolution subspace fitting (HRE) algorithm for robust estimation of direction of arrival (DOA) in the uniform linear array model with heavy-tailed signals and noise. Electromagnetic disturbances on telephone lines, atmospheric noise and underwater acoustic noise often exhibit heavy-tailed behaviour with differing characteristics. Although statistical models under Gaussian assumptions of signals and noise have been extensively investigated in the literature, there is limited research on robust methods in the non-Gaussian setting. A general model with sub-Gaussian α-stable signals is described, which includes the isotropic α-stable, and independent and dependent Gaussian models as special cases. It is shown that the HRE algorithm provides strongly consistent estimates of the DOAs. In addition, Monte Carlo simulation studies show that the proposed algorithm works extremely well for closely spaced targets, and outperforms the multiple signal classification-type algorithms for strongly dependent signals, both in the stable and the Gaussian cases.

References

    1. 1)
      • D. Johnson , D. Dudgeon . (1993) Array signal processing: concepts and techniques.
    2. 2)
      • A. Nehorai , P. Stoica . MUSIC, maximum likelihood and cramer-Rao bound. IEEE Trans. Acoust. Speech Signal Process. , 720 - 741
    3. 3)
    4. 4)
      • P. Stoica , K.C. Sharman . Maximum-likelihood methods for direction of arrival estimation. IEEE Trans. Signal Process. , 1132 - 1143
    5. 5)
    6. 6)
    7. 7)
    8. 8)
      • Schmidt, R.O.: `A signal subspace approach in multiple emitter location and spectral estimation', 1981, PhD, Stanford University, CA.
    9. 9)
      • R. Kumaresan , D.W. Tufts . Estimating the angles of arrival of multiple plane waves. IEEE Trans. Aerosp. Electron Syst. , 134 - 139
    10. 10)
      • B.D. Rao , K.V.S. Hari . Weighted subspace methods and spatial smoothing: analysis and comparison. IEEE Trans. Acoust. Speech Signal Process. , 2 , 788 - 803
    11. 11)
      • A.J. Weisss , B. Friedlander . ‘Performance analysis of spatial smoothing with interpolated arrays. IEEE Trans. Signal Process. , 5 , 1881 - 1892
    12. 12)
    13. 13)
      • Tsakalides, P., Nikias, C.: `Maximum-likelihood localization of sources in noise modeled as a Cauchy process', IEEE Military Communications Conf., 1995, 1994, 2, p. 613–617, MILCOM '95, Conference Record.
    14. 14)
      • Tsakalides, P., Nikias, C.: `Wideband array signal processing with alpha-stable distributions', IEEE Military Communications Conf., 1995, 1995, 1, p. 135–139, MILCOM '95, Conference Record.
    15. 15)
      • A.L. Swindlehurst , T. Kailath . A performance analysis of subspace-based methods in the presence of model errors, part I: the MUSIC algorithm. IEEE Trans. Signal Process. , 7 , 1758 - 1774
    16. 16)
      • S.U. Pillai . (1989) Array signal processing.
    17. 17)
      • G. Samorodnitsky , M.S. Taqqu . (1994) Stable non-Gaussian random processes: stochastic models with infinite variance.
    18. 18)
    19. 19)
      • Kannan, N.: `Estimation of directions of arrival in signal processing models', 1992, PhD, The Pennsylvania State University.
    20. 20)
      • D.E. Tyler . A distribution-free M-estimator of multivariate scatter. Ann. Stat. , 1 , 234 - 251
    21. 21)
      • Brown, C.L., Brcich, R.F., Zoubir, A.M.: `Adaptive ', Proc. Int. Symp. Applied Stochastic Models and Data Analysis (ASMDA), 2005.
    22. 22)
      • Tsakalides, P.: `Array signal processing with alpha-stable distributions', 1995, PhD, University of Southern California.
    23. 23)
      • Z.D. Bai , B.Q. Miao , C.R. Rao , S. Haykin . (1991) Estimation of direction of arrival of signals: asymptotic results, Advances in spectrum analysis and array processing.
    24. 24)
      • D.E. Tyler . Asymptotic inference for eigenvectors. Ann. Stat. , 725 - 736
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-spr_20060230
Loading

Related content

content/journals/10.1049/iet-spr_20060230
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading
This is a required field
Please enter a valid email address